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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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⏱ Duration: 16 Contact Hours (2 hours per Session) | Mode: offline
The micro-credential course “Data Analysis with SPSS (Basic to Intermediate)” is designed to develop students’ fundamental skills in data management, statistical analysis, and interpretation using SPSS software. The course aims to help learners conduct academic and research-based data analysis efficiently and accurately, enabling them to perform evidence-based research, prepare research reports, and enhance their academic and professional competencies in various fields such as Nutrition, Public Health, Business, and Social Sciences.
Upon completion of this course, participants will be able to:
After completing the course, participants will be able to:
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