Course Overview

Automation of Information Institutions using Koha-ILS and MARC21

⏱ Duration: 4 Days (Intensive Workshop) | In-person Hands-on Lab Training

Instructor

• Lead Instructor: Dr. Md. Milan Khan (Librarian, DIU; PhD in LIS, Univ. of Kalyani)
• Master Trainer: Md. Abdul Monnaf Sarker (Sr. Library Officer, DIU; PGDIT, JU)
• Co-Trainer: Syeda Aklima Begum (Library Officer, DIU; 20 years cataloging experience)
• Program Assist: Umme Ahasan (Library Officer, DIU)

Course Description 

This professional course is designed to equip library professionals and fresh graduates with specialized skills in library automation. It focuses on the installation, configuration, and management of Koha, the leading open-source Integrated Library System (ILS), combined with MARC21 bibliographic standards. The training addresses the need for modern digital hubs by teaching participants how to transition traditional libraries into automated, searchable, and interoperable systems.

Evidence of Demand

• Global Standard: Library automation is rapidly becoming a global standard for compliance and efficiency in academic and research institutions.
• National Need: Institutions in Bangladesh are actively seeking professionals who can transition traditional libraries into automated, searchable digital hubs.
• Mandatory Skill: For planning and managing libraries in universities, research institutes, and government organizations, knowledge of Koha and MARC21 is now considered a mandatory skill.
• Employment Gap: Employers increasingly seek professionals trained in Koha and library data standards, creating a strong demand for skills in installation, cataloging, and system administration.

Purpose and Objectives 

This course aims to equip library professionals and students with the technical skills to implement and manage automated library systems. Objectives:

• Master the installation and configuration of Koha (on Linux/Ubuntu).
• Understand bibliographic standards using the MARC21 framework.
• Learn to manage cataloging, circulation, report generation, and patron management digitally.
• Enable participants to customize OPAC (Online Public Access Catalog) for user-friendly access.

Tentative Syllabus (Highlights)

• Module 1: Introduction & Installation: Linux (Ubuntu) basics, Koha Installation, Post-install setup.
• Module 2: Administration & Configuration: Global system preferences, Library setup, Patron categories.
• Module 3: Cataloging with MARC21: Creating bibliographic frameworks, Z39.50/SRU targets.
• Module 4: Circulation & Serials: Check-in/Check-out rules, Fines, Serials control.
• Module 5: Reports & Tools: SQL Reports, Label creation, Batch patron modification.
• Module 6: OPAC Customization: Branding, search optimization, user account features.

Practical & Field Work

• Hands-on Lab Training: The course is delivered as an in-person, intensive workshop with a focus on practical implementation.
• Live Installation: Participants will perform live installation and configuration of the Koha ILS server.
• Cataloging Practice: Practical assignments involve creating MARC21 records and managing library resources digitally.

Learning Outcomes Upon completion, participants will be able to:

• Install and maintain a Koha ILS server on Linux.
• Catalog library resources using international MARC21 standards.
• Configure circulation rules, fines, and patron permissions.
• Customize the OPAC interface for institutional branding.
• Generate administrative reports using SQL queries.

Target Audience

• Library & Information Science Professionals / Students.
• IT Officers managing institutional repositories.
• Archivists and Documentation Officers.
• School/College Librarians transitioning to automation.

Entry Qualifications

• Basic computer literacy.
• Background or interest in Library Science / Information Management.
• Library professionals seeking skill upgrades.
• Minimum Age: 22 Years.

Progression Pathway 

After completing this course, learners may progress to roles such as:

• Library System Administrator
• Digital Archivist
• Information Manager
• Metadata Specialist

Assessment Criteria

• Practical Test (50%): Live installation and configuration task.
• Cataloging Assignment (30%): Creating MARC21 records.
• Quiz (20%): Theory on ILS standards.

Resource Requirements

• Facilities: Computer Lab with Internet Access, Dedicated Server/VM for practice.
• Tools: Bootable Pendrives (for Linux install).
• Materials: Course outline with documents, pad & pen.

Tentative Course Fee

• Professionals: BDT 5,500

• Students: BDT 5,000 

Course Overview

Restorative Justice: A Relational Framework of Justice in Bangladesh

⏱ Duration: 12 Hours (Total) | 6 Lectures (2 Hours each)

Instructor

• Lead Instructor: Dr. Muhammad Asadullah
• Affiliation: Visiting Professor, Dept. of Law, DIU; Associate Professor, Justice Studies, University of Regina, Canada.
• Distinctions: Recipient of 2024 CTL Teaching Award, President’s Teaching Scholar, and Best Paper Prize from the European Society of Criminology.

Course Description 

This introductory course offers a brief history and key themes of Restorative Justice (RJ), positioning it as a paradigm shift from traditional punitive justice. It critically examines the values, principles, and practices of RJ, exploring major themes such as relationship building and community strengthening in detail.

Evidence of Demand

• Global Phenomenon: Restorative Justice (RJ) is now used in over 100 countries to address the deeper aspects of crime and conflict.
• Critical Need in Bangladesh: There is a critical need for alternative dispute resolution mechanisms to support Village Courts, Indigenous justice systems, and community policing.
• Professional Skill Gap: Legal professionals, NGO workers, and community leaders increasingly require skills to facilitate justice that focuses on healing and relationship building rather than just punishment.

Purpose and Objectives 

This course aims to introduce the history, values, and principles of Restorative Justice. Objectives:

• Critically examine RJ values like respect, humility, and responsibility.
• Explore the role of RJ in building relationships and strengthening communities.
• Provide a framework to apply RJ lenses to day-to-day conflicts and macro-level social changes.

Course Content & Class Plan

• Module 1: Why does this matter? (RJ as a paradigm shift, Notion of conflict).
• Module 2: What is it? (Definition, Values: Respect, Humility, Responsibility).
• Module 3: Does it work? (Evidence, Measuring success, Peacemaking circles, Victim-offender mediation).
• Module 4: Building Relationships (Relational theory of justice).
• Module 5: Building Community (Role of community in resolving conflicts).
• Module 6: Implementation (RJ in day-to-day life, Living restoratively).

Practical & Field Work

• Interactive Delivery: The course utilizes an interactive mode comprising lectures, experiential learning exercises, and role-plays.
• Case Analysis: Students will apply RJ principles to specific real-world scenarios through final case analysis.

Learning Outcomes Upon completion, participants will be able to:

• Explain the history and key concepts of Restorative Justice.
• Articulate the core values and principles of RJ.
• Identify various RJ practices within the Bangladesh context (Village Courts/Indigenous).
• Apply the Restorative Justice lens to personal and professional life.

Target Audience

• Law Students and Legal Professionals.
• NGO Workers and Human Rights Activists.
• Police Officers and Village Court Officials.
• Social Workers and Community Leaders.
• Anyone interested in Peace and Conflict Studies.

Entry Requirements

• Academic: Higher Secondary Certificate (HSC) or Bachelor’s degree (ongoing/completed).
• Interest: Interest in social justice and community service.
• Age: Minimum 18 Years.

Career Pathways After completing this course, learners may progress to roles such as:

• Mediator / Arbitrator
• Restorative Justice Facilitator
• Village Court Assistant
• NGO Program Officer (Human Rights/Justice)

Assessment Criteria

• Worksheets & Reflections (40%): Weekly submission based on readings.
• Participation (30%): Engagement in role-plays and discussions.
• Final Case Analysis (30%): Applying RJ principles to a specific scenario.

Resource Requirements

• Materials: Reading materials (Fisher, Zehr, Braithwaite) and handouts for worksheets.
• Facilities: Multimedia classroom.

Tentative Course Fee

• Daffodil Students: BDT 1,500
• Non-Daffodil Participants: BDT 2,500 (This is a promotional offer).

Course Overview

Conflict Resolution : Transforming Challenges into Opportunities

⏱ Duration: 12 Hours (Total) | 6 Lectures (2 Hours Each)

Instructor

• Lead Instructor: Dr. Muhammad Asadullah
• Affiliation: Visiting Professor, Dept. of Law, DIU; Associate Professor, Justice Studies, University of Regina, Canada.
• Distinctions: Recipient of 2024 CTL Teaching Award, President’s Teaching Scholar, and Best Paper Prize from the European Society of Criminology.

Course Description
This introductory course familiarizes participants with key concepts of conflict, peace, conflict transformation, justice, and reconciliation. It moves beyond government-led resolutions to empower citizens with the skills to address crimes and conflicts at personal, relational, structural, and cultural levels. Through the "Peacebuilding Wheel" model, participants examine intervention options, their strengths and limitations, and how to choose contextually appropriate solutions.

Evidence of Demand

• Ubiquity of Conflict: Crimes and conflicts are pervasive issues affecting communities at personal, relational, structural, and cultural levels, creating a constant need for resolution skills.
• Need for Constructive Change: There is a critical need for professionals and community members who can address issues through constructive change processes rather than punitive measures.
• Sector-Wide Demand: Significant demand exists for skills in conflict analysis, nonviolent communication, and peacebuilding interventions across policing, social services, education, and community leadership sectors.

Purpose and Objectives
The purpose of this course is to familiarize participants with key concepts of conflict transformation, justice, and reconciliation. Objectives:

• Understand different conflict analysis tools (Pyramid, Onion, Conflict Tree).
• Develop essential skills for facilitating conflict resolution and reflective practice.
• Apply peacebuilding interventions using the "Peacebuilding Wheel" model.
• Examine strengths and limitations of various intervention models.

Course Content & Class Plan

• Week 1: Understanding Conflict: Theories of conflict, violence vs. conflict, community relations, and conflict transformation.
• Week 2: Tools for Conflict Analysis: Deep dive into analytical models including the Pyramid, Onion, Conflict Tree, and Timeline models.
• Week 3: Shame and Trauma: Understanding reintegrative vs. stigmatizing shame and the impact of trauma on conflict.
• Week 4: Peacebuilding Wheel: Exploration of Trauma Healing, Restorative Justice, Human Security, and Spirituality.
• Week 5: Nonviolent Communication & Active Listening: Developing emotional intelligence, empathy, and a reflective mindset.
• Week 6: Mediation and Negotiations: Theories and types of mediation and negotiation strategies.

Practical & Field Work (Experiential Learning)

• Mode of Delivery: Interactive Workshop comprising lectures, role-plays, and case studies.
• Methodology: The course relies heavily on experiential learning exercises and participatory methods.
• Class Limit: Class size is capped at 30 participants to ensure effective role-play and engagement.

Learning Outcomes

Upon completion, participants will be able to:

• Analyze conflicts using tools like the Onion and Conflict Tree models.
• Apply analytical tools to interpersonal and community case studies.
• Demonstrate reflective practice skills essential for conflict resolution.
• Design appropriate peacebuilding interventions for different conflict levels.

Target Audience

• Professionals in Policing and Justice Studies
• Community Leaders and Social Service Providers
• School Teachers, Educators, and Parents
• Youth & Outreach Workers
• Individuals interested in Social Science

Entry Requirements

• Academic: Open to all (No specific academic prerequisite mentioned).
• Interest: A strong interest in social justice and community peacebuilding.
• Age: Minimum 18 years.

Career Pathways

Completing this course supports progression into roles such as:

• Mediator / Arbitrator
• Community Outreach Coordinator
• Peacebuilding Program Officer
• Restorative Justice Facilitator
• Social Worker

Tools & Resources

• Classroom: Multimedia setup for case study videos.
• Materials: Reading materials (Fisher, Braithwaite, Rosenberg).
• Visual Aids: Whiteboard/Flipcharts for mapping conflict trees.

Assessment Criteria

• Participation & Role-Play (40%): Engagement in experiential exercises.
• Case Study Analysis (30%): Applying tools to a real-world conflict scenario.
• Reflective Journal/Quiz (30%): Understanding of core concepts.

Tentative Course Fee

• Daffodil Students: BDT 1,500
• Non-Daffodil Participants: BDT 2,500 (This is a promotional offer)

Course Overview

Techno Commercial Attributes in Food Industry

⏱ Duration: 24 Hours (Total) | Mode: Hybrid (In-person + Lab Sessions + Online)

Instructor’s :

• Maruf Muhammad Ahsanur Rahman – Asst. Manager-Sales, Orana A/S (Expertise: Food Industry Sales & Strategy)
• Dr. Md Nazmus Saqib – Asst. Professor, Dept. of Food Technology & Engg., PSTU (Expertise: Food Processing)
• Farzana Akter – Lecturer (Senior Scale), Dept. of NFE, DIU (Expertise: Food Processing)

Course Description

This course is a hands-on, hybrid micro-credential designed to bridge the gap between technical engineering and business strategy. Through real-world case studies, supply chain simulations, and strategic decision-making workshops, it transforms graduates into industry-ready leaders capable of managing both the production floor and the balance sheet.

Evidence of Demand

• Rapid Industry Growth: Bangladesh’s food industry is experiencing rapid growth due to shifting consumer behaviors and macroeconomic factors.
• Critical Skills Gap: Employers struggle to find professionals who possess both Food Processing Technology expertise and Commercial Strategy acumen.
• Need for "Hybrid Professionals": Industry leaders need professionals who can manage production efficiency while understanding market trends, supply chains, and profitability. This course is designed to fill that critical gap.

Course Objectives

This course aims to:

• Bridge the Technical-Business Gap: Connect technical engineering knowledge with business strategy in the food sector.
• Develop Decision-Making Skills: Equip participants with techno-commercial decision-making frameworks.
• Foster Resilience: Foster resilience and innovation in food business operations.
• Integrate Key Concepts: Teach the integration of supply chain, demand forecasting, and cost control.
• Prepare Leaders: Prepare graduates for leadership roles in the competitive food industry.

Course Content & Class Plan (Modules)

• Session 1: Intro to Techno-Commercial Aspects (Industry challenges).
• Sessions 2-5: Supply Chain Management (Procurement, Logistics, Value Chain).
• Session 6: Demand Analysis & Market Trends (Consumer behavior).
• Sessions 7-8: Material Management & Transportation.
• Sessions 9-10: Communication & Networking (Supplier/Regulator relations).
• Sessions 11-12: Strategic Management (Cost control, Change management).
• Session 13: Decision-Making (Risk assessment, Troubleshooting).

Practical & Field Work 

• Simulations: Usage of simulation tools for Supply Chain games.
• Lab Exercises: Hands-on lab facilities for material management exercises.
• Case Studies: Real-world case studies conducted in multimedia classrooms.
• Strategic Workshops: Strategic decision-making workshops to simulate industry scenarios.

Learning Outcomes

Upon completion, participants will be able to:

• Apply intuitive decision-making frameworks to industrial problems.
• Evaluate the commercial potential of food manufacturing processes.
• Drive competitive advancement through strategic capacity building.
• Master supply chain and material management strategies.

Target Audience

• Food Industry Job Seekers.
• Bachelor’s degree holders in Food-related fields (NFE, Food Tech, Agriculture).
• Aspiring professionals seeking industry knowledge.

Entry Requirements

• Basic understanding of food processing.
• Bachelor's degree (preferred).
• Minimum Age: 21 Years.

Career Pathways

After completing this micro-credential, learners may progress to roles such as:

• Techno-Commercial Manager: Overseeing product development with a focus on profitability.
• Supply Chain Executive: Managing procurement and logistics for food enterprises.
• Production Planner: Optimizing manufacturing processes for cost efficiency.
• Technical Sales Specialist: Selling food ingredients/machinery with deep technical knowledge.
• Food Entrepreneur: Launching and scaling a food business with strategic insight.

Tools & Resources

• Classroom: Multimedia Classroom for case studies.
• Software/Tools: Simulation tools for Supply Chain games.
• Facilities: Lab facilities for material management exercises.

Assessment Criteria

• Problem-Solving / Group Tasks: 40%
• Projects: 20%
• Final Exam: 40%

Tentative Course Fee

• Regular Fee: 2,500 /-
• Promotional Offer: 2,000 /-

Course Overview

Basic Economics : Understanding Market Forces, Consumer Behavior, and the Global Economy

Instructors:

1. Dr. Munmun Shabnam Bipasha
• Position: Asst. Professor, Dept. of Business Admin, DIU.
• Qualifications: PhD in Economics (JU), MSS Criminology (DU), MSc Economics (JU).
• Experience: 15+ Research Articles published.
2. Prof. Dr. Mohammad Jahangir Alam
• Position: Professor, Economics Dept., Jahangirnagar University.
• Qualifications: PhD (Hiroshima University, Japan).

⏱ Duration: 12 Hours (6 weeks - 2 Hours per seasson) | Mode: In-person | Class Day: Weekend (Friday/Saturday) or Scheduled Workshop Day

Evidence of Demand

Understanding the fundamentals of economics is essential for individuals across all disciplines, as economic principles directly influence business decisions, government policies, and everyday personal choices. There is currently a strong demand for economic literacy among non-economics professionals—including engineers, healthcare providers, and entrepreneurs—who need to understand market behavior and apply economic reasoning in real-life situations.

Purpose and Objectives

This course aims to provide participants with a foundational understanding of core economic concepts and theories. Objectives:

• Analyze Markets: Enhance analytical skills related to market dynamics.
• Understand Behavior: Understand consumer behavior and production costs.
• Macro Analysis: Analyze macroeconomic policy and national income.

Detailed Course Content (Syllabus)

• Module 1: Introduction: Micro vs. Macro Economics, Scope.
• Module 2: Basic Problems: Scarcity, Opportunity Cost, Production Possibility Curve (PPC).
• Module 3: Demand & Supply: Laws, Determinants, and Curves.
• Module 4: Market Equilibrium: Price mechanism and Shifts.
• Module 5: Consumer Behavior: Utility and Indifference curves.
• Module 6: Production & Costs: Short-run vs. Long-run costs.
• Module 7: Market Structures: Perfect competition, Monopoly, Oligopoly.
• Module 8: National Income: GDP and GNP concepts.
• Module 9: Inflation & Unemployment: Causes and Business Cycles.
• Module 10: Money & Banking: Monetary policy.
• Module 11: Fiscal Policy: Taxation, Budget, and Public Expenditure.
• Module 12: International Trade: Balance of payments and Exchange rates.

Learning Outcomes

Upon completion, participants will be able to:

• Analyze basic economic problems such as scarcity and choice.
• Evaluate market behavior using demand and supply analysis.
• Understand consumer behavior and pricing mechanisms.
• Assess national income, inflation, and unemployment trends.
• Evaluate the role of monetary/fiscal policies and international trade.

Target Audience

• Undergraduate/Graduate students.
• Corporate professionals and Executives.
• Entrepreneurs and Small Business Owners.
• Individuals interested in Banking and Public Policy.

Entry Qualifications

• Education: Bachelor’s degree from any discipline.
• Background: No prior background in economics required.
• Minimum Age: 22 Years.

Progression Pathway

After completing this course, learners may:

• Build a foundation for further studies in Business or Economics.
• Pursue careers in Banking, Public Policy, and Corporate Strategy.
• Engage in entrepreneurial ventures requiring market analysis.

Assessment Criteria

• Method: MCQ-based examination.
• Pass Requirement: Minimum 80% score.
• Certification: Certificate in Basic Economics.

Resource Requirements

Learning Materials & Tools:

• Facilities: Multimedia classroom setup.
• Class Size: 25–30 Participants.

Financial Information

• Tentative Course Fee:
• Promotional: BDT 700
• Regular: BDT 2,000

Course Overview

Medical Image Processing with Machine Learning : Revolutionize Healthcare Diagnostics with AI & Computer Vision

Instructors:

• Dr. S M Hasan Mahmud (Associate Professor, Dept. of SWE, DIU)
• Md. Tarek Aziz (AI Engineer, ATI Limited)

⏱ Duration: 6 Weeks | 24 Contact Hours (Blended: Online Lectures + In-person/Virtual Labs)

Evidence of Demand

The global AI in Healthcare market is currently experiencing explosive growth, creating a massive skills gap in the intersection of medicine and technology. Hospitals, diagnostic centers, and HealthTech startups are actively seeking specialized engineers who can analyze complex medical data—such as MRI, CT scans, and X-Rays—using Artificial Intelligence.

This skill set is becoming critical for the modern telemedicine and automated diagnostics industry, particularly for tasks such as the automated detection of tumors, pneumonia, and other pathologies. Despite the high demand, there is a scarcity of professionals capable of bridging the technical gap between traditional biomedical engineering and modern machine learning implementation.

Purpose and Objectives

This course is designed to bridge the gap between Biomedical Engineering and Artificial Intelligence, equipping learners with the ability to build automated diagnostic systems.

The course aims to:

• Master Pixel-Level Analysis: Provide deep technical knowledge of medical image formats (DICOM/NIfTI) and manipulation.
• Apply Advanced AI: Teach the application of Machine Learning and Deep Learning to solve real-world diagnostic problems.
• Automate Diagnostics: Enable students to build systems for detecting diseases like Cancer or Pneumonia automatically.
• Bridge Theory and Practice: Connect academic theory with real-world medical datasets to ensure industry readiness.

Detailed Course Content & Class Plan

This course follows a structured week-by-week progression from foundational image handling to advanced Deep Learning deployment.

Week 1: Introduction & Image Handling

• Theory: Understanding medical image formats (DICOM vs. NIfTI) and Ethics in Medical AI.
• Tools: OpenCV, NumPy, pydicom, Matplotlib.
• Lab: Loading, visualizing, and manipulating real MRI/CT scans.

Week 2: Preprocessing Techniques

• Theory: The critical importance of data cleaning in Medical AI pipelines.
• Techniques: Noise reduction, Histogram equalization, and Image normalization.
• Lab: Enhancing low-quality MRI data to improve analysis accuracy.

Week 3: Image Segmentation

• Theory: Strategies to separate the "Disease" (ROI) from the "Background" anatomy.
• Techniques: Thresholding, Region-growing, and Watershed algorithms.
• Lab: Automated Tumor Segmentation task.

Week 4: Feature Extraction & ML Classifiers

• Theory: Converting images into quantitative data using Statistical & Texture features.
• Techniques: Haralick features and Shape descriptors.
• Lab: Training classic ML classifiers (SVM/Random Forest) to detect Pneumonia patterns and evaluating with ROC/Confusion Matrices.

Week 5: Deep Learning in Medical Imaging

• Theory: Leveraging the power of Convolutional Neural Networks (CNNs) in diagnostics.
• Techniques: Transfer Learning (VGG16, ResNet) and Explainable AI (Grad-CAM) to visualize model decisions.
• Lab: Building a Deep Learning model for Multi-class Disease Classification.

Week 6: Capstone Project & Showcase

• Project: Design and build an end-to-end diagnostic solution (e.g., "Brain Tumor Detection System" or "Bone Fracture Analyzer").
• Presentation: Defense of findings, model accuracy, and real-world applicability to industry experts.

Learning Outcomes

After completing the course, participants will be able to:

• Process Medical Data: Handle and manipulate complex medical image formats using Python libraries.
• Enhance Quality: Apply noise reduction and preprocessing techniques to improve diagnostic clarity.
• Segment Anatomy: Isolate critical regions, such as tumors, from surrounding tissue.
• Train Models: Develop and train Machine Learning and Deep Learning models for precise disease classification.
• Deploy Pipelines: create a complete, end-to-end medical imaging analysis pipeline.

Target Audience

• University Students: 3rd to 4th-year students in CSE, BME, EEE, CIS, or SWE.
• Medical Professionals: Radiologists and clinicians interested in the intersection of healthcare and AI.
• Data Scientists: Professionals looking to pivot their career into the Healthcare domain.
• ML Engineers: Practitioners seeking specialized skills in computer vision for medicine.

Entry Qualifications

• Programming: Basic Python programming skills are required.
• Interest: A strong interest in Medical AI (Basic ML knowledge is helpful but not mandatory).
• Minimum Age: 18 Years.

Progression Pathway

After completing this micro-credential, learners may progress to roles such as:

• Medical Computer Vision Engineer
• Biomedical Data Scientist
• AI Research Assistant
• HealthTech Entrepreneur

Assessment Criteria

• Final Capstone Project: 40% (End-to-end solution design)
• Mini Projects (Labs): 30% (Practical implementation of weekly concepts)
• Weekly Quizzes: 20% (Theoretical understanding)
• Participation: 10% (Engagement in lectures and labs)

Resource Requirements

Tools, Instruments & Materials

• Software Environment: Python (Jupyter Notebook / Google Colab).
• Libraries: OpenCV, NumPy, pydicom, Matplotlib, TensorFlow/Keras or PyTorch.
• Hardware: Computers with GPU support (or Cloud access).
• Data: Real-world Medical Datasets (e.g., Kaggle, NIH X-Ray).

Standard Course Fee: Tk 5,000/-

The following discounts currently apply:

• Daffodil Students: Tk 3,000/-
• Non-Daffodil Students: Tk 3,000/- (Discounted from BDT 5,000)

Course Overview

Operation & Maintenance of Industrial Substations and Generating Stations

⏱ 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:

• Identify and explain components of industrial substations and generating stations

• Interpret single-line diagrams and protection systems

• Perform routine inspection and preventive maintenance

• Operate generators safely and manage industrial loads

• Apply electrical safety practices and hazard mitigation techniques

• Conduct basic testing of transformers, batteries, and grounding systems

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

• Diploma in Engineering (Electrical/Power/Mechanical) OR

• BSc in EEE, Mechanical, or related fields (students or graduates)

• Basic understanding of electrical systems and safety

• Prior industrial experience is an advantage but not mandatory

Progression Pathway

After completing this micro-credential, learners may:

• Work as Substation Maintenance Technician, Generator Operator, Electrical Safety Officer, or Maintenance Supervisor

• Progress to advanced certifications in:

  • Power System Protection

  • SCADA & Automation

  • High-Voltage Switching & Safety

• Apply skills directly to industrial jobs, internships, or apprenticeships

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: Tk 7,500/-

The following discounts currently apply:

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

Course Overview

Enterprise AI: Designing, Deploying, and Scaling AI Solutions for Business Transformation

Lead Instructor: Professor Dr. Emdad Khan (CEO, InternetSpeech Inc. USA)

Co-Instructor: Md. Ridoy Sarkar (Lecturer, Daffodil International University)

⏱ Duration: 10 Weeks | 48 Hours (Total)

Course Description

This course is designed to bridge the critical gap between technical AI skills and business value creation. Moving beyond experimental models, this program equips professionals to architect, govern, and scale AI solutions across large organizations. It focuses on integrating AI with legacy systems (ERP, CRM), ensuring compliance, and optimizing ROI for sustainable business transformation.

Evidence of Demand

With the rapid rise of AI and Digital Transformation, organizations are moving beyond experimental AI models to scalable, governed enterprise solutions. There is a critical gap for professionals who can bridge technical AI skills (Data Science, LLMs) with business value creation (ROI, Compliance, Integration). Industry demands architects who can deploy AI across supply chains, HR, and finance at scale.

Purpose and Objectives

The purpose of this course is to equip students with the skills to architect, govern, and scale AI solutions in large organizations. Objectives:

• Understand Enterprise AI architecture & Digital Twins.
• Learn to integrate AI with legacy systems (ERP, CRM).
• Master AI Governance, Security, and Compliance.
• Develop strategies for ROI optimization and scaling.

Course Content & Class Plan (Modules)

Tentative Syllabus:

• Module 1: Intro to Enterprise AI (Context & Maturity Models)
• Module 2: Generative AI & LLMs (RAG, Knowledge Assistants)
• Module 3: Enterprise Data Foundations (Data Lakes, Governance)
• Module 4: AI Solution Architecture (Cloud vs. On-Prem, Microservices)
• Module 5: Enterprise AI Use Cases & Case Studies (Finance, Health, Mfg)
• Module 6: AI & Agentic Workflow Development (Lifecycle, Feature Eng.)
• Module 7: MLOps & Model Lifecycle Management (CI/CD, Monitoring)
• Module 8: AI Integration with Enterprise Systems (ERP/CRM APIs)
• Module 9: AI Governance, Security & Compliance (Privacy, Ethics, Transparency)
• Module 10: Decision Intelligence & Analytics (Predictive vs. Prescriptive)
• Module 11: Scaling & Performance Optimization (Cost/Reliability)
• Module 12: Capstone Project (Design & Implementation)

Practical & Field Work

Note: Practical assessments constitute approximately 70% of the course grade.

• Labs & System Design: Hands-on tasks involving MLOps tools (Docker, MLflow), visualization (PowerBI/Tableau), and Python environments.
• Capstone Project: Students will design and implement a complete Enterprise AI solution, including defining the business problem, creating the architecture, and providing a live demonstration.
• Examples include: AI-Powered Academic Administration Systems, Enterprise Knowledge Assistants (RAG-based), and Predictive Analytics Dashboards.

Learning Outcomes

Upon completion, students will be able to:

• Strategize: Identify AI opportunities for business optimization.
• Architect: Design scalable Cloud/Hybrid AI systems.
• Integrate: Connect AI with enterprise apps via APIs.
• Govern: Implement security and compliance frameworks.
• Evaluate: Measure AI success via ROI and impact.
• Scale: Deploy sustainable systems using MLOps.

Target Audience

• CSE/SWE/CIS/ITM Students (3rd/4th Year)
• Data Scientists & ML Engineers
• Solution Architects & Project Managers
• Industry Professionals seeking AI leadership roles

Entry Requirements

• Minimum Age: 20 Years
• Basic Programming: Python recommended
• Foundational Knowledge: Introduction to AI/Machine Learning and fundamentals of Databases & Information Systems
• Resource Requirements: Internet/Cloud Access

Career Pathways

• Enterprise AI Architect
• AI Product Manager
• MLOps Engineer
• AI Transformation & Digital Transformation Consultant
• Chief AI Officer (CAIO) track

Tools & Resources

• Programming: Python Environment (Jupyter/Colab)
• MLOps Tools: Docker, Kubernetes, MLflow, Jenkins/GitHub Actions
• Cloud Platforms: AWS / Azure / Google Cloud (Conceptual & Hands-on)
• ML Frameworks: Scikit-learn, TensorFlow, PyTorch
• Visualization: PowerBI / Tableau

Assessment Criteria

• Case studies & assignments: 30%
• Labs & system design tasks: 30%
• Final project: 40%

Standard Course Fee: Tk 15,000/-

The following discounts currently apply:

• Daffodil Students: Tk 5,000/- (67% Discount Promotional Offer)
• Non-Daffodil Students: Tk 7,500/- 

Course Overview

Embedded Systems and IoT – Unlock the Future of Smart Technologies - Batch 2

Course Code: MC15001
Course Title: Embedded Systems and IoT – Unlock the Future of Smart Technologies
Start Date: October 16, 2025 📅
Duration: 18 weeks (3 modules, 6 weeks each, 72 hours total) ⏰
Mode: Blended (in-person, online, hands-on projects) 🌐
Class Size: Max 25 participants 👥
Course Equivalent: 2 Credit Hours
Course Fee: BDT 3,000 (discounted from BDT 4,000) 💸

Course Description 🚀
Embedded Systems and IoT – Unlock the Future of Smart Technologies (MC15001) taps into the booming demand for expertise in IoT and embedded systems, powering industries like smart homes, automation, and Industry 4.0. This hands-on course guides learners through building IoT prototypes, writing firmware, and mastering advanced embedded technologies using Arduino, Raspberry Pi, STM32, and RTOS. With real-world projects like smart home automation and industrial systems, participants will gain skills for high-demand careers in tech, supported by expert mentorship and industry-standard tools. 🌟

Learning Outcomes ✅
Participants will:

• Build and deploy IoT systems with real-time communication. 🌐

• Develop efficient firmware using Embedded C and RTOS. 💻

• Implement secure, scalable embedded solutions with STM32. 🔐

• Apply automation logic for industrial applications. ⚙️

• Create a portfolio of smart tech projects. 📜

Target Audience 🎓

• Engineering students (ECE, CSE, EE).

• Tech enthusiasts and hobbyists.

• Embedded firmware/IoT developers.

• Professionals upskilling in smart tech.

• Startup founders in IoT/automation.

Entry Requirements 📋

• Basic programming or electronics knowledge (helpful, not mandatory).

• Minimum age: 18 years.

Career Pathways 🚀

• Embedded/IoT Engineer roles in tech industries.

• M.Tech or postgraduate programs in IoT/embedded systems.

• Startup ventures in smart devices and automation.

Course Overview

Expert Network Engineering - 7 in One 

Course Code: MCA002
Course Title: Expert Network Engineering - 7 in One
Start Date: November 1, 2025 
Duration: 72 hours (12 weeks, ~6 hours per week) 
Mode: Blended (lab-based in-person, online classes, simulations) 
Class Size: 30 participants 
Course Equivalent: 6 Credit Hours
Course Fee: 10000 BDT (Discount Price 5000 BDT)

Course Description 

Expert Network Engineering - 7 in One (MCA002) addresses the critical shortage of skilled network engineers in Bangladesh’s $1.5B IT industry and global markets, where demand for certified professionals has surged due to cloud computing, IoT, and cybersecurity needs (BASIS, 2024). This comprehensive course combines industry-standard certifications (CCNA, MTCNA, Network+, Linux) with hands-on training in Cisco, MikroTik, network security, and data center management. Through labs, simulations, and a capstone project, participants will gain expertise in designing, configuring, and securing enterprise networks, preparing them for high-demand roles in ISPs, tech firms, and freelancing. 

Syllabus 

1. Core Networking Fundamentals

• Types of Network & Topologies.
• Introduction to Networking: LAN, WAN, MAN
• Network Devices & Cabling
• OSI & TCP/IP Models, Ethernets
• IP Addressing (IPv4 & IPv6) and Subnetting
• Switching & Routing
• VLANs & Trunking
• VLSM
• Static vs Dynamic Routing (RIP, OSPF, EIGRP, BGP)
• Hands-on: IP addressing, topology simulation (Packet Tracer)

2. Cisco Certified Network Associate (CCNA)

• Console, Telnet, and SSH access to devices
• Basic switch/router setup (hostname, banners, passwords)
• IPv4 and IPv6 address assignment
• Subnetting practice
• VLAN creation and assignment
• Inter-VLAN routing (router-on-a-stick)
• VLAN trunking (802.1Q)
• STP basic configuration and root bridge election
• Port security with sticky MAC and violation modes
• EtherChannel (LACP/PAGP)
• DHCP snooping and Dynamic ARP Inspection
• Static routing for IPv4 and IPv6
• Default routing
• OSPF (single-area and multi-area) for IPv4 and IPv6
• HSRP or VRRP (basic FHRP)
• PPP and PPP with PAP/CHAP authentication
• GRE tunnel between routers
• Basic IPSec site-to-site VPN demo
• Router and switch login security
• SSH remote management
• Standard and extended ACLs for IPv4 and IPv6
• DHCP server and DHCP relay (ip helper-address)
• NAT (static, dynamic, PAT)
• NTP client configuration
• Syslog to remote server
• SNMP basic setup
• DNS lookup and local hostname resolution
• Basic WLAN setup on WLC with SSID and WPA2-PSK and WLAN-VLAN mapping
• RESTCONF basic enablement and API usage
• Explore JSON/YAML outputs of show commands
• Use Postman to call device REST APIs (read-only)
• Troubleshoot VLAN, OSPF adjacency, ACL blocks, inter-VLAN routing, NAT, SSH, and interface issues.

MikroTik Certified Network Associate (MTCNA)

• Introduction to MikroTik RouterOS & Winbox
• Initial Configuration and Basic Management
• IP Addressing, DHCP Server, NAT and Firewall
• Bandwidth Management (Queues, Simple Queues, PCQ)
• PPPoE, Static IP, VPN and Remote Access Setup
• Backup, Logging, Monitoring, and Scripting

4. CompTIA Network+ Essentials

• Basic networking models (OSI vs TCP/IP)
• Types of networks (LAN, WAN, MAN, PAN, WLAN)
• IP addressing (IPv4/IPv6, subnetting, classes)
• Ports and protocols (TCP/UDP, DHCP, DNS, HTTP/S, FTP, SSH, SNMP)
• Routing vs switching concepts
• Wireless networking basics and standards (802.11)
• Network services (NAT, PAT, NTP, DHCP, DNS)
• Network devices (router, switch, firewall, access point, modem, NAS, load balancer)
• Cabling types (UTP/STP, fiber, coax)
• Connectors (RJ45, LC/SC, BNC, etc.)
• WAN technologies and connections
• Remote access methods
• Troubleshooting methodology
• Layer-wise troubleshooting (cables, interfaces, routing, DNS, DHCP)
• Common issues (IP conflicts, latency, VLAN misconfig, wireless interference)
• Tools: ping, tracert, ipconfig, nslookup, Wireshark, cable tester, TDR
• Fixing performance and connectivity problems

5. Network Security

• Fundamentals of Network Security
• Threats: Malware, DDoS, Phishing, Spoofing
• Firewalls, IDS/IPS, and Proxy Servers
• VPN Concepts and Secure Remote Access
• Port Security, AAA, and Wireless Security
• Basic Encryption and Authentication Techniques
• Security Policies and Risk Mitigation
• Cyber Hygiene and Best Practices
• Hands-on Firewall Configuration (Cisco/MikroTik)

6. Basic Linux for Networking

• File and directory management
• Viewing, creating, and editing text files
• Archiving and compressing
• Managing users and groups
• Configuring networking
• Hostname and name resolution
• Storage partitioning with fdisk / parted
• System rescue and password recovery

7. Data Center Management

• Overview of Data Center Architecture
• Rack, Cabling, and Power Management
• Cooling and Environmental Controls
• Redundancy: UPS, Backup, Failover Systems
• Physical and Logical Security
• Server Virtualization and Storage Basics
• Data Center Networking (Spine-Leaf, Core-Aggregation)
• Monitoring and Management Tools

Entry Requirements 

• Basic computer and internet knowledge.

• No prior networking experience required (IT background preferred).

• Minimum age: 18 years.

Career Pathways 

• Network Support Engineer, Network Administrator, Cisco/MikroTik Engineer.

• Network Security Associate, Data Center Technician, Linux Administrator.

• Freelance router configuration, IT consultancy, or ISP startup.

• Professional Certificate in Expert Network Engineering.