Are there any additional costs beyond the program fee?

While the curriculum mainly uses free and open source tools, it also includes showcases of a few paid tools that the learners can choose to pay for further exploration and their own use. All the concepts will be taught and demonstrated without the explicit need for any additional payment.

Agentic AI Certificate Course - Vishlesan I-Hub, TIH of IIT Patna

Program Duration
10 weeks (6-8hrs / Week)
Learning Format
Live, Online, Interactive

Why Join this Program

Earn Recognized Credential
Certificate of completion from Vishlesan I-Hub, TIH of IIT Patna

Certificate of completion from Vishlesan I-Hub, TIH of IIT Patna
Master the Agentic AI Stack
Progress from LLMs to RAG, MCP, multi-agent orchestration, product engineering, and deployment
Engineer AI-Native Products
Design multi-agent products with orchestration frameworks, MCP, tool integration and UX principles
Stay current with latest tools
Build with LangGraph, CrewAI, GitHub Copilot, Azure AI, Docker, n8n, and more.

Corporate Training

Enroll your employees into this program, NOW!

Talk to Our Advisor

Program Overview

Go beyond AI tools and learn to design, build, and deploy real-world AI solutions. This 10-week, hands-on program takes you from AI fundamentals to Agentic AI, Multi-Agent Systems, workflow automation, and AI product development—equipping you with the practical skills to build intelligent AI applications for modern businesses.

Key Features

Master the modern AI application stack—from Agentic AI, AI copilots, RAG, MCP, planning systems, multi-agent orchestration, workflow automation, AI UX, product strategy, GTM, ROI evaluation, LLMOps, observability, and production deployment.
Get hands-on with 29+ AI tools and frameworks, including LangChain, LangGraph, CrewAI, AutoGen, n8n, OpenClaw, Microsoft Copilot, Azure AI Foundry, GitHub Copilot, Hugging Face, LangSmith, Docker, Ollama, Figma, and more.
Turn concepts into production-ready skills with 40+ demos, 10+ guided exercises, and 10+ multi domain industry projects spanning ecommerce, analytics, marketing, finance, technology and more.
Transition into AI Product & Engineering Roles by developing AI product thinking, software engineering mastery, and production deployment expertise
Accelerate your learning with a beginner-friendly introduction to Python and AI development workflows before building intelligent AI systems.
Earn Microsoft Learn badges on the Microsoft Learn portal for Microsoft-branded courses
Graduate with an industry-recognized Professional Certificate from Vishlesan I-Hub, TIH of IIT Patna that strengthens your AI credentials.
Gain practical insights into designing and deploying enterprise-grade agentic AI systems with Microsoft Copilot Studio and AutoGen through an exclusive live masterclass.
Learn AI beyond coding through one of the market's most modern, hands-on curriculum—combining AI engineering, product strategy, real-world projects, and production-ready implementation.
With AI Impact Studio, stay ahead of AI, not just up to date. With an exclusive series of live workshops designed to keep you updated of every major AI trend, learn of new models, tools, and industry practices. You'll be part of hands-on sessions with experts—ensuring your learning extends well beyond the core curriculum.

Post Graduate Program Advantage

Develop the skills to build multi-agent AI systems, build RAG-driven workflows, and integrate tools using MCP. Gain hands-on experience designing AI systems that support automation, product development, and enterprise use cases.

Program Certificate
Earn a Program Completion Certificate
- Certificate of completion from Vishlesan I-Hub, TIH of IIT Patna
- Individual course completion certificates from Simplilearn
- Industry-recognized credential in Agentic AI and multi-agent systems
Industry Certificate
Partnership With Microsoft
- Microsoft Learn badges on the MS Learn portal for Microsoft courses
- Learn to build AI agents using Azure AI services and frameworks

Program Details

This program provides a structured learning journey across AI foundations, generative AI, LLMs, and multi-agent systems. Build hands-on experience designing agent workflows, planning systems, and AI solutions that support product innovation and enterprise use cases.

Learning Path

Getting Started with your Agentic AI Journey
Begin with an overview of the program structure, curriculum roadmap, and expected learning outcomes. The session introduces the key concepts covered throughout the program and explains the evolution of AI, generative AI, and agentic AI. You will also explore how AI systems influence modern products, industries, and business workflows.
Python Refresher with AI (Optional)
- Python programming essentials for AI and machine learning applications
- Environment setup across IDEs and cloud platforms
- Data structures, control flow, and object-oriented programming basics
- File handling and coding workflows for data tasks
- AI-powered code generation using GitHub Copilot
- Hands-on exercises comparing traditional and AI-assisted coding approaches
Foundations of AI & Agentic AI
- Learn, Build, Deploy framework for AI systems
- AI hierarchy, including AI, ML, DL, GenAI, and Agentic AI
- Transformer architectures and autonomous AI agents
- Key research such as Attention Is All You Need
- Prompting techniques, including Chain-of-Thought and ReAct
- Four-layer generative AI stack model
Generative AI Tech Stack and Prompt Engineering
- Four-layer GenAI stack: Infrastructure, Model, Orchestration, Application
- Cloud platforms and vector databases supporting GenAI systems
- Foundation models and model tuning approaches
- Agent frameworks and workflow orchestration
- Prompt engineering techniques, including zero-shot, CoT, and ReAct
- Hands-on demos for prompt design and experimentation
LLM Internals & Planning Systems
- Planning systems for AI-assisted workflows
- Prompt engineering principles for LLM interaction
- Building Q&A bots using LangChain and function-calling APIs
- Integration of external APIs and services in AI workflows
- Agent-driven planning workflows
- Development of multi-step agents with contextual tool integration
Multi-Agent Ecosystems (I)
- RAG systems and multi-agent architectures using CrewAI and LangGraph
- Agent collaboration patterns and role-based architectures
- YAML-based agent role design
- Memory strategies for multi-agent systems
- Orchestration frameworks for agent collaboration
- Modular agent teams for scalable information synthesis
Multi-Agent Ecosystems (II)
- Enterprise agent orchestration using AutoGen and n8n automation
- Communication protocols within multi-agent ecosystems
- Database integration within agent workflows
- Marketing agent pipeline projects
- Scalability, performance, security, and compliance considerations
- Visual workflow design and distributed agent system concepts
Model Context & Tooling Protocol
- Model Context Protocol (MCP) for AI tool integration
- Structured context binding and interoperability standards
- JSON schema design for tool communication
- Secure tool hosting and authentication methods
- Chaining tools and agents across workflows
- Memory persistence and enterprise security considerations
Metrics, GTM & ROI
- AI agent performance evaluation using OKRs and key indicators
- Metrics such as success rate and latency
- Observability tools, including LangSmith and Phoenix
- Logging and conversational analysis techniques
- Pricing strategy and go-to-market planning
- Deployment of agent MVPs with analytics dashboards
Agentic UX Design & Transparency
- UX design patterns for agentic AI systems
- Interaction design for probabilistic workflows
- Handling ambiguity in AI interactions
- Human-in-the-loop checkpoints
- Managing hallucination and bias risks
- Transparency through confidence signals and explainability
Dev Tools & Product Readiness
- Cloud vs edge hosting strategies
- Serverless and containerized environments
- Model hosting approaches
- Automation workflows using Firebase and n8n
- Feedback systems and testing frameworks
- Infrastructure-as-code tools, including Terraform and Pulumi
Develop AI Agents on Azure (Microsoft)
- Azure infrastructure for AI agent development
- Azure frameworks and orchestration workflows
- Deployment pipelines for AI applications
- Security integration and compliance considerations
- Hosting AI agents in the Azure ecosystem
- Scalable orchestration within cloud environments
Capstone - Product Strategy Simulation
Apply multi-agent design and product strategy in a comprehensive capstone. Participants build a four-agent market research and GTM system using n8n and CrewAI with MCP integration. The project includes Lean Canvas planning, pricing strategy, performance tracking, and chatbot deployment.

Electives:

Develop Generative AI Apps in Azure (Microsoft)
Create generative AI applications using Azure AI tools and Microsoft Foundry. Learners configure environments, deploy catalog models, build apps with the Foundry SDK, design prompt flows, implement RAG systems, fine-tune models, apply responsible AI principles, and evaluate performance in Azure AI Studio.
Masterclass on Agentic AI Solutions Using Copilot Studio and AutoGen
This live masterclass demonstrates how to design and deploy agentic AI systems using Copilot Studio and AutoGen. Led by industry experts, it highlights low-code and open frameworks that support efficient development and real-world implementation of intelligent automation solutions.
AI Impact Studio - Live workshops on AI trends, tools & breakthroughs
- Stay future-ready as AI evolves, with continuous learning beyond your core curriculum
- Build real AI systems with Claude, Claude Code, and agentic frameworks in the Builder Track
- Drive business outcomes — apply AI to decisions, productivity, and growth in the Business Track, no coding needed
- Learn directly from experts and practitioners solving real industry problems
- Turn knowledge into career capital — stronger projects, applied skills, better workplace impact

Programme Syllabus

15+ Skills Covered

MultiAgent Systems
Prompt Engineering
Context Engineering
RetrievalAugmented Generation
Model Context Protocol
Agent Orchestration
Workflow Automation
LLM Application Development
AI Product Strategy
Tool Integration
Vector Databases
Semantic Search
AI Deployment
AI Evaluation amp Monitoring
AI Solution Prototyping

29+ Tools Covered

Projects Covered

Project 1
Customer Order Insights With Python
Analyze order datasets using Python data structures to categorize products, identify buying patterns, and generate insights that support informed business decisions.
Project 2
Python Text Adventure Game With GitHub Copilot
Create a Python text adventure game using GitHub Copilot while applying variables, lists, loops, conditionals, and functions to build an interactive gameplay experience.
Project 3
RAG Pipeline With PDF Chunking and Retrieval
Build a retrieval-augmented generation pipeline by splitting PDF documents into chunks, generating embeddings, and using semantic vector search to retrieve relevant information.
Project 4
Agentic RAG Router With PDF and Web Search
Develop an agentic RAG system where router and retriever agents direct queries to either PDF vector search or web tools to generate responses grounded in reliable sources.
Project 5
LinkedIn Content Automation Workflow Using n8n
Design an automated LinkedIn content workflow using n8n and an AutoGen-style microservice to ideate, draft, review, and publish posts with structured guardrails.
Project 6
Agentic UX Trust Prototype for Financial Advisors
Create an agentic UX prototype for a financial advisor AI that previews actions, explains the reasoning behind decisions, and allows users to override or cancel them.
Project 7
MultiAgent Workflow Planner for Startup Teams
Build a workflow planner in which role-based agents collaborate to complete tasks, such as generating a structured pitch deck outline for startup accelerator programs.
Project 8
MultiAgent GTM and Market Research System
Build a multi-agent market research and GTM planning system using n8n and CrewAI with MCP integration, combining strategy planning, performance analytics, and chatbot deployment.
Project 9
Financial Auditor Agent
Building an Agentic RAG Pipeline For Org Financial Report Analysis. Statement auditor reviews financial statements for consistency, completeness, and audit-readiness

Disclaimer - The projects have been built leveraging real publicly available datasets from organizations.

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An Immersive Learning Experience

Peer to Peer engagement

Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.

Flexi Learn

Missed a class? Access recordings to always maintain learning progress and keep up with your cohort.

Mentoring session(s)

Expert guidance sessions from mentors for doubt clarifications, project assistance, and learning support.

Learning Support

Get a dedicated Cohort Manager for all your queries and help you succeed at every learning step.

Peer to Peer engagement

Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.

Flexi Learn

Mentoring session(s)

Learning Support

Program Trainers

Vinit Singh
15+ years of experience
AI consultant- Sony India
Unus Ebrahim
20+ years of experience
GenAI, Agentic AI & AWS Trainer
Abhinav Tonk
16+ years of experience
Dir–Morgan Stanley, LangChain expert

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Industry Trends

Organizations are moving from prompt-based tools to the next stage of AI systems that can plan tasks, coordinate agents, and execute workflows. Investment in AI and automation is increasing the demand for professionals who can design and manage these systems.

40%

of enterprise apps will have task-specific AI agents by end of 2026

Source: Gartner

23%

of organizations are already scaling agentic AI systems

Source: McKinsey

72%

of employees report that AI has changed the skills required in their role

Source: Business Insider

Companies Hiring

Batch Profile

This program caters to working professionals from a variety of industries and backgrounds; the diversity of our students adds richness to class discussions and interactions.

Industry
The class consists of learners from excellent organizations and diverse industries
Industry
Software Product - 34%Information Technology - 26%Healthcare & Pharma - 11%Banking & Finance - 9%Manufacturing - 5%Others - 15%
Companies

Learner Reviews

Admission Details

Application Process

The application process consists of three simple steps.

STEP 1

Submit Application

Complete the application by providing the essential details about yourself

STEP 2

Reserve Your Seat

Secure your seat by completing the program fee payment

STEP 3

Start Learning

Begin your learning journey on the designated cohort start date

Eligibility Criteria

For admission to this Agentic AI & Multi-Agent Systems, candidates should:

Formal work experience is preferred but not mandatory.

Program participants should be atleast 18 years old

Basic knowledge of programming concepts (preferred but not mandatory)

Apply Now

Program Benefits

Certificate from Vishlesan I-Hub, TIH of IIT Patna
Hands-on learning with 10 projects and a capstone
40+ demos, 10+ guided practices and 29+ tools and frameworks
From AI Fundamentals to Production-Ready AI
Copilot and AutoGen led exclusive masterclass on agentic AI

Agentic AI Certificate Course FAQs

Are there any additional costs beyond the program fee?
While the curriculum mainly uses free and open source tools, it also includes showcases of a few paid tools that the learners can choose to pay for further exploration and their own use. All the concepts will be taught and demonstrated without the explicit need for any additional payment.