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

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)

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