5 IIT AI Courses that go beyond prompting to advanced Agentic AI

Prompting helps people interact with AI models, but it does not explain how to build autonomous systems. Agentic AI also requires programming, retrieval, planning, tool integration, memory, orchestration, testing, security, and deployment.

The five programs below range from broad AI foundations to focused RAG and multi-agent engineering.

How We Selected These IIT AI Courses

• Agentic AI relevance: Planning, tool use, RAG, memory, orchestration, and multi-agent systems
• Technical depth: Programming, algorithms, ML, deep learning, LLMs, and computing systems
• Applied learning: Labs, projects, capstones, testing exercises, and deployment work
• Production readiness: APIs, containers, observability, security, evaluation, and governance
• Professional suitability: Formats compatible with working schedules
• Credential clarity: Distinction between diplomas and certificates

Overview of the 5 IIT AI Courses

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

This IIT AI course builds the technical base for dependable agentic systems. It covers data pipelines, ML, deep learning, LLMs, fine-tuning, and deployment.

Delivery & Duration: Online, 18 months, with 12 to 14 hours of weekly study

Credentials: 36-credit e-Postgraduate Diploma from IIT Bombay and alumni status after successful completion

Instructional Quality & Design: Live IIT Bombay faculty classes, assignments, case studies, supervised projects, campus immersion, examinations, and a faculty-guided capstone

Program Highlights: Python, SQL and NoSQL, regression, classification, clustering, neural networks, transformers, LLM fine-tuning, Docker, Kubernetes, and model management

Outcomes: Learners can prepare data, build and assess ML models, create GenAI applications, and deploy scalable solutions using cloud and container infrastructure.

Why It Stands Out

• Formal credit-based postgraduate diploma
• Links model development with deployment
• Builds foundations for later agent engineering

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

This production-focused program progresses from LLM foundations and model customization to RAG, agent architectures, external tools, and deployment.

Delivery & Duration: 100% live online, 8 months

Credentials: Executive Post Graduate Certificate from IIT Kharagpur, with executive alumni recognition and an on-campus award ceremony

Instructional Quality & Design: Live IIT Kharagpur CSE faculty teaching, six modules, system-building exercises, a guided project, and a faculty-mentored industry capstone

Program Highlights: LLM engineering, LoRA and QLoRA, hybrid-search RAG, reranking, evaluation pipelines, agent planning, tool use, multi-agent coordination, containerized APIs, and monitoring

Outcomes: Participants can fine-tune an open-source LLM, build enterprise RAG, develop a multi-agent workflow, and deploy a monitored AI API.

Why It Stands Out

• Gives agentic AI a production context
• Faculty-led live instruction
• Includes several applied system builds

3. e-Postgraduate Diploma in Computer Science and Engineering - IIT Bombay

This IIT Bombay CSE program takes a systems-first route. It combines programming, algorithms, databases, security, and infrastructure with reinforcement learning, GenAI, and computer vision.

Delivery & Duration: Online, 12 months, with 12 to 16 hours of weekly study

Credentials: Up to 36 IIT Bombay credits and an e-Postgraduate Diploma in CSE, with alumni status after completion

Instructional Quality & Design: Weekly live CSE faculty sessions, course baskets, projects, formal assessments, campus interaction, and in-person examinations

Program Highlights: Unix, C, C++, Python, algorithms, complexity, software security, cryptography, database internals, big-data systems, reinforcement learning, GenAI, and computer vision

Outcomes: Learners develop the engineering judgment to write reliable programs, select suitable algorithms, work with secure data systems, and build software layers for AI applications.

Why It Stands Out

• Strengthens the computer science base behind agents
• Covers systems, security, programming, and AI
• Provides a formal postgraduate CSE credential

4. Advanced Certificate Programme in Agentic AI and RAG Engineering - IITM Pravartak

Designed for professionals with programming experience, this program covers Python APIs, RAG, agent memory, multi-agent debugging, MCP, observability, security, and CI/CD.

Delivery & Duration: Live online weekends, 7 months, with 10 to 12 hours of weekly study

Credentials: Verified IITM Pravartak certificate plus three IBM industry certificates

Instructional Quality & Design: Weekly expert sessions, selected faculty classes, 20+ assignments and projects, virtual labs, a capstone, and optional research park immersion

Program Highlights: FastAPI, LangGraph, LlamaIndex, vector databases, RAG evaluation, agent testing, planner-executor patterns, MCP servers, tracing, Docker, CI/CD, and governance

Outcomes: Learners can build production RAG pipelines, engineer multi-agent systems, test failures, monitor performance, control costs, and deploy governed AI services.

Why It Stands Out

• Treats testing and observability as core skills
• Covers RAG and agent engineering together
• Requires complete systems, not only prompts

5. Certificate in Agentic AI - Great Learning and IIT Bombay

This agentic AI course option is dedicated to agent architecture. It covers how agents reason, call tools, retrieve knowledge, delegate tasks, use memory, and work within human controls.

Delivery & Duration: Online, 5 months, with 4 to 6 hours of weekly work

Credentials: Certificate of Completion from IIT Bombay

Instructional Quality & Design: Weekly live faculty sessions, guided labs, applied projects, peer learning, and dedicated program support

Program Highlights: MCP, RAG, GraphRAG, vector databases, CrewAI, LangGraph, ReAct, Chain-of-Thought, router patterns, function calling, memory, and multi-agent orchestration

Outcomes: Learners can design autonomous agents, connect tools and organizational knowledge, coordinate specialized agents, and add monitoring, guardrails, and human review.

Why It Stands Out

• Dedicated focus on agent architecture
• Uses current retrieval and orchestration frameworks
• Lower weekly workload than the diploma programs

How to Compare the Options

A diploma may suit someone who needs stronger programming, ML, or systems knowledge. A focused certificate may fit a developer who now needs RAG, MCP, orchestration, testing, or deployment practice.

Projects should require learners to connect models with data and tools, handle failures, and define when human approval is required.

Conclusion

A useful AI course should move beyond prompt templates and explain how intelligent systems behave under real operating conditions. That includes retrieval quality, memory design, tool reliability, security, cost, observability, and human oversight.

Before enrolling, compare prerequisite knowledge, credential type, live-learning commitment, project depth, and production tooling. The course should address a clear technical gap and provide enough practical work to show that the learner can build, test, and maintain an AI system.

(This article is sponsored; EPN takes no responsibility with this editorial.)