The Indian Institute of Technology Delhi (IIT Delhi), through its Continuing Education Programme (CEP), has launched an Executive Certificate in Agentic AI Systems (Foundation to Deployment). This six-month program aims to equip professionals with the skills to develop, orchestrate, and deploy autonomous AI systems for various enterprise applications.
Course Overview and Key Focus Areas
Beginning September 26, 2026, the program is structured to provide deep insights into critical areas of artificial intelligence. Participants will explore large language models (LLMs), autonomous AI agents, and multi-agent systems. Other core topics include Retrieval-Augmented Generation (RAG), AI Trust, Risk and Security Management (AI TRiSM), workflow design, and production deployment strategies.
The curriculum combines live, faculty-led online sessions, hands-on projects, and an industry-relevant capstone project, ensuring a practical learning experience.
Program Details: Duration, Format, and Fees
- Duration: Six months.
- Format: 100% live online classes, held on Saturdays from 3:30 pm to 6:30 pm IST.
- Fee: ₹1,45,000 plus 18% GST. Installment plans, loan, and EMI facilities are available through the program's service provider.
Eligibility and Application Process
Prospective applicants should hold a graduate or diploma degree and possess at least one year of work experience. A foundational understanding of programming, particularly Python, and familiarity with AI/ML concepts are recommended. There is no specified upper age limit, but selection is subject to IIT Delhi's eligibility and shortlisting process. Meeting minimum criteria does not guarantee admission.
Interested candidates can apply via the CEP IIT Delhi program portal. The application deadline is September 19, 2026.
Comprehensive Module Breakdown
The program is divided into five progressive modules designed to build expertise from foundational concepts to advanced deployment:
- Foundations of Agentic AI & Autonomous Systems: Covers core Agentic AI concepts, autonomy, agent architecture, comparison with GenAI, Model Context Protocol (MCP), and real-world applications.
- LLMs as Reasoning Engines for Agentic Systems: Focuses on reasoning workflows, advanced prompting techniques like ReAct and reflection, planning, task decomposition, and managing failure modes.
- Designing Autonomous Multi-Agent Systems: Explores single vs. multi-agent architectures, role-based agents, task distribution, communication, coordination, and scalability for enterprise.
- Agentic Workflows, Automation & Decision Orchestration: Addresses end-to-end workflows, MCP-based orchestration, APIs, enterprise automation, monitoring, human oversight, and event-driven architectures.
- Real-World Agentic AI Engineering: Includes RAG implementation, long-term memory, deployment across cloud, edge, and hybrid environments, governance, risk management, evaluation, and compliance.
Learning Outcomes and Capstone Project
Upon completion, participants are expected to be proficient in designing autonomous AI systems, building reliable LLM-based reasoning pipelines, creating multi-agent systems, automating enterprise workflows, and deploying secure, scalable, and production-ready Agentic AI solutions.
The program culminates in four module-end projects and a final enterprise capstone, where participants will design, develop, and deploy a complete Agentic AI system.