Explore our comprehensive catalog of micro-credential courses designed to boost your skills and career. Flexible, industry-aligned, and recognized by employers.
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)
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.
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.
The purpose of this course is to equip students with the skills to architect, govern, and scale AI solutions in large organizations. Objectives:
Tentative Syllabus:
Note: Practical assessments constitute approximately 70% of the course grade.
Upon completion, students will be able to:
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Instructors:
⏱ Duration: 6 Weeks | 24 Contact Hours (Blended: Online Lectures + In-person/Virtual Labs)
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.
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:
This course follows a structured week-by-week progression from foundational image handling to advanced Deep Learning deployment.
Week 1: Introduction & Image Handling
Week 2: Preprocessing Techniques
Week 3: Image Segmentation
Week 4: Feature Extraction & ML Classifiers
Week 5: Deep Learning in Medical Imaging
Week 6: Capstone Project & Showcase
After completing the course, participants will be able to:
After completing this micro-credential, learners may progress to roles such as:
Tools, Instruments & Materials
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Automate with AI Agents for Streamlined Success!
⏱ Duration: 14 Hours (Equivalent of 1 Credit Hour) | Mode of Delivery: Hybrid (Live Online Training & Physical Class)
Course Description
In today’s fast-moving digital world, the ability to automate tasks and work smarter is no longer optional — it is essential. This training program is designed for professionals and organizations looking to harness the power of AI Agents to transform their business operations. The curriculum covers essential concepts like AI-Driven Automation, Prompt Engineering, and Workflow Optimization. Participants will explore how to create and deploy no-code AI Agents, integrate them into existing systems, and automate routine tasks for enhanced productivity—all without writing a single line of code.
Instructor(s)
Evidence of Demand
In today’s fast-moving digital world, the ability to automate tasks and work smarter is no longer optional—it is essential. Organizations and professionals urgently need to harness AI tools to streamline daily operations, improve productivity, and enhance efficiency without relying heavily on coding.
Purpose and Objectives Purpose:
To help participants leverage modern AI tools to transform business operations via no-code agents.
Objectives:
Course Content & Class Plan (Tentative Syllabus)
Practical & Field Work
Learning Outcomes
By the end of this course, participants will know:
Target Audience & Requirements
Target Audience:
Entry Qualifications / Requirements:
Career Pathways (Progression)
Assessment Criteria
Evaluation based on:
Tools & Resources
Tools, Instruments & Materials:
Learning Materials:
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⏱ Duration: 12 Weeks (Approx.) | 48 Hours (Total) | Mode: Online / Blended (Live sessions + Labs)
To provide foundational knowledge and practical skills in investment analysis and portfolio management, enabling informed decision-making and effective portfolio strategies.
Instructor(s):
This course equips students with the advanced skills to design, build, and deploy autonomous AI agents. Moving beyond simple generative content creation, participants will learn to build systems that can reason, plan, and execute complex workflows autonomously. Students will master Agentic architectures, memory management, tool integration, and multi-agent coordination using industry-leading frameworks.
The AI industry is shifting from "Generative AI" (content creation) to "Agentic AI" (task execution). Tech giants like Microsoft (AutoGen) and OpenAI (Assistants API) are investing heavily in agents. There is a massive skills gap for professionals who can build autonomous systems that reason, plan, and use tools to automate complex workflows in enterprise and academia.
To equip students with the skills to design, build, and deploy autonomous AI agents.
Objectives:
Students will build fully functional agents such as:
Upon completion, students will be able to:
Target Audience:
Entry Requirements:
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Instructor:
1. Dipto Biswas | Lecturer (Senior Scale) , Dept. of Information and Communication Engineering (ICE), DIU. His research interests include Machine Learning, NLP, Expert Systems, Cloud Computing, and AI.
2. Md. Sakaid Hosain Shakir | Lecturer , Department of Information and Communication Engineering, DIU
⏱ Duration: 48 Hours | Pace: Self-paced with weekly deadlines and live sessions
A 2025 study by the UK's Department of Education revealed that 90% of businesses are grappling with skills gaps, particularly in entry-level and specialist roles. The data science field is experiencing rapid expansion, with projections indicating a market size of $178.5 billion globally by 2025. In Bangladesh, industries like e-commerce (e.g., Daraz), telecommunications, and banking are increasingly adopting data-driven strategies, creating a vibrant job market for data science professionals.
Purpose: To equip learners with essential data science skills, enabling them to analyze, visualize, and interpret complex datasets to make data-driven decisions.
Objectives:
Learners will work on a Collaborative group project (selecting a real-world problem, analyzing data, and building a model) and a Final Capstone Project. The capstone requires students to apply everything learned to develop and present a comprehensive data science solution involving data collection, cleaning, analysis, model building, and evaluation.
Career opportunities in:
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