TECHADEMY
Agentic AI Certification from Vishlesan i‑Hub Foundation IIT Patna
Master Agentic AI in 26 weeks. Build real systems. Future-proof your career.
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Applications close on
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Live classes by IIT faculty and top Agentic AI expertsMaster AI agents, RAG and multi-agent systemsCertification from Vishlesan i-Hub Foundation IIT Patna
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EligibilityWorking Professionals and Graduates'%3E%3Cpath stroke='%23FD600E' stroke-linecap='round' stroke-linejoin='round' d='M2.76 11.58a6.75 6.75 0 1 1 12.48-5.16 6.75 6.75 0 0 1-12.48 5.16M9 9 6.75 7.5M9 5.25V9'/%3E%3C/g%3E%3Cdefs%3E%3CclipPath id='a'%3E%3Cpath fill='%23fff' d='M0 0h18v18H0z'/%3E%3C/clipPath%3E%3C/defs%3E%3C/svg%3E){kind=small}
Duration6 Months (26 Weeks)
Learn From TopIIT & Industry Experts'%3E%3Cpath stroke='%23FD600E' stroke-linecap='round' stroke-linejoin='round' d='M15.75 9C10.8 9 9 10.8 9 15.75 9 10.8 7.2 9 2.25 9 7.2 9 9 7.2 9 2.25 9 7.2 10.8 9 15.75 9'/%3E%3C/g%3E%3Cdefs%3E%3CclipPath id='a'%3E%3Cpath fill='%23fff' d='M0 0h18v18H0z'/%3E%3C/clipPath%3E%3C/defs%3E%3C/svg%3E){kind=small}
Labs10+ Hands-on Labs'%3E%3Cpath stroke='%23FD600E' stroke-linecap='round' stroke-linejoin='round' d='M2.25 14.25a6.8 6.8 0 0 1 6.75 0 6.8 6.8 0 0 1 6.75 0M2.25 4.5A6.8 6.8 0 0 1 9 4.5a6.8 6.8 0 0 1 6.75 0m-13.5 0v9.75M9 4.5v9.75m6.75-9.75v9.75'/%3E%3C/g%3E%3Cdefs%3E%3CclipPath id='a'%3E%3Cpath fill='%23fff' d='M0 0h18v18H0z'/%3E%3C/clipPath%3E%3C/defs%3E%3C/svg%3E){kind=small}
Projects & Tools6 Advanced + Major Enterprise Capstone
Join 750k+ learners
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4.8/5 (7,900+ ratings)
Program highlights for Agentic AI Engineering
Personalized learning path
Build production-grade Agentic AI skills for engineers and tech professionals.
Capstone project
Build a complete enterprise Agentic AI system aligned to your domain.
Tools and technologies
Master 20+ tools, including LangChain, CrewAI, LangGraph and MCP.
Master classes
Exclusive master classes from top industry experts.
Top certification
Earn a prestigious certificate from Vishlesan i-Hub Foundation, IIT Patna.
AI agents and automation
Design, build and deploy production-grade AI agents and autonomous systems.
Project portfolio
Create a production-ready AI portfolio for career growth.
Exclusive career advantage
Access to a job portal with curated openings for experienced professionals.
Academic excellence from Vishlesan i-Hub Foundation, IIT Patna
A campus built for excellence
Where innovation begins
Lecture hall, where leaders are shaped
Student sports arena
Labs, future in action
Shaping minds. Creating futuresA Technology Innovation Hub
One of 25 set up across India under the Department of Science and Technology’s National Mission on Interdisciplinary Cyber-Physical Systems.
Speech, video and text analytics
The hub’s research focus, from translation and chatbots to misinformation detection.
Academia, industry and government
The hub brings the three together to advance AI, data science and emerging technologies.
Designed with academic experts
This program’s learning outcomes are set by industry.
Certificate of completion
A structured curriculum that takes you from foundations to real-world Agentic AI
Foundations for Agentic AI Engineering
Build the Python, API, and LLM fundamentals every later module depends on, and start your first working build.
Python & asynchronous engineering for AI services- Development environment & version control
- API & application integration (REST, JSON, auth)
- LLM & transformer fundamentals
- Tokens, embeddings & vector similarity
- Applied project foundations
LLM Engineering & Structured Reasoning
Build an LLM client that handles real-world chaos: outages, streaming, and messy outputs, kept in check with structured prompts and validation.
- Resilient, multi-provider LLM integration
- Streaming & asynchronous response handling
- Prompt engineering & reasoning techniques
- Structured output & schema validation
- Cost & latency benchmarking across providers
- Testing non-deterministic AI systems
Agent Fundamentals & Tool Use
Move from LLM apps to real agents. Pick the right architecture, then build one that reasons, uses tools, and recovers from its own mistakes.
- Agent Evaluation Methodology
- Agent architecture decision frameworks
- Reasoning & acting loops (ReAct)
- Task decomposition & planning patterns
- Structured tool integration
- Tool safety & least-privilege access
- Agent state management & execution tracing
Model Context Protocol & Agent Interoperability
Learn MCP, the emerging standard for connecting agents to tools and data, by building a secure server and client yourself.
- MCP architecture: hosts, clients & servers
- Standardized tool interoperability
- Secure server–client integration
- Capability discovery & transport design
- Wider AI interoperability ecosystem
Knowledge Systems: RAG & Agentic RAG
Build a retrieval system that grounds agents in real data, then make retrieval part of the reasoning loop with agentic RAG.
- Knowledge retrieval & semantic search
- Hybrid retrieval & reranking strategies
- Retrieval & generation quality evaluation
- Agentic RAG: retrieval as a tool call
- Enterprise knowledge-source integration
- Retrieval security & content screening
Frontier AI: Multimodal, Voice & Model Customization
Explore fine-tuning, multimodal, and voice agents, and learn to judge when each one actually earns its place in a system.
- Model customization strategy (prompting vs. RAG vs. fine-tuning)
- Parameter-efficient fine-tuning concepts
- Multimodal & vision-language systems
- Voice agent architecture
- Applied frontier-capability exploration
Multi-Agent Orchestration & Collaborative AI
Coordinate multiple agents at once. Design real workflows, justify your architecture choices, and learn to trace and debug when things break.
- Multi-agent orchestration topologies
- Inter-agent communication & memory scoping
- Trust boundaries & permission design
- Architecture decision frameworks
- Coordination quality & failure analysis
- Orchestration tracing & debugging
Agent Memory, Planning & Reliability
Give agents memory and plans that survive long tasks, then harden them with checkpointing and recovery for when things go wrong.
- Memory architecture (short-, long-term & episodic)
- Context & cost-aware memory design
- Goal decomposition & long-horizon planning
- Self-reflection & trajectory improvement
- Reliability engineering & crash recovery
- Long-horizon stress testing
AI Evaluation, Reliability & Observability
Replace guesswork with real evaluation: golden datasets, LLM-as-judge scoring, and dashboards that set the bar for every system after this one.
- Evaluation suite & golden-dataset design
- Task success & groundedness metrics
- LLM-as-judge & human evaluation design
- Automated regression testing
- Failure analysis & root-causing
- Observability & cost/latency dashboards
AI Security, Guardrails & Responsible AI
Build security in from the start: guardrails, human oversight controls, and a structured red-team pass before anything ships.
- Agentic threat modelling
- Defense-in-depth & runtime guardrails
- Data privacy & PII handling
- Governance, approval gates & escalation design
- Explainability & accountability
- AI regulation & compliance awareness
Production AI, Deployment & LLMOps
Take an agentic service from code to production: containerized deployment, cost-aware routing, CI/CD pipelines, and a rollback drill that proves it holds up under real failure.
- Containerization & service architecture
- Caching, queues & performance tuning
- Model & prompt versioning
- Cost governance & model routing
- CI/CD for AI systems
- Incident response & SLA/SLO tracking
Enterprise Agentic AI Capstone
You'll architect, build, harden, evaluate, and formally defend one enterprise-grade agentic AI system, chosen from real-world tracks and judged from the ground up. This is your final milestone.
- Enterprise problem framing & track selection
- Solution architecture & business case
- Core agentic system development
- Multi-agent & knowledge-system integration
- Security hardening & guardrail integration
- Observability & regression validation
- End-to-end system evaluation
- Production deployment & optimization
- Formal technical defense & presentation
Master 50+ production AI tools and technologies
Build production-ready AI systems for real impact
Resilient LLM API client
Build a production-ready asynchronous LLM API client with streaming, retry logic & fault tolerance using OpenAI, Anthropic, and Gemini SDKs.
Advanced prompt engineering
Develop a secure prompting system with Chain-of-Thought, ReAct, structured JSON outputs, and prompt injection protection.
Production RAG pipeline
Build a complete Retrieval Augmented Generation system with smart chunking, vector databases, semantic search, and ANN retrieval.
Advanced hybrid RAG
Create a production-grade RAG application with hybrid search, neural reranking, RAGAS evaluation, LangSmith tracing and LangFuse monitoring.
Autonomous AI agent
Design an intelligent AI agent with tool integration, memory systems, reasoning loops, and automated failure recovery.
Enterprise Agentic AI (capstone)
Develop a full-scale, production-ready Enterprise Agentic AI solution integrating RAG, multi-agent orchestration, harness engineering, MCP and observability. Choose from 5 specialization tracks.
Learn from top industry experts and IIT faculty
Adarsh Kant Sinha
Adarsh Kant Sinha is an AI Architect, and cybersecurity expert specializing in…
Vinay Kumar
Vinay Kumar is an AI Engineering expert specializing in Agentic AI, AI Agents…
Harish Saragadam
Harish Saragadam is an AI and Analytics leader at Vodafone Idea Limited, with…
2,000+ global companies partnered with Techademy
+2,000 more companiesOur proven track record
A consistent history of learner success that reflects our commitment to excellence.
Learner success rate: 95%
Our learners reported real career impact after completing the program.
Companies that work with Techademy: 2,000+
Organizations worldwide choose Techademy as their talent partner.
Global community rating: 4.8/5
Based on 2,000+ verified reviews worldwide.
Career support for real-world AI roles
Personalized guidance to accelerate your AI career transition.
Build 18+ hands-on projects and a flagship enterprise capstone.
Create a recruiter-ready resume and showcase your AI expertise.
Build a strong professional presence and attract new opportunities.
Earn globally recognized certifications to validate your expertise.
Position yourself for high-growth Agentic AI roles.
How this Agentic AI program stands apart
This programVishlesan i-Hub Foundation, IIT Patna Agentic AI programEnd-to-end production AI pathIIT faculty and senior AI architectsLive classes and hands-on labsEnterprise-grade projectsAgents, RAG, MCP and harness engineeringDedicated to professionalsIIT-backed certificateEMI and flexible payment options
Total fees
Registration fee (non-refundable)
₹2,000Program fee (non-refundable)
₹72,999Two ways to pay the program fee
Upfront
₹72,999
Paid once, all taxes included
EMI
₹6,499/month
12 months All taxes included
Your path to enrollment
Submit your application
Share your details to start your application, and our advisor will reach out to help you.
Confirm your enrollment
Secure your seat by completing enrollment with the payment option that suits you.
Talk to an advisor
Ask your questions and get expert guidance from an experienced advisor.
Begin learning
Get structured courses and continuous live support from the first class.
Frequently asked questions
Our support team can walk you through enrolling.
Call +91 91872 2432201How do I apply for this program?
You can get in touch with our support team to help you enroll in the Agentic AI Engineering Program.
To connect with our support team, call +91 9187224322.
02Am I eligible for this program?
The program is designed for any learners who want to build expertise in Agentic AI Engineering, including AI-powered applications, AI agents, multi-agent systems, RAG architectures, MCP, multimodal AI, and production deployment workflows.
03Is this program beginner-friendly?
Yes. The curriculum starts with a Foundations Track covering Python for AI, statistics, machine learning fundamentals, GenAI concepts, databases, and cloud essentials before progressing to advanced Agentic AI Engineering topics.
04What is the learning mode for the Advanced Agentic AI Engineering Program?
The program combines live lectures, hands-on labs, quizzes, summative assignments, projects, and a capstone project to provide practical experience in building production-grade AI systems.
05How much time do I need to commit to the program?
The program is spread across 26 weeks and requires roughly 8–12 hours of learning per week, including lectures, labs, assignments, projects, and capstone work.
06Will I work on real-world projects?
Yes, of course. Throughout the program, you will build practical systems including LLM applications, RAG pipelines, AI agents, multi-agent workflows, MCP-powered solutions, multimodal AI systems, cloud deployments, and an enterprise-scale capstone project.
07What topics are covered in the program?
The curriculum covers Python for AI & Software Engineering; APIs, LLM SDKs & Prompt Engineering; Structured Outputs & Workflow Design; RAG Engineering & Advanced RAG Systems; AI Agent Engineering & Multi-Agent Systems; Harness Engineering, Reliability & Observability; Model Context Protocol (MCP) & Tool Integration; Multimodal AI Systems; Deployment & Production AI Engineering; and the Enterprise Agentic AI Capstone Project.
08Can I manage this program alongside my job or other commitments?
Yes. The program is structured over 26 weeks with a balanced learning schedule, allowing professionals to build advanced Agentic AI skills while managing their work and other personal commitments.
09What is the duration of the program?
The Advanced Agentic AI Engineering Program is a 26-week (6-month) program: 20 weeks of modules followed by a 6-week capstone, requiring roughly 4-5 hours per week on average.
10What capstone project will I build?
As part of the capstone, you will design, build, deploy, and defend an enterprise-grade Agentic AI solution. Project tracks include Enterprise Copilot Assistants, AI Operations Automation Platforms, AI Knowledge Intelligence Systems, Multi-Agent Enterprise Research Systems, and Financial Intelligence Multi-Agent Systems.
11What are the key outcomes of this program?
By the end of the program, you will be able to build production-ready AI applications, implement RAG systems, engineer autonomous AI agents, orchestrate multi-agent workflows, integrate MCP-based systems, develop multimodal AI solutions, and deploy scalable AI applications in production environments.
12What is the refund policy?
All fees, including the Application Fee, Seat Reservation Fee and Program Fee, are non-refundable.
