Advanced Certificate Programme in AI Agents (Agentic AI)
Indian Institute of Technology Kanpur
Artificial Intelligence & Machine Learning
Application Deadline Approaching
Last date to apply: February 12, 2027 · Program starts on February 13, 2027
About Programme
Learn how to connect AI agents using databases, APIs, enterprise applications, and MCP to automate real-world business processes.
Use prompt engineering as well as organized outputs, function-calling APIs, RAG, and other tools to create real-world AI workflows.
Create RAG-powered AI agents using embeddings, the semantic web, and databases for vector knowledge graphs and memory.
Learn how to apply practical strategies to hallucination management, prompt injection protection, security testing, security measures, privacy, and AI governance.
What you'll learn
Turn LLMs into real-world AI workflows with RAG APIs, tools, and function calling.
Utilize modern AI agent frameworks to design and implement intelligent solutions.
Connect AI agents to tools, enterprise data APIs, databases, and MCP.
Develop multi-agent systems that collaborate to solve complicated business workflows.
Create useful visual or multimodal AI applications.
Create autonomous AI agents to plan and perform complex tasks.
Make use of Agentic AI in real-life problems that affect HR, financial health, sales, and finance.
Monitor, evaluate, and ensure that you are secure and deploy secure AI agents to increase production.
Skills you'll gain
AI Agent Development LLM & Prompt Engineering RAG & AI Memory Agent Orchestration Tool & API Integration AI Agent Evaluation & Observability Agent Security & Governance Enterprise AI Implementation MCP Integration Reasoning & Decision-MakingMultimodal AI Development
Programme Content
Topics Covered
Evolution from Expert Systems → ML → Deep Learning → GenAI → Agentic AI
What makes an AI System "Agentic"
AI Agents vs Chatbots vs Copilots
Agentic AI Market Landscape
Industry Use Cases and Adoption Trends
Future of Autonomous Digital Workers
Practical
Comparing ChatGPT, Claude, Gemini, Perplexity and Agent-based systems
Designing a simple AI Agent workflow
Agent capability mapping exercise
Industry use-case identification workshop
Topics Covered
Agent Architecture Fundamentals
Environment, Perception and Action Loops
Reactive, Deliberative and Hybrid Agents
Knowledge Representation
Planning and Reasoning Systems
Goal-Oriented Agent Design
Practical
Building a rule-based agent
Environment modelling exercise
Agent decision-tree implementation
Agent behavior simulation
Topics Covered
Transformer Architecture
LLM Capabilities and Limitations
Foundation Models for Agents
Prompt Engineering Principles
Structured Outputs and Tool Calling
Fine-Tuning vs RAG vs Agentic Systems
Practical
Prompt engineering labs
Function Calling implementation
Structured JSON output generation
Tool-using LLM demonstrations
Topics Covered
Agent Engineering Principles
ReAct Framework
Planning and Execution Loops
Tool Selection Mechanisms
Workflow Agents vs Autonomous Agents
Agent Design Patterns
Practical
LangGraph
CrewAI
AutoGen
Semantic Kernel
OpenAI Agents SDK
Building a research assistant agent
Topics Covered
Retrieval-Augmented Generation (RAG)
Embeddings and Semantic Search
Knowledge Graphs
Agent Memory Architectures
Episodic, Semantic and Working Memory
Long Context vs Memory Systems
Practical
Building RAG pipelines
Vector database implementation
Pinecone / Weaviate / FAISS
Memory-enabled agent creation
Enterprise knowledge assistant
Topics Covered
Tool-Augmented Agents
API Integration Strategies
Model Context Protocol (MCP)
Agent Communication Standards
Enterprise System Connectivity
AI Agent Infrastructure
Practical
Connecting agents with APIs
MCP server implementation
CRM integration exercise
Database-connected agent
Enterprise workflow automation
Topics Covered
Goal-Oriented Planning
Chain-of-Thought & Reasoning
Reflection and Self-Correction
Tree of Thoughts
Deliberative Planning
Autonomous Task Decomposition
Practical
Building reasoning agents
Multi-step planning exercises
Reflection loops implementation
Autonomous workflow execution
Topics Covered
Multi-Agent Architectures
Agent Communication Protocols
Coordination and Collaboration
Agent Negotiation Models
Hierarchical Agent Systems
Swarm Intelligence Concepts
Practical
Building multi-agent teams
Supervisor-agent architecture
Research team simulation
Customer support multi-agent system
Autonomous business process workflows
Topics Covered
Multimodal AI Fundamentals
Voice Agents and Conversational Systems
Vision-Language Models
Speech-to-Speech AI Systems
Real-Time AI Interaction
Digital Humans and AI Avatars
Practical
Voice assistant development
Image understanding agents
Video analysis agents
Real-time conversational agent
Multimodal workflow implementation
Topics Covered
AI Safety Fundamentals
Hallucination Management
Agent Security Risks
Prompt Injection Attacks
Data Privacy & Compliance
Responsible AI Frameworks
Global AI Regulations
Practical
Red-teaming AI agents
Security testing exercises
Guardrail implementation
Bias assessment workshop
Governance framework design
Topics Covered
Agent Lifecycle Management
AgentOps Fundamentals
Agent Monitoring & Observability
Performance Metrics
Evaluation Frameworks
Enterprise Deployment Strategies
Practical
LangSmith
Phoenix
Weights & Biases
Agent evaluation frameworks
Production deployment
Monitoring dashboards
Topics Covered
Enterprise Agent Transformation Roadmap
Scaling AI Agents Across Organizations
ROI Measurement
Emerging Trends in Agentic AI
AI Workforce of the Future
Self-Improving Agent Systems
Practical
Participants will build and present one of the following:
AI Research Assistant
Customer Service Agent
HR Recruitment Agent
Finance & Reporting Agent
Project Management Agent
Healthcare Assistant Agent
Education & Learning Agent
Enterprise Knowledge Assistant
Sales Copilot Agent
Autonomous Multi-Agent Business System
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