Course Overview

Research Methodology: R-Based Statistical Analysis and Scientific Report Writing

Instructor

• Md. Istiak Hossain Joy, Lecturer, Department of Agricultural Science (AGS), Daffodil International University (DIU).

• Dr. Shihab Uddin, Assistant Professor, Department of Soil Science, Bangladesh Agricultural University (BAU).

• Atiqur Rahman, Scientific Officer, Plant Breeding Division, Bangladesh Rice Research Institute (BRRI).

  ⏱ Duration: 06 Weeks | 16–18 Hours (10–12 Sessions) | Mode: Online (Google Meet) 

Course Description 

This micro-credential course equips agriculture and environmental science students with practical, workbench-level competencies in statistical data analysis, visualization using R and RStudio, academic thesis formulation, scientific report writing, and journal manuscript submission. Additionally, it provides structured coaching for agricultural research station job preparation, covering recruitment procedures, written technical assessments, and interview strategies.

Evidence of Demand 

Agriculture students often lack practical skills in advanced data analysis using RStudio, academic thesis writing, scientific report preparation, and journal article submission. They also have limited exposure to agricultural research station recruitment procedures, technical examinations, and interview preparation. These gaps reduce their readiness for higher education, research publication, and professional employment. Training in RStudio, data visualization, thesis composition, and job screening addresses this critical skill gap.

Purpose and Objectives 

The course aims to equip agriculture students with practical skills in advanced data analysis using RStudio, academic thesis writing, scientific report preparation, research article submission, and agricultural research station job preparation, enhancing their research competencies and career readiness.

Specific objectives include:

• Develop practical skills in statistical data analysis, interpretation, and visualization using R and RStudio.

• Equip learners with standard academic thesis writing, research organization, citation, and referencing conventions.

• Build competencies in scientific report writing, manuscript preparation, journal selection, and submission procedures.

• Prepare candidates for agricultural research station recruitment through guidance on written exams, technical assessments, and interview dynamics.

Course Content & Class Plan (Modules)

• Module 1: Introduction to Research Methodology and RStudio (2 hrs)

• Module 2: Statistical Data Analysis and Visualization Using R-Studio (4–5 hrs)

• Module 3: Academic Thesis Writing Guidelines (3–4 hrs)

• Module 4: Scientific Report Writing & Article Submission Guidelines (2 hrs)

• Module 5: Guidelines for Agricultural Research Station Job Preparation (2 hrs)

Practical

• Hands-on statistical analysis routines and scripting using RStudio via interactive Google Meet lab sessions.

• Data transformation, hypothesis testing, model interpretation, and graphic generation/data visualization exercises.

• Practical assignments structuring academic thesis chapters and reference lists.

• Manuscript drafting workshop: scientific report composition and mock journal submission workflows based on selected research topics.

Learning Outcomes 

After completing the course, participants will be able to:

• Conduct statistical data analysis and data visualization using R and RStudio.

• Prepare academic theses following standard writing, structuring, and referencing guidelines.

• Write scientific reports and research articles and navigate formal journal submission procedures.

• Apply strategic guidelines for agricultural research station recruitment examinations and interviews.

Target Audience & Requirements

• Target Audience:

• Undergraduate students in Agricultural Science or Environmental Science.

• MS students and early-career scientists working in agricultural research sectors.

• Entry Requirements:

• Background in Agricultural Science, Environmental Science, Soil Science, Genetics, or related biological disciplines.

• Basic computer literacy and fundamental knowledge of agricultural concepts.

• Access to a computer/laptop with R and RStudio installed and a stable internet connection.

• Minimum Age: 18 Years.

Career Pathways

 After completing this micro-credential, learners may:

• Work as Agricultural Research Assistant, Young/Undergraduate Researcher, or Quality Control Analyst (Agri-Tech).

• Successfully compete in recruitment examinations for national agricultural research stations (e.g., BRRI, BARI, BINA).

• Progress to Advanced Micro-Credentials, postgraduate higher studies (MS/PhD), or international research fellowships.

Tools & Resources

• Software & Digital Tools: R and RStudio software environment, Google Meet for live practical sessions.

• Facilities & Hardware: Personal computer or laptop with active internet connectivity.

• Learning Materials: Lecture slides, code scripts, demo agricultural datasets, thesis formatting guidelines, and job preparation briefs.

Assessment Criteria 

Aligned with Outcome-Based Education (OBE) frameworks:

• Practical Assignments (R-Studio Data Analysis & Visualization – LO1): 60%

• Report Writing Project based on Research Topic (Thesis & Article Writing – LO2 & LO3): 40% (Recommended Benchmarks: Minimum 80% attendance, minimum 60% pass score)

Financial Information & Certification

• Tentative Course Fee: BDT 1500/-

• Class Size: 30 to 60 participants (Maximum 60 per operational batch)

• Certification: Micro-Credential Certificate issued by DIU Micro-Credentials Academy upon successful assessment completion

Course Overview

Site Execution Management, Safety & EHS Management (Batch 02)

⏱ Duration: 30 Hours (Total) | Weekend (Friday/Saturday)

Course Description

This course aims to equip future site engineers and project managers with practical skills in structural execution supervision and comprehensive site safety management.

Instructor

1. Shafkat Ar Rahman (Lecturer, Department of Civil Engineering, DIU)
2. Faysal Ahmed (Senior Engineer, Daffodil International University)
3. Md. Rabiul Islam (Assistant Engineer, P&D. Specialist in Foundation Engineering & Site Safety)
4. Md. Tonmoy Alam (Assistant Engineer, P&D. Expert in High-Rise Structural Execution)

   Evidence of Demand

• There is a critical gap between academic theory and on-site reality in the construction sector.
• Many graduates lack practical supervision skills for structural execution and are unfamiliar with mandatory safety protocols (BNBC/EHS).
• Construction projects frequently face delays, quality issues, and safety hazards due to inadequate site management.
• Industry demands engineers who can enforce quality control and safety compliance simultaneously.

Course Objectives

This course aims to:

• Master field execution of Piling, Concreting, and Grid Alignment.
• Implement rigorous Site Safety protocols and EHS management.
• Ensure quality control through pre-pour/post-pour inspections.
• Manage labor and logistics effectively during critical phases.

Course Content & Class Plan (Modules)

Module 1: Structural Execution

• Cast-in-Situ Piling methods & Tremie Pipe concreting. * Structural Casting (Columns/Slabs) & Grid Alignment.
• Rebar checking & Reinforcement scheduling.

Module 2: Site Safety & EHS

• BNBC Safety Guidelines & Risk Assessment.
• PPE Compliance, Scaffolding Safety, & Fall Protection. * Emergency response & First Aid basics.

Module 3: Operational Management

• Holiday operations & Labor management.
• Pile Load Testing (PDA/PIT) interpretation.

Practical & Field Work (60% of Course)

• Mode of Delivery: Blended (Classroom Theory + 60% Field Work on active sites).
• Practical Activities: Site visits for Piling Rig observation & Safety Audits.

Learning Outcomes

Upon completion, participants will be able to:

• Supervise and validate Piling and Structural Casting operations.
• Execute precision Grid Line markings using surveying tools.
• Implement and enforce Site Safety protocols (EHS).
• Conduct Risk Assessments for hazardous site activities.
• Interpret technical test reports (Pile Load Test).

Target Audience:

• Civil Engineering Students (3rd/4th Year).
• Fresh Graduates seeking Site Engineer roles.
• Project Managers & Construction Interns.
• Site Supervisors looking to upskill.

Entry Requirements:

• Diploma or B.Sc. in Civil Engineering (or currently studying).
• Basic understanding of construction materials and structural drawings.
• Minimum Age: 20 Years.

Career Pathways

After completing this course, learners may progress to:

• Site Engineer / Senior Site Engineer.
• Project Manager.
• EHS Officer / Safety Manager.
• Quality Control (QC) Engineer.

Tools & Resources

• PPE (Helmets, Vests) for all students.
• Access to active DIU construction sites.
• Surveying instruments (Level machine/Total station).

Assessment Criteria

• Field Checklist (40%): Completing inspection cards on site.
• Safety Audit (30%): Identifying hazards in a mock site walkthrough.
• Final Quiz (30%): Theory on codes, calculations, and safety rules.

Tentative Course Fee:

• BDT 1,500 for Daffodil Student.

• BDT 3,000 for without Daffodil Student. 

Course Overview

Micro-Credential Course on Basics of Organic Agriculture

Instructor(s)

• Uswatun Hasana Hashi: Assistant Professor, Dept. of Agricultural Science, DIU; expert in sustainable agriculture.
• Md. Hanif Uddin Abir: Head of Product Development, INTEFA; 12 years of experience in bio/synthetic pesticides.

⏱ Duration: 10 Weeks | 20 Contact Hours (2 Hours per Week) | Equivalent to 1 Credit Hour Mode of Delivery: Hybrid (online + in-person sessions) Class Size: 20-25 participants

Course Description 

Basics of Organic Agriculture (MC55002) addresses the global organic food market's growth to $437B by 2026 and Bangladesh's rising demand for organic products. With increasing consumer preference for sustainable produce and government support for organic farming, this course equips learners with practical skills in soil management, crop production, and certification processes. Through hands-on training and field visits, participants will contribute to sustainable food systems and tap into local/export markets.

Evidence of Demand

• The global organic market's 10% CAGR and a 30% rise in Bangladesh's organic product demand highlight the need for skilled professionals.
• BARI notes 65% of farmers seek organic training, with job postings on bdjobs.com for organic specialists at firms like ACI Agribusiness, underscoring the course's relevance.

Course Objectives

This course aims to:

• Understand organic agriculture principles and practices.
• Develop skills in soil management, crop, and livestock production.
• Learn certification standards and marketing strategies.
• Promote sustainable farming and environmental conservation.

Course Content & Class Plan (Modules)

• Week 1: Intro to Organic Agriculture - Principles, history, market trends.
• Week 2: Soil Health - Composting, green manure, erosion control.
• Week 3: Organic Crop Production - Crop selection, pest management.
• Week 4: Organic Livestock - Feed, housing, integration.
• Week 5: Certification & Standards - USDA, EU standards, labeling.
• Week 6: Sustainable Practices - Agroecology, permaculture, water conservation.
• Week 7: Economics & Marketing - Cost analysis, market strategies.
• Week 8: Case Studies - Successful organic farms.
• Week 9: Practical Applications - Organic farming plan development.
• Week 10: Final Project & Viva - Organic farm plan presentation.

Practical & Field Work

• Conducting soil analysis demonstrations.
• Performing seed treatment in a laboratory setting.
• Designing permaculture tasks.
• Participating in marketing plan workshops.
• Visiting demonstration plots for field experience.
• Presenting an organic farm plan and participating in a viva.

Learning Outcomes

After completing the course, participants will be able to:

• Apply organic agriculture principles effectively.
• Design and implement organic farming systems.
• Navigate certification processes and market organic products.
• Contribute to sustainable food systems and conservation.

Target Audience & Requirements

• Target Audience: Farmers, agri-entrepreneurs, agriculture students, researchers, and environmental/sustainability enthusiasts.
• Entry Requirements: High school diploma or equivalent, with a minimum age of 18 years. A basic understanding of agriculture or biology is optional but helpful.

Career Pathways

After completing this micro-credential, learners may:

• Pursue roles as an Organic farmer, Agri-entrepreneur, Certification consultant, or Organic market specialist (e.g., roles in ACI Agribusiness, government projects).
• Follow a pathway to advanced studies in organic crop production or soil science.

Tools & Resources

• Statista reports, BARI manuals, FAO resources, and export case studies.
• Soil analysis tools, demonstration plots, organic guidelines, and certification guides.

Assessment Criteria

• Quizzes: 20%.
• Assignments: 20%.
• Practical projects: 30%.
• Final project & viva: 30%.

Financial Information

• Tentative Course Fee: 2,000 BDT.

Course Overview

RTL Design & Digital Logic Fundamentals for VLSI

⏱ Duration: 30–36 Hours (2 Credit Hours) | Mode: Physical / Hybrid

Instructor

• Md. Rasedul Islam, Assistant Professor, Daffodil International University (DIU).
• Md. Emad Hossain Likhon, Lecturer, Department of Computer Science and Engineering, Daffodil International University (DIU).
• M Rifat Hossain, Lecturer, Daffodil International University (DIU) – Ex-Ulkasemi Pvt. Limited (Trained in Analog Design, IC Mask Design/Mixed-Signal Layout, and IC Physical Design; Expert in Verilog RTL Design). (Endorsed by: Professor Dr. Sheak Rashed Haider Noori, Professor & Head, Department of Computer Science and Engineering, DIU)
• Md. Ashikur Rahman, Technical Manager, Design Verification & RTL, SILICONOVA LIMITED
• Akash Ghosh, Sr. Engineer, Design Verification & RTL, SILICONOVA LIMITED

Course Description 

This technical micro-credential course builds a strong, practical foundation in Digital Logic Design (DLD) and Register-Transfer-Level (RTL) coding using industry-standard hardware description languages (Verilog/VHDL). Designed as an essential feeder course for the semiconductor industry, it equips participants with hands-on skills to design, code, simulate, and verify combinational, sequential, and finite state machine (FSM) digital circuits, serving as a direct stepping stone into VLSI frontend and backend engineering careers.

Evidence of Demand 

Foundational digital logic and RTL design skills are a prerequisite for nearly all VLSI frontend and backend career tracks. However, many engineering students and fresh graduates lack this working knowledge at entry, creating a critical preparatory competency gap before they can join advanced semiconductor training or industry roles. Through industry consultation and job-market analysis, this course has been specifically identified as a foundational feeder program for learners aiming to enter advanced BSIA–SICIP semiconductor workforce development programs (such as Advanced Physical Design: RTL to GDSII and DFT and Verification Engineering for ASIC Designers), both of which require working RTL and digital-design proficiency upon entry.

Course Objectives

This course aims to:

• Build a strong foundation in Digital Logic Design (DLD) and Register-Transfer-Level (RTL) coding using industry-standard hardware description languages (Verilog/VHDL).
• Familiarize learners with semiconductor physics, CMOS logic gates, and gate-level timing and performance trade-offs.
• Develop practical competencies in designing combinational logic, sequential memory systems, and Finite State Machines (FSMs).
• Train participants to write synthesizable RTL code, construct testbenches, and perform waveform-based functional verification to prepare for VLSI design careers.

Course Content

• Module 1: Semiconductor & CMOS Fundamentals – MOSFET Device Physics, CMOS Logic Gates, and CMOS Inverter (Concept lecture and logic simplification exercises).
• Module 2: Gate-Level Performance & Timing Analysis – RC Delay Models, Power & Speed Trade-offs (Circuit design & simulation exercises).
• Module 3: Combinational Logic Circuit Design – Karnaugh Maps, Boolean simplification, Adders, subtractors, multiplexers, demultiplexers, encoders, and decoders (Circuit design & simulation exercises).
• Module 4: Sequential Logic & Memory Systems – Bistable Circuits, Timing Constraints, Registers & Counters (Hands-on sequential circuit lab).
• Module 5: Finite State Machines (FSM) — Design and Implementation – Control logic state diagrams and implementation (FSM design workshop).
• Module 6: Introduction to Verilog/VHDL — Syntax, Data Types, and Constructs – Hardware description fundamentals (HDL coding lab).
• Module 7: RTL Coding Practices — Writing Synthesizable Code – Industry coding standards for hardware synthesis (Guided synthesizable-code exercises).
• Module 8: Simulation and Functional Verification Basics – Testbenches and Waveform Analysis (Testbench writing & waveform analysis lab).
• Module 9: Capstone — Design, Code, and Simulate a Simple Digital Module – End-to-end digital module implementation from specification to verified functionality (Capstone project).

Practical

• Circuit Design & SPICE Simulation Labs: Hands-on logic simplification, RC delay modeling, combinational circuit design, and sequential register/counter evaluation using SPICE simulation tools.
• FSM Design Workshop: Practical state-machine architecture planning and control logic implementation.
• HDL & Synthesizable RTL Coding Labs: Writing structured, synthesizable Verilog/VHDL code in professional development environments.
• Functional Verification & Capstone Project: Writing self-checking testbenches, analyzing simulation waveforms, and completing an end-to-end digital module design from specification to verified functionality.

Learning Outcomes

After completing the course, participants will be able to:

• Explain Semiconductor & CMOS Fundamentals.
• Explain Gate-Level Performance & Timing Analysis.
• Design combinational circuits and sequential circuits.
• Design and implement finite state machines (FSMs) for control logic.
• Write RTL code in Verilog/VHDL using correct syntax and synthesizable coding practices.
• Complete a capstone project — design, code, and simulate a digital module from specification to verified functionality.

Target Audience & Requirements

• Target Audience:
• Undergraduate students and fresh graduates in EEE, ECE, CSE, ICE, or RME interested in entering VLSI and semiconductor design careers.
• Entry Requirements:
• Undergraduate student or graduate in EEE, ECE, CSE, ICE, RME, or a related engineering discipline.
• Basic familiarity with introductory electronics and computer operation (serves as an entry-level preparatory course for advanced VLSI tracks).

Career Pathways

After completing this micro-credential, learners may:

• Apply for entry-level semiconductor roles such as Junior RTL Design Engineer, Digital Logic Design Intern, Trainee Engineer (IC Physical Design), Trainee Engineer (IC Mask Design), Trainee Engineer (Design Verification - DV), VLSI Physical Design Trainer, or VLSI Layout Design Trainer.
• Progress directly into Advanced Micro-Credentials and specialized industry tracks, including BSIA–SICIP's Advanced Physical Design: RTL to GDSII and DFT and Verification Engineering for ASIC Designers.

Tools & Resources

• Facilities & Equipment:
• FPGA and VLSI simulation laboratory access.
• Computers configured with Verilog/VHDL development environments.
• Tools, Instruments & Software:
• HDL Simulation Tools: Xilinx Vivado, ModelSim, Questa, or equivalent academic-licensed simulators.
• SPICE Simulation Software: LTSpice, QSpice, or equivalent circuit simulators.
• Learning Materials:
• Course syllabus, lecture slides, logic simplification worksheets, sample RTL design exercises, and functional verification testbenches.

Assessment Criteria

Aligned with Course Learning Outcomes (LO1–LO6):

• Hands-on Lab & Coding Exercises across Modules 1–8 (Assesses LO1–LO5) – 50%
• Capstone Project: Digital Module Design, Code & Simulation Report in Module 9 (Assesses LO6) – 40%
• Class Participation & Engagement (Supports All LOs) – 10% (Recommended Benchmarks: Minimum 80% attendance and minimum 60% overall assessment pass score)

Financial Information, Remuneration & Certification

• Tentative Course Fee: BDT 3,000
• Certification: Micro-Credential Certificate (2 Credit Hours) issued by DIU Micro-Credentials Academy (DIU-MCA)

Course Overview

Management Information Systems: An Industry Approach Application 

⏱ Duration: 5 Weeks | 20–22 Hours (2 Classes per Week on Friday/Saturday; 2 Hours per Class) | Mode: Blended Learning (Interactive Lectures + Applied Lab Demonstrations + Industry Workshops)

Instructor

• Md. Mahbobor Rahaman, Senior Lecturer, Department of Business Administration, Daffodil International University (DIU).
• Md. Moshiur Rahman, Head of MIS, PRAN Industrial Park, PRAN RFL Group.
• Maria Islam, Lecturer, Department of Business Administration, Daffodil International University (DIU).

Course Description 

This industry-oriented micro-credential course equips learners with practical knowledge and hands-on competencies in Management Information Systems (MIS). Bridging the gap between academic theory and enterprise operations, the course trains participants to leverage digital technologies, enterprise systems (ERP, CRM, SCM), business intelligence tools, cybersecurity governance, and AI-driven workflows to solve real-world business challenges and drive strategic organizational performance.

Evidence of Demand 

The rapid digital transformation of industries has created strong demand for professionals with practical Management Information Systems (MIS) skills. Organizations across banking, healthcare, manufacturing, retail, logistics, government, and e-commerce increasingly depend on digital technologies, business analytics, ERP, cloud computing, cybersecurity, and AI to improve performance and support strategic decisions. In Bangladesh, initiatives such as Smart Bangladesh 2041, digital government services, fintech expansion, and Industry 4.0 are accelerating the need for industry-ready MIS professionals. Despite this demand, many graduates lack hands-on experience with enterprise systems and data-driven decision-making. This micro-credential course bridges the gap by equipping learners with practical, industry-oriented MIS competencies that align with current employer expectations and emerging digital workforce requirements.

Course Objectives 

This course aims to equip learners with practical knowledge and industry-relevant skills in Management Information Systems, enabling them to leverage digital technologies, enterprise systems, and data-driven decision-making to improve business performance.

Upon successful completion, learners will be able to:

• Explain the strategic role of MIS in modern organizations.
• Analyze business processes using enterprise information systems and apply digital technologies to support organizational decision-making.
• Utilize Business Intelligence and data visualization tools.
• Understand ERP, CRM, SCM, and cloud-based business systems.
• Evaluate cybersecurity, data privacy, and ethical issues in MIS.
• Develop practical solutions for real business challenges using information systems.

Course Content

 A 20-hour comprehensive hands-on curriculum across 7 modules:

• Module 1: Introduction to Management Information Systems (2 Hours) – Fundamentals of IS and MIS, components and types of Information Systems, role of MIS in modern organizations, information as a strategic resource, digital transformation, and Industry 4.0.
• Module 2: Business Processes and Enterprise Information Systems (4 Hours) – Business processes and workflow automation, Business Process Reengineering (BPR), Functional Information Systems (HRIS, AIS, MKIS, FIS), Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), and Supply Chain Management (SCM).
• Module 3: Business Data Management and Database Systems (3 Hours) – Business data vs. information, database concepts, Database Management Systems (DBMS), data warehouses and data lakes, Big Data fundamentals, and data quality and governance.
• Module 4: Business Intelligence and Decision Support Systems (3 Hours) – Decision Support Systems (DSS), Executive Information Systems (EIS), Business Intelligence (BI) concepts, data visualization principles, Key Performance Indicators (KPIs), and dashboard design.
• Module 5: Cybersecurity, Ethics, and Information Governance (3 Hours) – Information security fundamentals, organizational cybersecurity threats, data privacy and protection, business continuity planning, ethical issues in MIS, AI ethics and governance, and regulatory compliance (GDPR and Bangladesh ICT/Cyber Security Act overviews).
• Module 6: Emerging Technologies and AI in MIS (3 Hours) – Artificial Intelligence in business, Machine Learning applications, Robotic Process Automation (RPA), Generative AI for business operations, predictive analytics, smart business systems, and future MIS careers.
• Module 8 (7): Industry Case Studies (2 Hours) – Digital transformation strategies, MIS implementation challenges, industry best practices, change management, project management basics, and career pathways in MIS.

Practical

• Enterprise Workflow & Process Mapping: Analyzing organizational workflows, conducting Business Process Reengineering (BPR), and simulating functional operations across ERP, CRM, SCM, and HRIS platforms.
• Database & Big Data Architecture Labs: Structuring business data within Database Management Systems (DBMS) and evaluating data quality and governance models.
• BI Dashboard Design & KPI Visualization: Hands-on laboratory demonstrations building Decision Support Systems (DSS) and interactive KPI dashboards using Business Intelligence visualization principles.
• AI Operations & Industry Case Projects: Applying Generative AI and RPA concepts to business operations, auditing cybersecurity/compliance risks, and delivering an end-to-end Industry Project Presentation.

Learning Outcomes

After completing the course, participants will be able to:

• Analyze organizational business processes using enterprise information systems.
• Apply business intelligence tools to support managerial decision-making.
• Evaluate enterprise technologies including ERP, CRM, SCM, cloud computing, and AI.
• Identify cybersecurity risks, ethical challenges, and governance issues in organizational information systems.
• Demonstrate practical MIS solutions for real-world business problems using industry-standard digital tools.

Target Audience & Requirements

• Target Audience:
• Students of MIS, Business Administration, Business Technology Management, Computer Science, Information Technology, Information Technology Management, or other related departments.
• Entry Requirements:
• Undergraduate students from any related discipline.
• Basic computer and technology literacy.
• No programming knowledge required.
• Minimum Age: 18 Years.

Career Pathways

After completing this micro-credential, learners may:

• Earn 1 Credit Hour within the DIU-MCA framework.
• Transition into MIS Executive, Business Analyst, ERP Associate, IT Project Coordinator, or Digital Transformation roles across banking, manufacturing, retail, logistics, and fintech.
• Progress into higher-tier technological specializations and global professional certifications, including Microsoft Power BI, SAP, Oracle, Salesforce, and Google Data Analytics.

Tools & Resources

• Facilities & Equipment:
• Dedicated Computer Lab and fully technology-equipped multimedia classrooms.
• Access to the DIU Learning Management System (LMS).
• Tools, Instruments & Software:
• Enterprise Information Systems (ERP, CRM, SCM) demonstration environments.
• Database Management Systems (DBMS), Business Intelligence (BI) & KPI dashboard visualization tools, and Generative AI/RPA business tools.
• Learning Materials:
• Module lecture slides, industry case study briefs, lab exercise workbooks, and regulatory compliance guides (GDPR & Bangladesh ICT/Cyber Security Act).

Assessment Criteria Fully mapped to an Outcome-Based Education (OBE) scheme:

• Industry Project Presentation – 25%
• Module-based Quizzes – 20%
• Practical Lab Exercises – 20%
• Case Study Analysis – 20%
• Final Assessment / Viva – 15%

Financial Information, Remuneration & Certification

• Tentative Course Fee: 5,000 BDT (DIU Students / Alumni) | 6,500 BDT (External Candidates)
• Certification: Micro-Credential Certificate (1 Credit Hour equivalent) issued by DIU Micro-Credentials Academy upon successful completion

Course Overview

AI-Driven UI/UX & Product Design Career Track

⏱ Duration: Approx. 24 Weeks | 72 Contact Hours (48 Classes × 1.5 Hours; 2 Classes per Week on Monday & Thursday at 9:00 PM – 10:30 PM) | Mode: Online

Instructor

• Ayesha Siddika, Assistant Professor, Department of Software Engineering, Daffodil International University (DIU), and PhD Researcher in Computer Science and Engineering.
• Imam Hossain, Lead Software Engineer (Exoveon Limited), PMP-Certified IT Leader, Technology Consultant, and PhD Researcher in AI-based Software Testing.
• Sohanul Habib, Senior UI/UX & Product Designer with 8+ years of industry experience in SaaS, fintech, enterprise, and digital product design.

Course Description

This career-track micro-credential course equips learners with practical, job-oriented UI/UX and Product Design skills spanning the complete digital product lifecycle—from problem framing and generative UX research through responsive interface design, scalable design systems, AI-assisted prototyping, usability evaluation, and developer handoff. Divided into two comprehensive levels (UI Design Foundation and Product Design & UX Professional), the course emphasizes hands-on Figma execution, evidence-based design decisions, cross-functional collaboration, and building portfolio-ready product case studies.

Evidence of Demand 

Digital product design increasingly requires professionals who can integrate interface design, user research, accessibility, prototyping, design systems, developer collaboration, and AI-assisted workflows. The U.S. Bureau of Labor Statistics projects 7% employment growth for web developers and digital designers from 2024 to 2034, creating approximately 14,500 openings annually. Furthermore, the World Economic Forum Future of Jobs Report 2025 identifies creative thinking (57%), technological literacy (51%), empathy and active listening (50%), AI and big data (45%), and design and user experience (25%) among core employer-demanded skills. Evolving industry standards—including W3C WCAG 2.2 accessibility guidelines and Figma's Variables, Dev Mode, Figma Make, and MCP workflows—further drive the need for structured training in AI-integrated product design and design-to-development collaboration.

Purpose and Objectives

This course aims to:

• Equip learners with practical, job-oriented UI/UX and Product Design skills from problem framing and research through responsive interface design and developer handoff.
• Build advanced proficiency in Figma, including components, variants, Auto Layout, variables, design tokens, and interactive prototyping.
• Integrate WCAG 2.2 accessibility standards, visual design principles, and scalable atomic design systems into real-world workflows.
• Train participants in AI-assisted product design, prompt engineering for designers, and MCP-enabled functional prototyping.
• Guide learners through generative and evaluative UX research, product strategy, usability testing, and three collaborative case studies to build an industry-ready portfolio.

Course Content

Level 1 – UI Design Foundation (26 Classes)

• Module 1: Orientation, UI/UX Foundations & Figma Basics (4 Classes) – Figma setup, Education plan, workspace structure; UI vs. UX vs. graphic design, designer roles; UX Honeycomb, Human-Centered Design (HCD); product types (mobile, web, SaaS) and AI landscape.
• Module 2: Practical UI Analysis & Accessibility (2 Classes) – Real-life UI analysis, structured interface recreation, and WCAG 2.2 foundations (contrast, readability, focus, target size, labels, accessible interaction).
• Module 3: Problem Solving, IA & Wireframing (4 Classes) – Problem framing, brainstorming, affinity mapping; card sorting, Information Architecture (IA), sitemaps, user flows; low-, mid-, and high-fidelity wireframing for mobile and web.
• Module 4: Visual Design Foundations & Product Process (4 Classes) – Color theory (60-30-10 rule, gradients, color-blindness considerations); typography scales and hierarchy; shadows, elevation, spacing, Golden Ratio; Double Diamond process, Agile vs. Waterfall, and dashboard practice.
• Module 5: Components, Variants & Interactive Prototyping (2 Classes) – Reusable components, properties, states, advanced variants, interactive components, and complex prototyping.
• Module 6: Auto Layout, Responsive Design & Grid Systems (4 Classes) – Auto Layout fundamentals and nested patterns; responsive web/mobile breakpoints, adaptive interfaces, grid systems, and layout constraints.
• Module 7: Variables, Design Systems & Developer Handoff (6 Classes) – Figma Variables and Tokens (types, collections, aliases, modes for color, type, spacing, themes, localization); atomic design systems, documentation, governance; Team Libraries; Dev Mode, annotations, specs, and developer handoff.

Level 2 – Product Design & UX Professional (22 Classes)

• Module 8: AI-Assisted Product Design & Prompting (3 Classes) – AI fundamentals, responsible AI use, AI agents, prompt engineering for designers; Figma Make / Figma AI and MCP-enabled workflows for ideation and functional prototyping.
• Module 9: Generative UX Research, Persona & Storyboarding (3 Classes) – Research planning (interviews, surveys, question design); research synthesis, user personas, empathy mapping, storyboarding, and insight communication.
• Module 10: Product Strategy & Prioritization (2 Classes) – Competitor/comparative analysis, SWOT, opportunity mapping; Kano Model, MoSCoW prioritization, user journeys, and feature definition.
• Module 11: UX Laws, Evaluation & Experimentation (4 Classes) – Core UX laws and cognitive principles; quantitative vs. qualitative and generative vs. evaluative research; usability testing, heuristic and accessibility evaluation; A/B testing, analytics, and research reporting.
• Module 12: Collaborative Product Projects & Case Studies (6 Classes) – Execution of three end-to-end Group Projects (2 classes each) covering topic selection, teamwork, design execution, presentation, and structured critique.
• Module 13: Portfolio, Career & Freelancing Preparation (4 Classes) – Portfolio and case-study storytelling; CV, LinkedIn, interview prep, and design challenge guidance; freelancing profiles, proposals, pricing, client communication, and final portfolio QA.

Practical 

• Interface Recreation & Responsive Wireframing: Hands-on UI analysis, WCAG 2.2 accessibility auditing, information architecture mapping, and multi-device wireframing.
• Design System & Token Architecture: Building scalable component libraries with Figma Variables, multi-mode tokens (light/dark/localization), Auto Layout, and Dev Mode handoff specs.
• AI-Assisted Functional Prototyping: Utilizing prompt engineering, Figma Make/AI, and MCP workflows to generate, critique, and iterate interactive product concepts.
• UX Research & Usability Testing Labs: Conducting user interviews, synthesizing personas, applying Kano/MoSCoW prioritization, running heuristic/usability evaluations, and executing three collaborative product case studies.

Learning Outcomes

After completing the course, participants will be able to:

• Translate real product problems into information architecture, user flows, wireframes, responsive high-fidelity interfaces, and interactive prototypes.
• Use Figma professionally, including components, variants, Auto Layout, grids, variables, tokens, modes, libraries, and advanced prototyping.
• Apply visual-design fundamentals and WCAG 2.2 accessibility principles to create clearer, more inclusive interfaces.
• Build scalable design systems and prepare professional design-to-development handoff using Dev Mode, specifications, and reusable system assets.
• Plan and synthesize UX research, prioritize product opportunities, and evaluate designs through heuristics, usability testing, A/B testing, accessibility checks, surveys, and analytics.
• Use AI-assisted design and prompting workflows responsibly for research support, ideation, prototyping, critique, and iteration.
• Produce collaborative product case studies and a portfolio-ready body of work for UI/UX, Product Design, internship, freelance, or junior-role opportunities.

Target Audience & Requirements

• Target Audience:
• Aspiring UI/UX and Product Designers.
• Graphic or web designers looking to upskill.
• CS/IT or business students.
• Freelancers and professionals transitioning into digital product design.
• Entry Requirements:
• Basic computer literacy is required.
• No prior UI/UX experience is necessary; familiarity with web or mobile applications and basic English is recommended.
• Minimum Age: 16 Years.

Career Pathways

After completing this micro-credential, learners may:

• Work in junior UI/UX Designer, Product Designer, UX Researcher, or Interaction Designer roles, as well as internships and global freelance positions.
• Progress to advanced specializations in Product Design, UX Research, Interaction/Motion Design, Design Systems Architecture, Product Strategy, and Frontend Collaboration.

Tools & Resources

• Facilities & Equipment:
• Laptop or desktop computer with reliable internet connectivity.
• Presentation display/projector and digital whiteboard for collaborative critiques.
• Tools, Instruments & Software:
• Figma account (Education plan where eligible), including Figma Variables, Dev Mode, and Team Libraries.
• AI-assisted design tools (Figma Make / Figma AI, MCP-enabled workflows, and approved generative AI prompting tools).
• Modern web browser.
• Learning Materials:
• W3C WCAG 2.2 accessibility documentation, Figma Learn/Developer Docs, UX research templates, design system checklists, and case-study portfolio guides.

Assessment Criteria

• UI/UX Foundations, Problem Solving & Practical UI Tasks (Classes 1–10) – 10%
• Visual Design, Components, Auto Layout & Responsive Design (Classes 11–20) – 20%
• Variables, Tokens, Design Systems & Developer Handoff (Classes 21–26) – 15%
• AI-Assisted Product Design & Functional Prototyping (Classes 27–29) – 10%
• UX Research, Persona, Storyboard & Product Prioritization (Classes 30–34) – 15%
• UX Laws, Usability, Heuristics, Accessibility & Experimentation (Classes 35–38) – 10%
• Three Collaborative Product Projects & Case Studies (Classes 39–44) – 15%
• Portfolio, Career/Freelancing Readiness, Final Presentation & QA (Classes 45–48) – 5%

Financial Information, Remuneration & Certification

• Tentative Course Fee: BDT 5,000
• Certification: Micro-Credential Certificate issued by DIU Micro-Credentials Academy (DIU-MCA) upon successful completion of course assessments.

Course Overview

Intellectual Property, Innovation & Technology Commercialization

Instructor

• Professor Dr. Kudrat-E-Khuda Babu, Professor of Law and Associate Dean,
  Faculty of Humanities and Social Sciences (FHSS), Daffodil International University

• Dr. Md. Zahurul Haque, Consultant (Patent), Faculty of Graduate Studies, DIU.

• Dr. S. M. Aminul Haque, Professor & Associate Head, Department of Computer Science and Engineering, DIU.

 ⏱ Duration: 12 Contact Hours (1 Credit Hour) | 6 Sessions (2 Hours Each) | Mode: Online

Course Description 

This professional micro-credential course equips learners with foundational and applied knowledge of Intellectual Property, covering legal-institutional frameworks, patent search and filing, and technology transfer pathways. It enables innovators, academics, and professionals to translate research and technological innovations into protected, commercializable assets in full alignment with the Bangladesh Patent Act 2023 and DIU’s institutional IP policies.

Evidence of Demand 

Universities and enterprise ecosystems increasingly require systematic IP generation, protection, and management capabilities among students, faculty, and research teams, yet many lack applied exposure to patent databases, claim interpretation, and technology transfer mechanisms. A strong institutional priority on IP management, together with DIU's IP & Patent Policy, the DIU-DPDT MOU, the WIPO Technology & Innovation Support Center (TISC) partnership, and the national mandate for research commercialization under the Bangladesh Patent Act 2023, underscores the critical demand for structured, professional IP training.

Course Objectives 

This course aims to:

• Equip participants with foundational and applied knowledge of Intellectual Property covering national and international legal frameworks.

• Build competence in patent searching, prior-art analysis, and screening innovations against statutory patentability criteria.

• Demystify patent specification drafting, filing workflows, and prosecution systems in Bangladesh.

• Provide actionable pathways for technology transfer, IP valuation, spin-offs, licensing, and commercialization consistent with institutional and WIPO-TISC guidelines.

Course Content & Class Plan (Modules)

• Module 1: Foundations of Intellectual Property & Its Strategic Value for Universities | Core concepts, IP classifications, scope and duration under Bangladeshi law, institutional rankings, and policy frameworks.

• Module 2: Patents: Core Concepts and Patenting Emerging Technologies | Statutory patentability criteria (novelty, inventive step, industrial applicability); patenting AI, software architectures, and industrially applicable innovations.

• Module 3: Trademarks, Copyright, Industrial Design, GI & Trade Secrets | Comparative scope, registration boundaries, term durations, and the bundle of exclusive rights across non-patent IP regimes.

• Module 4: Patent Search, Prior-Art Analysis & Patentability Assessment | Hands-on navigation of WIPO PATENTSCOPE, Google Patents, and DPDT registries; search syntax formulation, landscape mapping, and WIPO-TISC resources.

• Module 5: Patent Filing, Prosecution & the Bangladesh/DIU IP Ecosystem | Patent specification structuring, Bangladesh Patent Act 2023 filing process, prosecution stages, DIU IP & Patent Policy, and invention disclosures.

• Module 6: Technology Transfer, Licensing & Commercialization | Technology transfer lifecycles, university spin-offs, valuation principles, licensing structures, and action plan formulations.

Practical

• Prior-Art Search & Landscape Practicum: Formulating search syntax and querying WIPO PATENTSCOPE, Google Patents, and national DPDT databases to generate an evaluated one-page prior-art search summary.

• Patentability Screening Workshop: Evaluating emerging software and AI technological disclosures using structured analytical matrices against novelty and inventive step criteria.

• Invention Disclosure Drafting: Formulating a structured, one-page draft invention disclosure complying with DIU IP Policy protocols.

• Capstone Action Plan Defense: Developing and peer-reviewing an end-to-end IP & Commercialization Action Plan for an innovation asset.

Learning Outcomes 

After completing the course, participants will be able to:

• Explain the foundational principles, categories, and legal-institutional framework of IP under Bangladeshi and international law.

• Conduct prior-art/patent searches and assess patentability against novelty, inventive step, industrial applicability, and eligible subject matter.

• Evaluate and apply pathways for IP protection, patent filing, technology transfer, licensing, and commercialization.

Target Audience & Requirements

• Target Audience:

• Undergraduate and postgraduate students across technical and business disciplines.

• Faculty members, research associates, and lab personnel.

• DIU alumni, startup founders, and entrepreneurs engaged in research and product development.

• Entry Requirements:

• Current student, graduate, researcher, or faculty member engaged in innovation or academic work.

• Basic computer literacy and internet research skills.

• Minimum Age: 18 Years.

Career Pathways 

After completing this micro-credential, learners may:

• Work as IP/Patent Analyst, Technology Transfer Officer, Research Commercialization Associate, IP Consultant, or Innovation & Licensing Manager.

• Protect and commercialize proprietary academic and startup ventures through formal patent and trademark registrations.

• Progress to Advanced Micro-Credentials, professional IP bar certifications, or higher postgraduate research tracks in technology governance and law.

Tools & Resources

• Facilities & Digital Systems: Multimedia-equipped virtual delivery platforms, live demonstration setups, and DIU LMS integration.

• Databases & Tools: WIPO PATENTSCOPE, Google Patents, and Department of Patents, Designs and Trademarks (DPDT) digital records.

• Learning Materials: DIU IP and Patent Policy documentation, Bangladesh Patent Act 2023 briefs, WIPO-TISC toolkits, invention disclosure templates, and lecture slide decks.

Assessment Criteria

Fully mapped to Course Learning Outcomes (CLOs):

• In-Session Formative Tasks (Modules 1–5): 40% (Quizzes, worksheets, matching exercises, and prior-art search summary)

• Capstone IP & Commercialization Action Plan (Module 6): 40% (Drafting, evaluation, and peer review)

• Participation & Engagement: 20% (Requirements: Minimum 80% attendance, Minimum 60% overall pass score)

Financial Information & Certification

• Tentative Course Fee: BDT 1,500

• Class Size: Maximum 30 participants per batch

• Certification: Micro-Credential Certificate (1 Credit Hour equivalent) issued by DIU Micro-Credentials Academy

Course Overview

AI for Small Entrepreneurs: Opportunities of AI in Your Online Business

Instructors

• Lead Instructor / Course Designer: Engineer M. M. Obayed Quader Sultan — CEO, Proxima Soft; AI Business Consultant (Profile: https://apusultan.com)

• 2nd Instructor: Mr. Sadman Sharif — Lecturer, Department of Innovation & Entrepreneurship, DIU

• Qualifications: B.Sc. in CIS; AI Integration Specialist; Academic Faculty in Entrepreneurship

• Experience: 24+ years industry, 20+ years training

• Expertise: AI Workflows, Digital Entrepreneurship, E-Commerce Strategy, Prompt Engineering

  ⏱ Duration: 5 Weeks | 15 Contact Hours (3 Hours per Week, 5 Classes) | Mode: Hybrid 

Course Description

This micro-credential course equips beginners and existing small business owners with the foundational skills to run a Facebook-based online business, while integrating practical AI tools (ChatGPT and prompting techniques) to automate marketing, business profile setup, customer communication, and sales workflows. Delivered in hybrid mode over five 3-hour sessions, it combines lectures, hands-on workshops, case studies, and a capstone project in which each participant produces a ready-to-use AI Business Output Pack for their own business idea. 

Evidence of Demand 

There is rising interest among small entrepreneurs and beginners in launching Facebook-based online businesses, coupled with challenges in core business operations and a growing need for practical AI adoption in marketing, content creation, and customer communication.

Industry consultation, surveys, job-market analysis, partner recommendation, and existing demand data all point to high market demand for low-cost, AI-driven automation tools among online micro-entrepreneurs seeking to reduce operational overhead and scale social media sales.

Industry Expert / Partner: Engineer M. M. Obayed Quader Sultan (CEO, Proxima Soft & AI Business Consultant) in collaboration with Mr. Sadman Sharif (Lecturer, Department of Innovation & Entrepreneurship, DIU).

Course Objectives 

This course aims to:

• Equip participants with foundational management skills to run a Facebook-based business

• Introduce practical AI tools (ChatGPT) and prompting techniques to streamline marketing, content creation, and overall business workflows

• Enable participants to automate business profile setup, customer communication, and sales workflows using AI

• Guide participants to build a repeatable AI workflow and a complete AI Business Output Pack for their own business

Course Content & Class Plan (Modules)

• Module 1 – Day 1: Business Foundation + Customer (3 hrs)
  Practical: Customer persona mapping & matching product solutions to customer problems.

• Module 2 – Day 2: Offer + Branding + Marketing + Sales + Operations (3 hrs)
  Practical: Structuring a business offer, sales funnel layout, and mapping operational workflows.

• Module 3 – Day 3: AI for Business + Prompting (3 hrs)
  Practical: Hands-on AI prompting practice, identifying AI insertion points, and responsible AI use (fact-checking, avoiding misleading content, data privacy).

• Module 4 – Day 4: Business Profile + Marketing with AI (3 hrs)
  Practical: Building an AI-ready profile, generating content using AI, message/comment automation for customer service, and creating visuals without manual prompting.

• Module 5 – Day 5: AI Workflow + Final Output + Recap & Final Challenge (3 hrs)
  Practical: Assembling a repeatable AI workflow, presenting the final AI Business Output Pack, plus basics of reading Facebook insights and scaling.

Practical

• TEvery session pairs a short concept briefing with hands-on work; roughly 9 of the 15 contact hours are practical:

• Customer persona mapping and problem–solution matching (Day 1)

• Offer structuring, sales funnel layout, and operations workflow mapping (Day 2)

• Live AI prompting practice on real business tasks (Day 3)

• AI-ready business profile build, AI content generation, and comment/message automation setup (Day 4)

• Capstone: assembling a repeatable AI workflow and presenting a complete AI Business Output Pack (Day 5)

Delivery methods: Lecture | Hands-on | Workshop | Case Study | Project

Learning Outcomes 

After completing the course, participants will be able to:

1. Understand Facebook-based business operations, identify target customer personas, match problem–solutions, and build simple business workflows

2. Write effective AI prompts and utilise ChatGPT to generate marketing content, offers, copy, captions, and customer communications

3. Create an AI-ready business profile and establish repeatable AI workflows for daily business operations

4. Produce a complete, ready-to-use AI Business Output Pack for their own business idea

Target Audience & Requirements Target Audience:

• Starters and aspiring entrepreneurs

• Existing small business owners

• Individuals interested in starting or growing a Facebook-based online business

Entry Requirements:

• Open to beginners — no prior AI or technical background required

• Basic familiarity with Facebook and smartphone/computer use

• Access to an internet-connected device (laptop or smartphone)

• An existing Facebook page or a business idea is an advantage but not mandatory

Career Pathways 

Relevant job roles:

• Facebook E-commerce Entrepreneur

• Small Business Owner

• AI-Powered Digital Marketer

• Freelance Social Media Manager

Progression: Advanced Micro-Credential courses; launching or scaling one's own entrepreneurial venture

Tools & Resources

• Facebook Business tools

• ChatGPT and AI prompting

• Business profile templates; workflow / output pack templates

• Internet-connected devices

• AI Toolbox subscription (per participant):

• Regular Intro Pack — BDT 1,500 (BDT 1,000 one-month subscription + BDT 500 credit balance)

• Offer Intro Pack — BDT 600 (BDT 300 one-month subscription + BDT 300 credit balance); offer rate valid for the next 6 months

• Resource availability: Available at DIU

Assessment Criteria

Methods: Quiz | Assignment | Project | Practical | Presentation

• Daily class participation & workflow assignments (LO1) – 30%

• Practical AI prompting & marketing content assignments (LO2 & LO3) – 30%

• Day 5 capstone: AI Business Output Pack submission & presentation (LO4) – 40%

Minimum attendance: 80% | Minimum pass score: 60% 

Financial Information, Remuneration & Certification

• Tentative Course Fee: BDT 3,000 only

• Class Size: Maximum 20–30 participants

• Certification: Micro-Credential Certificate issued by DIU-MCA upon completing assessment requirements

Course Overview

From Idea to Publication: Research Paper Writing & Publishing

Instructors

• Mohammad Mustafizur Rahman, Assistant Professor, Department of English, Daffodil International University.

• Sakiba Binte Yusuf, PhD Research Fellow, School of International Studies, Zhengzhou University, Henan, China.

   ⏱ Duration: 12 Hours (12 Classes × 60 Minutes) | Mode: Online

Course Description

This beginner-friendly, hands-on micro-credential course is designed to help participants understand and practice the complete research paper writing process in a clear, practical, and academically responsible manner. Moving beyond pure theory, the course uses a running demo study, guided worksheets, classroom activities, peer review, and instructor feedback to walk learners through formulating research questions to preparing a publishable manuscript or comprehensive research-paper blueprint.

Evidence of Demand 

Research paper writing has become an essential academic and professional competency for university students, postgraduates, scholarship applicants, and early-career academics who must prepare theses, conference papers, and evidence-based reports. Beginners and non-native English-speaking learners often understand their subject matter but struggle with structuring topics, synthesizing literature, applying methodologies, adopting APA 7 conventions, avoiding plagiarism, and responsibly leveraging AI tools while preserving academic integrity. This course directly bridges these workbench-level writing and publication gaps.

Course Objectives 

This course aims to:

• Help learners understand the importance and role of research in academia and industry.

• Guide learners to identify focused, ethical topics and develop effective titles, problem statements, and research questions.

• Teach systematic methods to search, evaluate, synthesize, and cite scholarly literature using APA 7.

• Clarify core research designs, sampling strategies, data-collection procedures, analysis techniques, and research ethics.

• Guide section-by-section drafting of academic papers from Abstract to Appendices.

• Promote responsible, integrity-first use of AI tools and verification of genuine vs. fabricated evidence.

• Enable participants to produce an actionable mini research paper or research blueprint.

Course Content & Class Plan (Modules)

• Class 1: Why Research Matters – University study, higher education, real-life problem-solving, and intro to the running demo paper.

• Class 2: Structure of a Research Paper – Title, Abstract, Keywords, IMRAD structure, References, and Appendices.

• Class 3: Choosing a Research Topic and Title – Novelty, researchability, research gaps, working vs. publication-style titles.

• Class 4: Writing the Introduction – Context, problem statement, research gap, objectives, research questions, and significance.

• Class 5: Writing the Literature Review – Finding credible sources, synthesizing, identifying gaps, and conceptual frameworks.

• Class 6: Writing the Methodology – Research design, population/sample, sampling, instruments, reliability/validity, and ethics.

• Class 7: Writing the Results/Findings – Organizing quantitative and qualitative findings, tables, percentages, themes, and evidence.

• Class 8: Writing the Discussion – Interpreting findings, linking to research questions/literature, and explaining implications.

• Class 9: Writing the Conclusion, Recommendations, Limitations, and Future Research.

• Class 10: APA 7 In-text Citations and References – Paraphrasing, reference lists, DOIs, URLs, and plagiarism avoidance.

• Class 11: Writing the Abstract, Keywords, Appendices, and Final Paper Assembly – Academic consistency and presentation.

• Class 12: From Draft to Research Ready – Editing, proofreading, responsible AI use, peer review, and final presentation.

Practical

• Topic Formulation & Problem Statement Sprints: Transforming raw ideas into viable titles, research gaps, and research questions.

• Literature Search & Citation Labs: Live database retrieval exercises in Google Scholar, reference synthesis, and APA 7 list building.

• Methodology & Data Interpretation Workshops: Designing sample parameters, building basic results tables, and drafting discussion sections.

• Peer Review & Capstone Blueprint Formulation: Evaluating draft sections against research integrity standards, validating AI outputs, and finalizing the mini research-paper submission.

Learning Outcomes 

After completing the course, participants will be able to:

• Explain the standard structure and basic principles of an academic research paper.

• Convert broad interests into focused, researchable topics with clear objectives and research questions.

• Locate, evaluate, and synthesize scholarly literature into a coherent literature review.

• Select appropriate research designs and articulate sampling, instruments, analysis, and ethical safeguards.

• Present quantitative/qualitative findings using structured tables, themes, and evidence.

• Interpret results logically against previous literature and research questions.

• Write effective conclusions, recommendations, limitations, and future research avenues.

• Apply APA 7 citation, referencing, and academic formatting standards accurately.

• Identify plagiarism, fabricated citations, invented data, and ethical integrity violations.

• Utilize generative AI tools responsibly without compromising academic authorship.

• Prepare and present a structured mini research paper or publishable blueprint.

Target Audience & Requirements Target Audience:

• Undergraduate students across all disciplines.

• Final-year students preparing projects, theses, or research assignments.

• Fresh graduates preparing postgraduate applications or scholarship submissions.

• Master's and beginning postgraduate students.

• Early-career researchers, academics, and professionals writing evidence-based reports.

• Non-native English speakers seeking a structured foundation in academic writing.

Entry Requirements:

• Minimum Higher Secondary Certificate (HSC) or equivalent.

• Basic English reading and writing proficiency.

• Basic computer literacy and internet navigation skills.

• Access to a laptop/computer for writing practicums.

• Minimum Age: 18 Years.

• Prior publication experience is not required.

Career Pathways 

After completing this micro-credential, learners may:

• Produce undergraduate and postgraduate theses or capstone project papers.

• Prepare abstracts, posters, and full papers for academic conferences.

• Submit stronger writing samples for international scholarships and master's/PhD admissions.

• Advance to specialized training in systematic reviews, advanced quantitative/qualitative methodologies, or journal manuscript preparation.

• Enhance analytical reporting skills for careers in academia, think tanks, NGOs, policy institutes, and development organizations.

Tools & Resources

• Software & Digital Platforms: Microsoft Word (or equivalent word processor), Google Scholar, and academic database platforms.

• Delivery Infrastructure: Online meeting and presentation software with stable internet connectivity.

• Learning Materials: Course handbook, lecture notes, running demo research paper, practical worksheets, and APA 7 quick-reference guides.

Assessment Criteria

• Final Mini Research Paper / Research Blueprint – 25%

• Topic, Title, Problem, and Research-Question Task – 15%

• Literature Review and APA 7 Citation Task – 15%

• Methodology Planning Task – 15%

• Results / Discussion Interpretation Exercise – 15%

• Class Participation and Guided Activities – 10%

• Final Presentation / Viva – 5% (Passing Requirement: Minimum 40% overall score with satisfactory attendance per MCA policy)

Financial Information, Remuneration & Certification

• Tentative Course Fee: BDT 1,000 only

• Class Size: Maximum 20–30 participants

• Certification: Micro-Credential Certificate issued by DIU-MCA upon completing assessment requirements

Course Overview

Hands-on Molecular Biology: Plant DNA Extraction, PCR Amplification and Agarose Gel Electrophoresis  

Instructors

• Dr. ATM Majharul Mannan, Assistant Professor and Head, Department of Agricultural Science, DIU.

• Prof. Dr. Md. Abdur Rahim, Professor and Chairman, Department of Genetics and Plant Breeding, Sher-e-Bangla Agricultural University (SAU).

• Dr. Mst. Hosne Ara, Manager, Laboratory Support and Customer Training, Central Dogma Lab, Invent Technologies Ltd., Dhaka, Bangladesh.

   ⏱ Duration: 5–6 Sessions | Total Hours: 16–18 Hours | Mode: Hybrid

Course Description 

This course provides participants with practical, hands-on skills in extracting genomic DNA from plant tissue using the CTAB method and performing PCR amplification, enabling them to apply foundational molecular biology techniques in research, diagnostics, and breeding programs. Delivered through hands-on workbench practicums, the training bridges the gap between academic theory and practical lab execution in agri-biotech and food safety.

Evidence of Demand 

There is a growing need for hands-on molecular biology skills among students in Agriculture, Biotechnology, Genetic Engineering, and Public Health Nutrition disciplines. DNA extraction and PCR are foundational techniques widely required in plant breeding, GMO detection, disease diagnostics, and research labs, yet many students lack practical, workbench-level exposure to these methods. The increasing use of molecular tools in the agri-biotech and food safety sectors reflects a clear and growing skills demand among students and early-career researchers.

Course Objectives

This course aims to:

• Equip participants with practical, hands-on skills in extracting genomic DNA from plant tissue using the CTAB method.

• Train learners to perform PCR amplification and verify target genes.

• Enable application of foundational molecular biology techniques in research, diagnostics, and breeding programs.

• Provide practical workbench-level laboratory training in quality and purity assessments.

Course Content & Class Plan (Modules)

• Module 1: Introduction to Plant Molecular Biology and Lab Safety (2 hrs)

• Module 2: DNA Extraction – Plant Sample Preparation and Cell Lysis (2–3 hrs)

• Module 3: DNA Purification and Precipitation (2–3 hrs)

• Module 4: DNA Resuspension & Quality/Quantity Assessment (2 hrs)

• Module 5: Principles of PCR (2 hrs)

• Module 6: PCR Setup and Thermal Cycling (2 hrs)

• Module 7: Agarose Gel Preparation, Gel Electrophoresis and Analysis (2 hrs)

• Module 8: Applications, Documentation and Capstone (2 hrs)

Practical & Field Work (60% of Course)

• Plant Sample Preparation & Cell Lysis using liquid nitrogen and CTAB extraction protocols.

• DNA Purification, Precipitation, and Resuspension in TE buffer.

• DNA Concentration and Purity Assessment via spectrophotometry ($A_{260}/A_{280}$).

• PCR Master Mix setup, primer addition, MgCl2 optimization, and thermal cycler operation.

• Casting agarose gels, loading samples, running electrophoresis, and documenting bands using gel imaging systems.

• Comprehensive Capstone: Complete extraction-to-gel workflow with results presentation.

Learning Outcomes

After completing the course, participants will be able to:

• Extract high-quality genomic DNA from plant tissue using the CTAB method.

• Determine DNA concentration and purity using spectrophotometry ($A_{260}/A_{280}$).

• Amplify a target gene through PCR and verify amplification by agarose gel electrophoresis.

Target Audience & Requirements

• Target Audience:

• Undergraduate and postgraduate students and researchers in Agriculture, Biotechnology, Genetic Engineering, Botany, Microbiology, and Public Health Nutrition.

• Laboratory technicians seeking molecular biology skills.

• Entry Requirements:

• Background in Agriculture, Biotechnology, Genetic Engineering, or related life science disciplines.

• Basic interest in molecular biology laboratory techniques (no prior advanced workbench certification required).

Career Pathways

After completing this micro-credential, learners may:

• Work as Research Assistant, Molecular Biology Lab Technician, Biotechnology Researcher, Plant Breeder/Geneticist, or Quality Control Analyst (Agri-Biotech/Food Safety).

• Progress to Advanced Micro-Credentials, Higher Study, or Professional Certifications in genomics and molecular diagnostics.

Tools & Resources

• Facilities & Equipment:

• Centrifuge, micropipettes, water bath/heating block.

• Thermal cycler (for PCR amplification).

• Agarose gel electrophoresis setup and gel documentation/imaging system.

• Tools, Instruments & Materials:

• Fresh plant leaf samples, liquid nitrogen, CTAB buffer, chloroform, isopropanol/ethanol, TE buffer.

• PCR master mix, primers, dNTPs, MgCl2, agarose gel reagents.

• Learning Materials:

• Laboratory manuals, standard operating procedures (SOPs), lecture presentations, and DIU LMS access.

Assessment Criteria

• In-session practical checkpoints on DNA extraction quality (LO1) – 40%

• Capstone complete extraction-to-gel workflow with results presentation and PCR setup accuracy (LO2 & LO3) – 40%

• Participation and lab technique evaluation (All LOs) – 20% (Recommended: Minimum 80% Attendance, Minimum 60% Pass Score)

Financial Information, Remuneration & Certification

• Tentative Course Fee: BDT 3,000

• Class Size: Maximum 30 participants per batch

• Instructor Remuneration: As per DIU-MCA Policy

• Certification: Micro-Credential Certificate / Certificate of Completion issued by DIU-MCA

Course Overview

The Complete Research Guide and Publication Roadmap (Batch 02)

⏱ Duration: 21 Hours. | Mode of Delivery: In-person

Instructor(s)

1. Md Mizanur Rahman: Lecturer (Senior Scale), Department of CSE, Daffodil International University.
2. RKO Shahed Hossain Khan: Founder and Chairman of SkillChefs Private Limited.

Course Description

This professional course is designed to equip learners with the core research skills and the technical foundation in Python, Machine Learning, and Deep Learning required to begin a publishable research project. The course is structured in a natural research flow: learners first build the research foundation, then immediately learn the data analysis tools, and finally come back to the writing and publication preparation steps.

Evidence of Demand

• In Bangladesh, undergraduate and graduate students often complete their degrees without ever publishing a research paper due to a lack of training in practical workflows.
• Globally, scholarship admissions, higher studies opportunities, and competitive job markets increasingly value applicants who already have research publications.
• In emerging fields, hands-on skills with Python and ML libraries have become a baseline requirement rather than an advantage.
• Students heavily struggle with early steps like domain selection, literature review, and methodology design, creating a steady demand for structured, mentorship-based programs.

Purpose and Objectives

• Purpose: To walk the learner from the absolute basics of research to building a complete research foundation, while simultaneously providing the Python and Machine Learning skills needed to execute a modern data-driven project.
• Objectives:
• Understand the full research workflow, from domain selection to manuscript preparation.
• Read, analyze, and review journal articles in a systematic and critical way.
• Identify a meaningful research gap and design a hypothesis around it.
• Work confidently with Python, key data libraries, and Machine Learning/Deep Learning techniques.
• Write each section of a research paper, including the introduction, methodology, results, abstract, and conclusion.

Course Content & Class Plan (Modules)

• Class 01: Orientation, overall discussion of research, necessary platforms, domain selection.
• Class 02: Article search strategy (journal ranking, selection strategy, article access, predatory journals), reading strategy of an article, literature review.
• Class 03: Identifying research gap, designing methodology, building hypothesis.
• Class 04: Data collection tools (Kobo Toolbox), data description, and diagram design tools.
• Class 05: Systematic literature review writing.
• Class 06: Introduction writing (background knowledge, highlighting relevancy, objectives and contributions).
• Class 07: Methodology writing, result analysis and discussion writing.
• Class 08: Basic Python, development environment, installation, Hello World, conditions, loops, string operations, functions, list, tuple, set, dictionary.
• Class 09: Introduction to Python libraries (NumPy, Pandas), Matplotlib, Seaborn, OpenCV and PIL.
• Class 10: Introduction to Machine Learning, regression (linear and logistic), classification and ML classifier implementation.
• Class 11: Feature extraction and selection, ensemble Machine Learning.
• Class 12: Introduction to Deep Learning, transfer learning model implementation, CNN model, hyperparameter tuning.
• Class 13: Abstract and conclusion writing, referencing and reference management tools (Mendeley, Zotero), plagiarism and AI checking tools.
• Class 14: Journal selection, manuscript preparation (LaTeX and Word), article submission, address review, and research proposal making.

Practical & Field Work

• Data Collection & Mapping: Practical use of tools like Kobo Toolbox and diagram design tools.
• Programming Exercises: Writing Python code utilizing core data structures, loops, and conditions.
• Model Implementation: Applying regression, classification models, and Deep Learning (CNNs) on real datasets.
• Manuscript Preparation: Hands-on writing practice for academic sections and formatting using tools like LaTeX and Word.

Learning Outcomes

Upon completion, participants will be able to:

• Research Workflow: Choose a research domain, search for quality articles avoiding predatory journals, and identify clear research gaps.
• Methodology Design: Build testable hypotheses and use appropriate data collection tools.
• Academic Writing: Write systematic literature reviews and fully structured paper sections while using referencing and plagiarism tools appropriately.
• Programming Foundation: Set up a Python environment and visualize data using NumPy, Pandas, Matplotlib, and Seaborn.
• Machine Learning Skills: Apply regression/classification models, perform feature extraction, and understand basic Deep Learning frameworks.

Target Audience & Requirements

• Target Audience:
• Undergraduate and graduate students of any discipline, or fresh graduates.
• Early career researchers, university teachers, and research assistants.
• Professionals interested in transitioning into data-driven research.
• Entry Requirements:
• Currently studying or completed an undergraduate degree in any discipline (B.Sc in Computer Science and Engineering noted for 3rd year, final year, or graduate).
• Basic computer literacy is expected, but no prior research or programming experience is required.
• Minimum Age: 21 years.

Career Pathways

• Continue to advanced phases of the Complete Research Guide (Advance Statistics and Paper Writing/Publication).
• Apply for research assistant positions in universities and research labs.
• Begin working on independent research papers for journal or conference submission.
• Pursue higher studies (MS or PhD) abroad with a stronger research profile.
• Move into data analyst, junior ML engineer, or research analyst roles in the industry.

Tools & Resources

• Well-equipped classroom and lab room for Python, Machine Learning, and Deep Learning classes.
• Data collection and management tools (Kobo Toolbox, Mendeley, Zotero).
• Development environments and Python libraries (NumPy, Pandas, OpenCV, PIL, etc.).
• Manuscript preparation software (LaTeX and Word) and AI/plagiarism checkers.

Assessment Criteria

• Class attendance and participation in live sessions.
• Weekly Quizzes and practical assignment session performance.
• A short research proposal draft prepared by the end of the course.
• Final evaluation through a viva or oral discussion on the prepared proposal.

Financial Information

• Tentative Course Fee: 2,000 BDT.

Course Overview

From Leaf to Cup: Tea Processing, Quality and Industrial Practices 

Instructor(s):

• Md. Habibur Rahman: BSc in Food Engineering and Tea Technology (SUST, Sylhet)
  MSc in Nutrition and Food Science (University of South Asia, Banani, Dhaka)
  MBA in Supply Chain Management (BUP, Mirpur Cantonment, Dhaka)
  About 12 years of experience in the tea industry (MM Ispahani Tea Ltd., BRAC
  Tea Estates Ltd., City Group Tea Estates Ltd., ACME Consumer Products Ltd. -
  Tea & beverage Unit, Kazi & Kazi Tea estate Ltd.)

• Dr. Atiqual Islam: Assistant Professor & Associate Head, Daffodil International University
  PhD and Postdoc – South Korea
  (Analytical chemistry, Chromatographic method development)
  Profile: https://faculty.daffodilvarsity.edu.bd/profile/nfe/atiqual.html

• Dr. Md. Al Mamunur Rashid: Assistant Professor, Daffodil International University
  PhD and Postdoc – South Korea
  (Food Chemistry, Nutrition, Computational Chemistry, Polymerization)
  Profile: https://faculty.daffodilvarsity.edu.bd/profile/nfe/mamunur.html

• Md. Monirujjaman: Lecturer (Senior Scale), Daffodil International University
  B.Sc. & M.S in Food Engineering (Food Engineering, Bioactive Compound Extraction, Sustainable Food
  Processing)
  Profile: https://faculty.daffodilvarsity.edu.bd/profile/nfe/monirujjaman.html

Duration: 16 Hours 

Delivery Mode: Blended: In-person and online, site visit | Class Size: 20 

Course Description

This course integrates industry-based knowledge with academic learning, offering practical insights into tea manufacturing, quality management, and product innovation.

It is designed to bridge the gap between academic knowledge and practical industry requirements, supporting entrepreneurship and value-added tea businesses.

Evidence of Demand

The global tea industry is rapidly evolving with increasing demand for premium, specialty, and functional tea products. As a key tea-producing country, Bangladesh has strong potential in both domestic and export markets, yet faces a shortage of skilled professionals in tea processing, quality assurance, and value addition. At the same time, a gap persists between academic knowledge and practical industry requirements, limiting employability and productivity.

This micro-credential course aims to bridge that gap by integrating industry-based knowledge with academic learning, offering practical insights into tea manufacturing, quality management, and product innovation. It will also support entrepreneurship and value-added tea businesses. By developing industry-ready skills, the course will enhance competitiveness, promote sustainable practices, and contribute to the overall growth of the tea sector. 

Course Objectives

• Specific: Enable learners to understand and apply modern tea processing techniques, including withering, rolling, fermentation, drying, and packaging.

• Measurable: Ensure learners can perform quality assessment and tea tasting for at least three types of tea and evaluate their quality using industry standards.

• Achievable: Equip learners with practical skills in tea blending, cost control, and inventory management through hands-on exercises and case studies.

• Relevant: Prepare learners for employment or entrepreneurship in tea estates, beverage industries, and tea-based businesses by providing industry-relevant knowledge.

• Time-bound: By the end of the course, learners will demonstrate proficiency in tea production operations, quality assurance practices, and value-added product development through assessments and practical projects. 

Course Content & Class Plan (Modules)

1. Introduction to the tea industry, course guidelines, global and Bangladesh tea sector overview, Q/A

2. Tea plant, cultivation practices, plucking methods, types of tea (black, green, oolong, white), Q/A

3.  Withering process, rolling and CTC method, fermentation (oxidation) principles, processing parameters

4.  Drying and firing techniques, grading and sorting, packaging methods, storage conditions

5.  Tea quality parameters, liquor characteristics, aroma and flavor, tea tasting techniques, sensory evaluation

6. Chemical composition of tea, quality indicators, basic laboratory analysis, Q/A

7. Tea blending techniques, specialty and functional tea, product development concepts

8. Industrial tea processing workflow, factory operations, cost control, inventory management

9. Quality assurance systems (GMP, HACCP basics), hygiene and safety in tea industry

10.  Tea business opportunities, branding and marketing strategies, export potential and regulations

11.  Case study on tea processing and quality control, problem-solving session

12. Tea tasting session (minimum three types), practical evaluation and data recording

13. Development of value-added tea product, group project work, presentation

14.  Industry visit (tea factory) / virtual tour, observation and report preparation

15. Final assessment: practical, project presentation, viva 

Learning Outcomes

They will learn to

1. Demonstrate tea processing techniques (withering, rolling, fermentation, drying) through practical application

2. Evaluate tea quality using standard sensory parameters (color, aroma, flavor, liquor) for at least three tea types

3. Apply basic quality control and safety principles (GMP, HACCP) in tea production

4. Develop a value-added tea product and perform basic blending

5. Analyze tea processing operations and prepare a brief technical or business report 

Target Audience & Requirements

Students (graduate/undergraduate) of Food Technology, Food Engineering, Chemistry, Food and Nutrition, professionals, and entrepreneurs. 

Career Pathways

1. Higher studies in Food Engineering, Food Technology, Nutrition, or Beverage Science

2. Entry- to mid-level roles in the tea and beverage industries (processing, quality control, production)

3. Internship and industrial training in tea estates and tea processing factories

4. Career as a sensory evaluator or tea quality analyst

5. Entrepreneurship in tea-based businesses (tea blending, specialty tea, tea cafés, value-added products 

Tools & Resources

1. Tea processing equipment

2.  Sensory evaluation setup

3.  Basic lab facilities

4. Classroom & multimedia support

5. Learning materials & LMS

6. Industry visit/virtual tour

7. Safety and hygiene items 

Assessment Criteria

1. Quizzes,

2. Project work

3. Report writing

4. Viva 

Certification

Awarded a Certificate of Completion by the DIU Micro-Credentials Academy.

Financial Information

• Tentative Course Fee: 2,500 BDT

Course Overview

Advanced Research Methods in Public Health Nutrition: From Study Design to Scientific Publication and Dissemination  

Instructor(s):

• Md. Shahadoth Hossain | Lecturer, Department of Nutrition and Food Engineering, Daffodil International University

• Md. Sakhawot Hossain | Lecturer, Department of Nutrition and Food Engineering, Daffodil International University

• Tasniya Akter | Lecturer, Department of Nutrition and Food Engineering, Daffodil International University

• Md. Hafizul Islam | Industry Expert & Research Associate, Center for Non-communicable Diseases and Nutrition, BRAC James P Grant School of Public Health, BRAC University

Duration: 21 Hours 

Delivery Mode: Online / In-person / Blended 

Course Description

This micro-credential equips learners with applied competencies that are highly valued in academic research, public health programs, and evidence-informed policymaking. It addresses current skill gaps by providing hands-on training across the complete research process, bridging the gap from study design and data analysis to scientific writing and publication.

Evidence of Demand

There is a growing demand for professionals with practical research skills in public health nutrition as Bangladesh and the South Asian region continue to address undernutrition, micronutrient deficiencies, and the rising burden of non-communicable diseases. Universities, research institutes, NGOs, and development partners increasingly seek graduates and early-career professionals who can design studies, analyze data, and communicate findings through scientific publications. However, undergraduate programs often provide limited hands-on training across this complete research process.

Course Objectives

This course aims to equip learners with the full research pipeline in public health nutrition, from study design through to scientific publication and dissemination.

Course Content & Class Plan (Modules)

• Module 1: Introduction to Public Health Nutrition Research Role of research in public health nutrition, identifying research gaps, research questions and hypotheses, and conceptual/theoretical frameworks.

• Module 2: Study Design and Research Methodology Quantitative, qualitative, and mixed-methods research; observational, experimental, and quasi-experimental studies; implementation and operational research; conducting systematic reviews and meta-analysis.

• Module 3: Sampling and Data Collection Sampling strategies, sample size determination, questionnaire development, dietary assessment methods, anthropometry and biomarkers, digital data collection tools, and acquisition of secondary data.

• Module 4: Nutritional Epidemiology and Interpretation Nutrition and health indicators (women's, child, and population health), food security and diet quality, interpreting epidemiological findings, and translating research evidence into policy and practice.

• Module 5: Scientific Writing and Reporting Guidelines Writing each section of a scientific paper, reporting guidelines (STROBE, CONSORT, PRISMA, RECORD), reference management (Zotero, Mendeley, EndNote), and ethical reporting/plagiarism prevention.

• Module 6: Data Management and Statistical Analysis Data cleaning and management, handling missing data, descriptive and inferential statistics, regression analysis/adjusting for confounders, statistical software (R, Stata, SPSS), and interpreting/presenting results.

• Module 7: Journal Selection, Manuscript Formatting, and Submission Selecting an appropriate journal, formatting manuscripts, writing cover letters, graphical abstract preparation, online manuscript submission systems, and navigating the peer-review process.

• Module 8: Research Ethics, Grant Writing, and Research Dissemination Research ethics and IRB approval, informed consent, grant proposal development/budget preparation, and research communication (conference presentations and policy briefs).

Practical & Field Work

• Drafting a functional research protocol and ethics application summary.

• Developing a data analysis plan and presenting results using a sample dataset.

• Preparing a publication-ready manuscript (or substantial draft) alongside a cover letter and journal selection rationale.

Learning Outcomes

After completing the course, participants will be able to:

• Explain the role of research in advancing public health nutrition; identify research gaps and formulate clear research questions and hypotheses.

• Distinguish between quantitative, qualitative, and mixed-methods approaches; select an appropriate study design.

• Choose suitable sampling strategies, calculate sample size, and develop/pilot data collection instruments.

• Select and interpret nutrition and health indicators to assess nutritional status, diet quality, food security, and population health.

• Write each section of a scientific paper following reporting guidelines (STROBE, CONSORT, PRISMA, RECORD).

• Clean, code, and manage a research dataset; apply descriptive/inferential statistics and regression analysis using R/Stata/SPSS.

• Prepare a publication-ready manuscript, select an appropriate journal, and navigate submission and peer review.

• Obtain ethics/IRB approval, develop a grant proposal, and communicate research through presentations and policy briefs.

Target Audience & Requirements

• Target Audience: Undergraduate students.

• Entry Requirements: A basic knowledge of nutrition, public health, and statistics is required as a prerequisite.

• Minimum Age: 18 years or above.

Career Pathways

• Academic Progression: Supports undergraduate and postgraduate research in Nutrition, Public Health, Epidemiology, and related disciplines. Provides a strong foundation for Master's and PhD programs requiring research and scientific writing skills. Facilitates progression to advanced research-focused micro-credentials.

• Professional Progression: Prepares learners for research assistant, research associate, monitoring and evaluation, and data analyst roles in universities, research institutes, NGOs, and development organizations. Enhances competitiveness for research fellowships, graduate admissions, and funded research opportunities.

Tools & Resources

• Laptop, Projector, White board & Marker pen.

Assessment Criteria

• Research protocol – 15%

• Ethics application summary – 10%

• Data analysis plan – 15%

• Results presentation (using a sample dataset) – 20%

• A publication-ready manuscript (or a substantial draft) – 30%

• Cover letter and journal selection rationale – 10%

Certification

Awarded a Certificate of Completion by the DIU Micro-Credentials Academy, recognizing competency in public health nutrition research methods and scientific communication.

Course Overview

Translating Product Development into Research (Batch 02)

Lead Instructors:

• Zannatul Ferdoush (Senior Lecturer, Department of Nutrition and Food Engineering, DIU)

• Juwel Rana (Assistant Professor, Department of Nutrition and Food Engineering, DIU)

• Dr. Nizam Uddin (Associate Professor and Head, Department of Nutrition and Food Engineering, DIU)

Guest Instructor:

• Zoheb Hasan Fahad (Scientific Officer, Bangladesh Agricultural Research Institute)

⏱ Duration: 3 Days (21 hours total, 7 hours per day) | Blended (Online + In-Person Practical Workshop)

Course Description
This course bridges the gap between food innovation, research, and academic publishing by teaching learners how to convert practical food product development into structured research articles.

Evidence of Demand 

The food sector has experienced rapid expansion driven by consumer demand for safe, nutritious, sustainable, and innovative food products. At the same time, research institutions emphasize applied research outputs, yet a significant gap exists: many students and industry professionals lack the skills to convert practical product work into structured research articles suitable for publication.

Purpose and Objectives 

The purpose of this course is to equip learners with the ability to convert product development processes into structured research frameworks. Objectives include:

• Understand the relationship between food product development and research publication.

• Apply appropriate research methodologies in food product development studies.

• Analyze and interpret data from food product testing and evaluation.

• Convert product development processes into structured research frameworks.

• Develop well-organized research articles based on product innovation projects.

• Apply academic writing standards, including referencing and journal formatting.

Course Content & Class Plan (Modules)

Tentative Syllabus:

• Module 1: Introduction to Food Product Development and Research

• Module 2: Research Methodology for Product-Based Studies

• Module 3: Chemical and Quality Analysis of Innovative Food Products

• Module 4: Sensory Evaluation of Food Products

• Module 5: Data Analysis and Interpretation

• Module 6: Academic Writing and Publication

• Module 7: Capstone Project

Practical & Field Work

• Practical Project: Hands-on development of food products (accounts for 30% of the final grade).

• Laboratory Work: Utilizing chemical analysis facilities for proximate analysis (moisture, ash, protein, fat, fiber) and engaging in sensory testing methods like hedonic scaling and ranking.

• Capstone Project: The development of a food product-based research paper integrating proximate analysis, sensory evaluation, and demand evidence, culminating in manuscript preparation and presentation.

Learning Outcomes

Upon completion, students will be able to:

• Explain the relationship between food product development and academic research publication.

• Conduct proximate analysis (moisture, ash, protein, fat, fiber, carbohydrate) for innovative food products.

• Perform sensory evaluation using appropriate methods.

• Design research studies based on food product development processes.

• Collect and analyze data from chemical, sensory, and consumer-based studies using appropriate techniques.

• Interpret and integrate experimental results into coherent research findings.

• Develop a structured research article based on food product innovation.

• Apply academic writing and referencing skills for publication.

• Prepare and present a complete product-based research manuscript.

Target Audience

• Undergraduate students in Food Science and Technology, Nutrition, Engineering, Biotechnology, Innovation & Entrepreneurship and related fields.

• Postgraduate students (MSc) working on food product development or applied research projects.

• Diploma in Food Technology students.

Entry Requirements

• Minimum Age: 18 years and above.

• Qualifications: Enrollment in or completion of a Bachelor's degree in Food Science and Technology, Nutrition, Biotechnology, Agriculture, Chemistry, or related fields.

Career Pathways

This course supports career advancement into roles such as:

• Food Product Development Scientist

• Research and Development (R&D) Officer

• Quality Assurance / Quality Control Specialist

• Food Laboratory Analyst

Tools & Resources

• Laboratory Facilities: Well-equipped Food Science Laboratory for product development and analysis, basic food processing equipment, chemical analysis facilities, glassware, and safety equipment.

• ICT and Software Resources: Computers or laptops with internet access and statistical software (e.g., SPSS, Excel) for data analysis.

• Academic Resources: Textbooks and reference materials in Food Science, Food Chemistry, and Product Development.

Assessment Criteria

• Daily Quizzes & Assignments: 40%

• Practical Project (Development of Products): 30%

• Final Exam (Comprehensive analytical test covering all modules): 30%

Standard Course Fee

• Base Fee: BDT 1500

Course Overview

Agronomic Research Techniques 

Instructor(s):

• Uswatun Hasana Hashi : Assistant Professor, Department of Agricultural Science, Faculty of Agriculture Science, Daffodil International University

Duration: 2 weeks

Mode of Delivery: Blended learning 

Course Description

This course is designed to equip undergraduate and graduate students from agricultural and non-agriculture backgrounds with practical skills in designing, implementing, and managing field-based agronomic experiments. The course covers experimental layout, sampling protocols, use of field instruments, data collection, quality assurance, and preliminary data analysis to support evidence-based agricultural decision-making. 

Evidence of Demand

There is an increasing need for skilled field technicians in agricultural R&D. There is strong demand from public research institutes, private seed/agrochemical companies, and NGOs for professionals capable of data-driven crop management. 

Course Objectives

This course aims to:

• Teach practical skills in designing, implementing, and managing field-based agronomic experiments.

• Train participants in experimental layout and sampling protocols.

• Familiarize learners with the use of field instruments and proper data collection methods.

• Provide foundational knowledge in data quality assurance and preliminary data analysis to support evidence-based agricultural decision-making.

Course Content & Class Plan (Modules)

• Module 1: Principles of Experimental Design (RCBD, Split-Plot, Factorial Designs)

• Module 2: Field Plot Techniques (Land preparation, plot demarcation, treatment application)

• Module 3: Sampling Methods (Plant sample, Soil, plant tissue, pest/disease, and yield sampling)

• Module 4: Field Instrumentation (Use of different instruments used in agronomic research, soil probes, moisture meters, different sensors, etc.)

• Module 5: Data Collection Protocols (Paper-based vs. electronic data capture, field notebooks)

• Module 6: Data Quality Assurance

• Module 7: Explanation of Statistical Analysis (ANOVA, mean separation, interpretation)

• Module 8: Report Writing and Presentation of Field Results.

Practical & Field Work

• The course utilizes a blended delivery mode, with 60% of the training consisting of in-person field practical sessions at designated research farms.

• Practical elements include field assignments for layout and sampling, as well as compiling a Field Data Collection Portfolio with quality checks.

Learning Outcomes

After completing the course, participants will be able to:

• Design and lay out a statistically sound field experiment.

• Apply proper sampling techniques for soil, crops, and pests.

• Operate standard field data collection instruments and sensors.

• Collect, record, and manage field data with accuracy and integrity.

• Perform basic statistical analysis and interpret experimental results.

• Prepare a professional technical report on field research findings.

Target Audience & Requirements

Target Audience:

• Undergraduate and graduate students from agricultural and non-agriculture backgrounds.

• Early-career agronomists, agricultural extension officers, and research assistants.

• Graduate students in crop science and field technicians working in agricultural research stations or commercial farming operations.

Entry Requirements:

• A diploma or currently studying Undergraduate in Agriculture, Agronomy, Crop Science, Soil Science, or a related field.

• Minimum age of 18 years.

Tools & Resources

• Facilities & Locations: Access to experimental field plots.

• Instruments: Field instruments including lux meters, LAI, soil augers, moisture meters, GPS units, weighing scales, and canopy sensors.

• Technology: Laptops/tablets with spreadsheet software (MS Excel, R, or SPSS) and internet access for online modules.

• Materials: Printed field notebooks and data sheets.

Career Pathways

After completing this micro-credential, learners may:

• Proceed to advanced courses in Experimental Design and Data Analysis in Agronomy, Applied Field Research (Design, Data Management, Analysis and Reporting), or Advanced Agricultural Research Methods.

• Use this credential as a foundation for pursuing a Master's degree in Agronomy or Plant Sciences.

Assessment Criteria

• Practical Field Assignment (Layout & sampling) – 30%

• Field Data Collection Portfolio (with quality checks) – 30%

• Final Data Analysis Report (using real field data) – 30%

• Online Quiz (Theory & design principles) – 10% (Note: A pass mark of 60% is required out of the total 100%).

Certification

• Achieving the pass mark of 60% across the practical and theoretical assessments qualifies the participant for course completion.

Financial Information

• Tentative Course Fee: 1500 BDT

Course Overview

Microgreen Development and Its Applications in Food

Instructor(s):

• Dr. Nizam Uddin : Associate Professor and Head, Department of Nutrition and Food Engineering, DIU

• Rifat Khan Tushar : Founder & CEO, Water and Plant.

• Md. Naimur Rahman : Lecturer, Department of Nutrition and Food Engineering, DIU

⏱ Duration: 20 Hours | Mode of Delivery: Blended Learning (Interactive Lectures + Applied Laboratory Demonstrations + Practical Culinary/Cultivation Workshops)

Course Description

This comprehensive 20-hour course provides participants with practical knowledge and hands-on skills in sustainable microgreen production, post-harvest management, nutritional profiling, and microgreen-enriched food product development. It is designed to empower learners to formulate functional foods and construct viable commercial models tailored to urban agriculture ecosystems.

Evidence of Demand

Rapidly expanding global wellness and culinary market projections highlight an increasing reliance on nutrient-dense functional foods. Urban populations, particularly in rapidly densifying cities like Dhaka, face spatial limits for traditional cultivation, driving high demand for microgreen indoor agriculture, vertical farming solutions, and specialized knowledge in commercial post-harvest packaging.

Purpose and Objectives

Purpose: To provide participants with practical knowledge and hands-on skills in sustainable microgreen production, post-harvest management, nutritional profiling, and microgreen-enriched food product development.

Objectives:

• Differentiate microgreens from sprouts and baby greens based on developmental stages and growth parameters.

• Master environmental media preparation, substrate selection, and seed density setups.

• Formulate, execute, and evaluate functional food applications (salads, smoothies, enriched bakery items).

• Construct a viable commercial model tailored to microgreen urban agriculture ecosystems.

Course Content & Class Plan (Modules)

• Module 1: Introduction to Microgreens (3 Hours): Taxonomy, definition boundaries, sustainable food value chains, global market trends, and practical identification of common species.

• Module 2: Microgreen Production Techniques (5 Hours): Seed selection protocols, substrates, watering schedules, light/temperature management, and practical production tray setups.

• Module 3: Harvesting & Post-Harvest Management (3 Hours): Identification of maturity indicators, sanitation loops, packaging configurations, shelf-life extension methods, and structural laboratory report formulation.

• Module 4: Nutritional and Functional Properties (3 Hours): Evaluation of phytochemicals, anti-inflammatory properties, comparative analysis with mature plants, and diagnostic literature review exercises.

• Module 5: Food Applications of Microgreens (4 Hours): Functional food synthesis, incorporation into ready-to-eat products, sensory panel analysis, and a food product development workshop.

• Module 6: Entrepreneurship & Commercial Production (2 Hours): Cost-benefit analysis, vertical urban farming scaling, local market branding, and business model canvas formulation.

Practical & Field Work

• Cultivation: Practical production tray setups, seedling sowing, watering, and disease management.

• Harvest & Post-Harvest: Identifying maturity indicators and executing packaging and shelf-life extension methods.

• Culinary Workshop: Formulating and testing microgreen-enriched functional foods (salads, smoothies) using systematic sensory standards.

• Business Planning: Designing scalable urban farming business strategies and mapping budget layouts.

Learning Outcomes

Upon successful completion, learners will be able to:

1. Distinguish suitable microgreen seed varieties, select growing media, and control target environment variables.

2. Demonstrate practical seedling sowing, watering, disease management, and harvesting procedures.

3. Formulate and test a microgreen-enriched functional food product using systematic sensory standards.

4. Design a scalable, resource-efficient urban farming business strategy mapping budget layouts and revenue lines.

Target Audience & Requirements

    Target Audience:

• Students of Nutrition, Food Engineering, Agriculture, Food Science, Public Health.

• Commercial entrepreneurs, urban planners, home gardeners, and hospitality or food industry processing professionals.

     Entry Requirements:

• Basic computer literacy and fundamental understanding of basic biological or health sciences.

• Open to beginners; no prior farming or advanced culinary certification required.

• Minimum Age: 18 Years.

 Career Pathways

• Earns 1 Credit Hour within the DIU-MCA framework.

• Establishes the foundational technical skills required for direct pathways into higher-tier programmatic specializations such as Advanced Controlled Environment Agriculture (CEA), Commercial Hydroponic System Design, or Functional Food Enterprise Management.

Assessment Criteria

Fully mapped to an Outcome-Based Education (OBE) scheme:

• Functional Product Development Project: 20%

• Hands-On Lab Work & Cultivation Maintenance Tasks: 20%

• Business Plan Group Presentation: 15%

• Final Technical Viva Voce Defense: 15%

• Objective Module Quizzes: 10%

• Conceptual Assignments & Research Tasks: 10%

• Comprehensive Post-Harvest Laboratory Report: 10%

Tools & Resources

• Climate-controlled training lab, specialized seedling trays, growing substrates (Cocopeat/biodegradable mats).

• Optimized growth lighting grids, clean seed banks, food preparation facility tools.

• Access to the DIU Learning Management System (LMS).

• Class Size: Maximum 25-30 participants per operational batch.

Financial Information & Certification

• Tentative Course Fee: 2,500 BDT (DIU Students/Alumni/Agriculture and Nutrition Research Members) | 4,500 BDT (External Candidates/Entrepreneurs).

• Certification: Micro-credential professional certification (1 Credit Hour equivalent) issued upon successful completion.

Course Overview

Operation & Maintenance of Industrial Substations and Generating Stations (Batch 02)

⏱ Duration: 12 Weeks | 36 Contact Hours (3 Hours per Week)

Evidence of Demand

With the rapid expansion of industrial zones, power plants, EPZs, Hi-Tech Parks, and modern electrical infrastructure in Bangladesh, the demand for skilled professionals in substation and generator operation & maintenance is growing significantly.

Although many engineers and technicians graduate with strong theoretical knowledge, there remains a critical skills gap in hands-on operation, fault diagnosis, safety compliance, and maintenance of live electrical systems such as 33/11 kV substations and industrial generating stations.

Industries now seek professionals who can operate equipment confidently, follow safety standards, reduce downtime, and ensure uninterrupted power supply. This micro-credential course directly responds to that industry demand by delivering practical, site-based, and industry-aligned training.

Purpose and Objectives

This course aims to:

• Provide hands-on training in the operation and maintenance of industrial substations and generating stations

• Develop practical skills in handling transformers, switchgear, LT panels, generators, and protection systems

• Enhance understanding of industrial load management, grounding, and safety protocols

• Familiarize learners with real-world equipment, testing methods, and troubleshooting techniques

Tentative Syllabus (Highlights)

• Introduction to 33/11 kV and 11/0.415 kV substations

• Substation layout, HT & LT switchgear

• Power transformers: operation, protection, and maintenance

• Industrial LT distribution systems & load management

• Diesel and gas generator installation, operation & maintenance

• Battery banks, DC systems, grounding & lightning protection

• Electrical safety standards (BNBC, IEC, NFPA)

• Industrial site visits and final practical evaluation

Learning Outcomes

After completing the course, participants will be able to:

1. 1. Identify components of substations & generators.
   2. Understand single-line diagrams (SLD) & switch gears.
   3. Routine inspection, Operation and Maintenance (O&M) of Substation and Generator.
   4. Troubleshoot of Substation and Generator.
   5. Follow Personal Protective Equipment (PPE) and logout and tag out (LOTO) procedures.
   6. Different type of test of substation and generating station.
   7. Substation load distribution and Power Factor Correction.

Target Audience

• Diploma and BSc-level engineering students (EEE, Power, Mechanical)

• Substation and generator operators or technicians

• Junior field engineers and maintenance personnel

• Professionals from factories, power plants, EPZs, and EPC companies

Entry Qualifications

1. B.Sc. in Electrical and Electronic Engineering (Completed or currently pursuing, Level 2–Level 4)
2. Diploma in Engineering (Electrical, Electronic, Power).
3. Technician with industrial experience (Educational qualification be flexible).

Progression Pathway

After completing this micro-credential, learners may:

1. Assistant Engineer.(Substation and generating station)
2. Maintenance Engineer. (Manufacturing (FMCG), Footwear, Textile).
3. Assistant Safety Engineer. (Industries, Constructions)
4. Service Engineer. (Substation and generator Supply Company)
5. Project Engineer. (Constructions Projects, Architecture Firm, Engineering Firms, Interior Design)
6. Sir/Technical Support Assistant (Diesel Generator).

Assessment Criteria

• Class participation & attendance – 10%

• Weekly quizzes / viva – 20%

• Practical skill evaluation / group project – 40%

• Field visit report – 10%

• Final practical evaluation & demonstration – 20%

Resource Requirements

Facilities & Equipment

• Multimedia-equipped classrooms

• Functional 33/11 kV and 11/0.415 kV substations

• Industrial generator stations

• Battery banks, DC systems, and protection panels

Tools, Instruments & Materials

• Insulation Resistance (IR) testers

• Earth resistance testers

• Transformer oil testing kits

• Multimeters, clamp meters

• PPE, LOTO kits, relay testing equipment

Learning Materials

• Course manual & handbook

• Weekly presentation slides

• Maintenance checklists

• Field visit logbook

• Safety standards documentation (BNBC, IEC, NFPA)
  
  
  

Standard Course Fee:

The following discounts currently apply:

• Daffodil Students: Tk 2,500/-
• Non-Daffodil Students: Tk 3,000/- (60% Discount Promotional Offer)