This course introduces students to Agentic AI, a fast-growing area where AI systems can plan, reason, act, and adapt with a level of autonomy. Across ten focused sessions, students learn how agents make decisions, use tools, manage tasks, and work in multi-step workflows. The course blends core concepts with hands-on activities so students can design simple agentic pipelines on their own. By the end, they gain a clear understanding of how modern agentic systems power automation, engineering tasks, data operations, and real-world applications.
What you'll learn
Module 1: Foundations of Agentic AI
Hours: 4 (Day 1–2)
- What makes AI “agentic”
- Agent architectures and components
- Goal-driven behavior and action loops
- Reasoning, planning, context handling
- Real-world examples of agentic systems
Module 2: Autonomous Decision-Making and Tool Use
Hours: 4 (Day 3–4)
- Multi-step reasoning
- Task decomposition and planning
- Tool invocation and action execution
- Memory systems and state tracking
- Hands-on demos with simple agent pipelines
Module 3: Designing and Building Agentic Workflows
Hours: 6 (Day 5–7)
- Workflow orchestration
- Prompt engineering for agents
- API-based agent tools
- Multi-agent collaboration basics
- Building a small agent system (guided activity)
Module 4: Applications of Agentic AI in Engineering and Computing
Hours: 4 (Day 8–9)
- Agentic AI for automation and data tasks
- Use cases in software engineering, IoT, cybersecurity, education
- Evaluation metrics for agent behavior
- Strengths, weaknesses, and limitations
Module 5: Mini-Project and Review
Hours: 2 (Day 10)
- Students build or present a small agentic workflow
- Discussion on improvements and extensions
Course wrap-up and future directions
- Students will be able to explain how agentic AI systems plan, reason, and operate autonomously.
- Students will design and test basic agentic workflows using real tools and datasets.
- Students will evaluate the performance and behavior of agents in different problem settings.
- Students will apply agentic AI concepts to mini projects, demonstrating practical understanding and creativity.
1. Who can enroll in this course?
Students from CSE, IT, AIML, Data Science, and related branches. Basic programming knowledge is helpful but not mandatory.
2. Do I need prior experience in AI?
No. The course starts with fundamentals and gradually moves to applied concepts.
3. Will there be hands-on practice?
Yes. Students work on guided activities and a small mini-project in the final session.
4. What skills will I gain?
You learn how agentic systems think, plan, use tools, and carry out tasks. You also learn to design and test simple agent workflows.
5. Is there a certificate?
If your institution issues one, this course fits well for certification on completion and project submission.
6. Can this help with projects or internships?
Absolutely. Agentic AI is becoming a core skill in automation, research, and industry tools, making it valuable for academic and industry opportunities.
