Agentic AI and AI Agents
Build intelligent AI agents that reason, use tools, automate workflows, and solve real-world business problems.
This course introduces Agentic AI, autonomous AI agents, large language models, tool integration, and multi-agent systems. Students learn to design agents that plan tasks, use external tools, retrieve information, maintain context, and execute workflows with appropriate human oversight. Through practical exercises and projects, learners explore agent architectures, frameworks, API integration, evaluation, security, and deployment for real-world business applications.
- Duration
- 3 Months
- Level
- Beginner
- Language
- English, Hindi
- Time commitment
- 6–8 hours per week
- Course code
- AGENTIC-AI-101
Who this course is for
Students, graduates, software developers, Python programmers, AI enthusiasts, automation specialists, business analysts, and IT professionals who want to build AI agents and intelligent workflow automation solutions.
What you will learn
- - Explain Agentic AI concepts and AI agent architectures.
- - Understand the role of LLMs in autonomous systems.
- - Design agents that plan and execute multi-step tasks.
- - Build AI agents using Python and LLM APIs.
- - Integrate tools, APIs, and external data sources.
- - Implement memory and context management.
- - Develop multi-agent collaboration workflows.
- - Build retrieval-augmented AI agent applications.
- - Add human approval and supervision to agent workflows.
- - Evaluate agent accuracy, reliability, and performance.
- - Apply security controls and responsible AI practices.
- - Deploy practical AI agent solutions for business use cases.
Course curriculum
Module 1: Introduction to Agentic AI Module 2: Large Language Models for Agents Module 3: Python for AI Agents Module 4: AI Agent Architecture Module 5: Tool Calling and Integrations Module 6: AI Agent Frameworks Module 7: Multi-Agent Systems Module 8: RAG and Knowledge-Based Agents Module 9: Agent Security, Evaluation, and Deployment Module 10: Capstone Project
Prerequisites
Basic computer and internet knowledge. Basic Python programming is recommended. Familiarity with APIs and JSON is helpful. No previous AI agent development experience required. A laptop or desktop with internet access. Access to an LLM API or compatible model; some providers may charge usage fees.
Projects and practical work
- Project 1: Build a research assistant that gathers and summarizes information. - Project 2: Develop a document-question-answering agent using RAG. - Project 3: Create a customer support agent that uses approved knowledge sources. - Project 4: Build a multi-agent workflow for research, analysis, and report generation. - Project 5: Develop a task automation agent with tool calling and human approval. - Final Project: Build a business AI agent that plans tasks, integrates APIs, retrieves relevant data, handles errors, and operates with defined security permissions.
Certificate
Certificate of Course Completion Students who successfully complete the modules, practical assignments, and capstone project will receive an institute-issued Agentic AI and AI Agents Course Completion Certificate.