5 IIT Courses for Developing Skills in AI Models, GenAI Applications, and Agent Workflows

AI engineering now spans more than model training. Professionals may work with statistical learning and deep neural networks at one stage, then move into LLM applications, retrieval systems, model customization, deployment, and autonomous agents at another.

That makes the learning path less linear than it used to be. Some engineers need stronger foundations in data science and machine learning, while others are ready to work with RAG, MCP, tool calling, memory, and multi-agent orchestration.

The five IIT programs below cover different parts of that progression, from broader AI and data science education to focused GenAI and agent engineering.

5 IIT AI Courses

1. Certificate in Agentic AI – IIT Bombay

Professionals comparing options for an Agentic AI course will find this IIT Bombay certificate focused specifically on autonomous-system engineering. The curriculum establishes LLM and programming foundations before moving into retrieval, tool access, memory, reasoning patterns, MCP, orchestration, and collaborative agent systems.

Delivery & Duration: Five months, fully online, with weekly live IIT Bombay faculty sessions, guided labs, hands-on projects, and an optional campus immersion.

Credentials: Certificate of Completion from IIT Bombay.

Program Highlights: RAG, GraphRAG, vector databases, Tool-Augmented Generation, MCP and its Python SDK, LangGraph, CrewAI, Chain-of-Thought, ReAct, reflection, DSPy, LangSmith, FastAPI, Streamlit, Docker, HITL, monitoring, and safety.

Outcomes: Learners build agents that plan, reason, call tools, retain workflow knowledge, and collaborate across multi-step tasks. They also study how to monitor and deploy agentic applications with appropriate safeguards.

Why should you choose this course?

• The curriculum is centered on autonomous agents. MCP, memory, reasoning, and multi-agent coordination are core subjects, not short add-ons.
• Agent construction continues into operation. Monitoring, human intervention, security, APIs, and deployment come later in the learning path.

2. Executive Post Graduate Certificate in Generative AI & Agentic AI - IIT Kharagpur

IIT Kharagpur takes a production-first route through Generative AI. Learners move from deep learning and transformer foundations into advanced prompting, retrieval, LLM customization, multimodal AI, autonomous agents, and deployment.

Delivery & Duration: Eight months, 100% live online, taught by faculty from IIT Kharagpur's Department of Computer Science and Engineering.

Credentials: Executive Post Graduate Certificate from IIT Kharagpur.

Program Highlights: Foundation models, transformer architectures, hybrid RAG, reranking, PEFT, LoRA, QLoRA, multimodal AI, tool-using agents, multi-agent workflows, model serving, optimization, monitoring, and AI safety.

Outcomes: Learners build enterprise RAG systems, customize open-source LLMs, develop multi-agent applications, and address deployment considerations such as inference, performance, reliability, and production operations.

Why should you choose this course?

• Model customization receives significant attention. LoRA, QLoRA, alignment, and fine-tuning add depth beyond API-based GenAI development.
• The progression reaches production. Retrieval and agents are followed by serving, optimization, monitoring, and safety.

3. e-Postgraduate Diploma in Artificial Intelligence and Data Science - IIT Bombay

This IIT AI course provides the broadest data science foundation in the list. Its six-course, 36-credit curriculum connects programming and statistical reasoning with machine learning, deep learning, Generative AI, and practical deployment.

Delivery & Duration: Designed for completion in 18 months through synchronous online IIT Bombay classes, with around 12 to 14 hours of weekly study and in-person end-term examinations.

Credentials: e-Postgraduate Diploma in Artificial Intelligence and Data Science from IIT Bombay, with IIT Bombay eAlumni status after successful completion.

Program Highlights: Python, data analytics, statistical learning, regression, classification, clustering, deep learning, transformers, NLP, Generative AI, TensorFlow/Keras, PyTorch, Docker, Kubernetes, cloud deployment, and an AI-ML capstone.

Outcomes: Learners analyze and validate data, build predictive and deep learning models, use text data for GenAI applications, and develop end-to-end AI/ML solutions for business problems.

Why should you choose this course?

• The program builds the modeling layer in depth. Statistics, ML, deep learning, and data science come before production AI work.
• The AI-ML in Practice component connects models with deployment, including containers, cloud infrastructure, and an applied capstone.

4. Advanced Certificate in Agentic AI - CEP, IIT Delhi

IIT Delhi's certificate focuses on moving autonomous agents from architecture to enterprise deployment. Each module adds another layer, including reasoning, RAG, orchestration, multi-agent coordination, tool integration, governance, and reliability.

Delivery & Duration: Six months, fully online, with live IIT Delhi faculty sessions, module projects, assessments, and an enterprise capstone.

Credentials: Certificate of Successful Completion from CEP, IIT Delhi, for participants who meet the required academic and attendance criteria.

Program Highlights: LangChain, AutoGen, CrewAI, MCP, RAG, agent planning, tool use, role-based multi-agent coordination, workflow orchestration, APIs, HITL, governance, reliability, Docker, and deployment.

Outcomes: Participants design single-agent and multi-agent systems, integrate external tools and services, structure autonomous workflows, and build an enterprise-oriented agentic application.

Why should you choose this course?

• Every module leads to practical implementation, keeping architecture connected to building.
• Enterprise deployment is part of the core sequence, including governance, reliability, and human oversight.

5. Generative AI and Agentic AI for Developers - IIT Patna

IIT Patna takes developers from basic GenAI applications into more structured agent workflows. Learners first work directly with models and APIs before adding memory, application frameworks, advanced RAG, MCP, and LangGraph-based orchestration.

Delivery & Duration: Six months online with live and recorded classes, 30+ live sessions, 10+ projects and case studies, and a capstone.

Credentials: Certificate issued by IIT Patna.

Program Highlights: OpenAI and open-source models, Hugging Face, Ollama, vLLM, LoRA, QLoRA, structured outputs, conversation memory, LangChain, advanced RAG, MCP, LangGraph, retries, fallbacks, and workflow automation.

Outcomes: Learners build chat assistants, RAG applications, autonomous agents, and multi-step workflows, then combine models, memory, retrieval, and agent execution into portfolio-ready projects.

Why should you choose this course?

• Learners see what happens before frameworks are introduced. The course covers memory, parsing, retries, and API calls directly.
• The curriculum gradually builds toward agent workflows, moving from GenAI applications to RAG, MCP, and orchestration.

Conclusion

AI models, GenAI applications, and autonomous agents increasingly belong to the same engineering stack. The difference between programs often starts with where the learning begins: statistical modeling and deep learning, or LLM customization, retrieval, or agent orchestration.

When comparing Agentic AI courses, consider the technical layer you need next. A broader diploma can strengthen data science and model development, while focused certificates can help experienced professionals move faster into RAG, MCP, multi-agent systems, and production agent workflows.