Master Agentic AI & Build
Autonomous AI Systems – Live Training
(no-code with n8n, then under the hood with Python, LangChain, RAG & MCP)
Step into the future of software development with our Agentic AI Engineering Program. This hands-on training is designed to help professionals build intelligent AI agents, automate complex workflows, and develop real-world AI-powered applications using the latest Agentic AI frameworks and technologies. You’ll learn Python, Prompt Engineering, LLM Foundations, RAG (Retrieval-Augmented Generation), Vector Databases, Multi-Agent Systems, MCP Integration, and AI-powered development practices. The course provides practical experience with modern AI ecosystems including GPT, Claude, Gemini, LangChain, LangGraph, CrewAI, and AutoGen.
Through industry-focused projects, participants will learn how to design, build, deploy, and manage AI agents capable of reasoning, planning, memory management, tool usage, and autonomous decision-making. The program covers AI agent architectures, agent workflows, context management, knowledge retrieval, API integrations, and production deployment strategies to prepare learners for next-generation AI engineering roles.
Whether you are a Software Developer, QA Engineer, SDET, Automation Tester, DevOps Engineer, Cloud Professional, Business Analyst, or AI enthusiast, this course provides the skills needed to create enterprise-grade AI assistants, AI copilots, automation agents, and multi-agent applications that solve real business problems.
About the Instructor:
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Shashank Gupta Engineer. Innovator. Builder of AI-powered Quality Engineering Workflows. With over a decade of experience across QA, automation, and engineering strategy, Shashank has transformed quality from a mere “checkpoint” into a genuine competitive advantage. As an Engineering leader at a Fortune 500 financial services / IT company, he specialises in reimagining QA with AI, ML Ops, process automation, and intelligent test design — enabling teams to ship faster, smarter, and with confidence. Having delivered 30+ training programmes and personally mentored 200+ students — including QA engineers, developers, and tech leads across the industry — Shashank brings a rare blend of corporate depth and teaching clarity. His learners have gone on to build and deploy real AI-powered systems inside their organisations. His hands-on, problem-first approach means every session connects directly to things you’ll actually build at work. |
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 259 109 USD Or USD13000 INR 12900 INR 8900 Rupees
OR
Free Demo Session:
Indian Timings: 29th June @ 9 PM – 10 PM (IST)/
U.S Timings: 29th June @ 11:30 AM – 12:30 PM (EST)/
U.K Timings: 29th June @ 4:30 PM – 5:30 PM (BST)
Class Schedule:
For Participants in India: Monday to Friday @ 9 PM – 10 PM (IST)
For Participants in the US: Monday to Friday @ 11:30 AM – 12:30 PM (EST)
For Participants in the UK: Monday to Friday @ 4:30 PM – 5:30 PM (BST)
What Students Say about Shashank Gupta:
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👨 Arjun Mehta :The n8n module blew my mind — I built a fully automated lead nurturing workflow in day 3 without writing a single line of code. Then moving to Python and LangChain felt like a natural progression. Best AI course I’ve taken. 👩 Priya Sharma :I joined as a manual QA tester with zero AI background. The RAG module and vector DB section opened my eyes to what’s possible. The capstone project I built is now part of my portfolio and has helped me land a new role. 👨 Venkat Reddy :The MCP Protocol and multi-agent systems section was something I hadn’t found in any other course. The trainer clearly knows the industry — every module had real-world examples directly applicable to enterprise projects. 👩 Ananya Singh :Joined from the US batch — the timing worked perfectly. The Telegram RAG Assistant capstone was the best part. I deployed a fully working AI assistant for my team within a week of completing the course. 👨 Rohit Kulkarni :I’ve done 4 AI courses before this. None of them covered LangGraph or multi-agent orchestration with real code. This program actually builds your confidence — not just theory. The live Q&A sessions were incredibly valuable. |
Salient Features:
- 35 Hours of Live Training along with recorded videos
- 1 Year Access to Videos
- Course Completion Certificate
Who can enroll for this course?
- Software Engineers
- DevOps Engineers
- Platform Engineers
- Automation Engineers
- Data Professionals
- Cloud Engineers
- QA Engineers
- Technical Leads
- Solution Architects
- Business Analysts
- AI Enthusiasts
- Fresh Graduates
- Working Professionals Seeking AI Skills
What will I learn by the end of this course?
- Understanding Agentic AI & Autonomous Agents
- Prompt Engineering for AI Agents
- Building AI Workflows Using n8n
- Creating Intelligent AI Assistants
- Automating Business Processes with AI
- Working with OpenAI & Gemini APIs
- Building RAG (Retrieval-Augmented Generation) Applications
- Creating Knowledge-Based AI Chatbots
- Developing Telegram AI Assistants
- Agent Memory & Context Management
- Learning Python for AI Development
- Building AI Agents from Scratch
- Function Calling & Tool Integration
- Working with the LangChain Framework
- Building Multi-Agent Systems
- Understanding Model Context Protocol (MCP)
- Implementing AI Security & Guardrails
- Designing Production-Ready AI Solutions
- Real-World Business Automation Projects
- Building Portfolio-Ready Capstone Projects
- Deploying & Demonstrating AI Applications
- Best Practices for Enterprise AI Implementations
Course Syllabus:
Module 1: Foundations of Agentic AI (Sessions 1–4 • 4 hrs)
Session 1: What is Agentic AI?
- Generative vs. Agentic AI
- Workflow vs. AI agent
- The ReAct framework
- Types of agents
- Agentic architecture
- Live demos of real agents
Session 2: How LLMs Actually Work
- Tokens
- Context windows
- Hallucinations — intuition, no math
- What a prompt really is: composition of a formal prompt
Session 3: Prompt Engineering for Agents
- Zero-shot
- Few-shot
- Chain-of-thought
- ReAct prompting
- Context engineering
- System prompts
Session 4: APIs & Workspace Setup
- What an API key is
- Getting your OpenAI/Gemini key
- Setting up your n8n workspace
- No code fear
✓ Checkpoint: Short quiz on foundations.
Module 2: Building Agents Without Code: n8n (Sessions 5–14 • 10 hrs)
Session 5: n8n Fundamentals
- Structure of an n8n workflow
- n8n vs. Zapier vs. Make
- Your first data pipeline: form to CRM
Session 6: Automation Pipelines
- Automating lead generation
- Google Form to CRM
- Triggers, nodes, and data flow
Session 7: Routing & Branching Logic
- Automated social media pipeline with advanced routing and branching
Session 8: AI Support Triage Agent
- Your first AI agent
- LLM + prompts + tools
- Incoming emails classified, routed, and logged to a database
Session 9: Invoice Data Extraction Agent
- Structured outputs
- Forcing strict JSON schemas so AI returns clean, reliable data
Session 10: Agent Tools & Memory
- A recommendations agent with tools, memory, and real-world architecture
- Why agents forget
Session 11: RAG — The Concept
- Knowledge bases
- Vector embeddings
- Chunking
- Semantic search — explained visually
Session 12: RAG — The Build
- Your first RAG workflow
- From knowledge base to conversational AI
Session 13: Telegram RAG Assistant
- A conversational Telegram bot with advanced retrieval
- A real AI assistant on your phone
Session 14: Mini-Project #1
- Your Personal AI Representative
- A RAG agent over YOUR own resume or business docs
- Shared as a working link
✓ Checkpoint: Short quiz, plus every participant shares their working agent in the cohort group.
Module 3: Just Enough Python (Sessions 15–20 • 6 hrs)
Session 15: Python Basics I
- Variables
- Strings
- Lists
- Dictionaries
Session 16: Python Basics II
- Functions
- Loops
- Working with JSON
Session 17: Your First LLM Call in Code
- Calling the LLM API directly from Python
- The same brain n8n used, now under the hood
Session 18: Function Calling Demystified
- How LLMs really use tools
- Manual JSON tool schemas
- The function-calling mechanism
Session 19: Build an Agent From Scratch I
- The ReAct agent loop with the raw API
- No framework
- Full understanding
Session 20: Build an Agent From Scratch II
- The ReAct prompt
- Building an AI agent even without function calling
- The “aha” moment of the course
✓ Checkpoint: Short quiz on Python and tool calling. Everything runs in Google Colab — no local Python installation.
Module 4: Agent Engineering with LangChain (Sessions 21–24 • 4 hrs)
Session 21: LangChain Essentials
- Prompt templates
- Chat models
- Chains
- Build a text-summarizer chain
- Debugging and tracing
Session 22: LangChain Agents
- Your first LangChain agent with tools and LLMs
- Real-world web search with Tavily
- Structured outputs with Pydantic
Session 23: RAG with LangChain
- Document loaders
- Text splitters
- Embeddings
- A vector database
- A complete RAG pipeline in code
- Mini-Project #2 begins
Session 24: MCP — Model Context Protocol
- Why MCP exists
- MCP architecture and servers
- Using a pre-built MCP server with AI clients
- Mini-Project #2 due & shared
Module 5: Multi-Agent Systems & Production Reality (Sessions 25–28 • 4 hrs)
Session 25: Multi-Agent Systems
- A multi-agent marketing team
- Supervisor & worker architecture
- Sequential agents and context handoff
Session 26: Error Handling & Self-Healing Pipelines
- Centralized error handling in n8n
- Building workflows that recover from failure
- Production-grade reliability
Session 27: Agent Security & Safe AI
- LLM application security
- Common vulnerabilities
- Guardrails and human-in-the-loop checkpoints
Session 28: LLM Apps in Production & Capstone Prep
- Privacy and data retention
- Production architecture insights
- Mapping agent patterns to your capstone
Module 6: Capstone Project (Sessions 29–35 • 7 hrs)
Session 29: Capstone Kickoff
- Choose your track and project
- Scoping & success criteria
- 4–6 hours of build time over two weeks
Sessions 30–33: Guided Build Sessions
- Hands-on building with live instructor support
Session 34: Polish & Rehearse
- Debugging clinic
- Demo preparation
Session 35: Demo Day 🎉
- Capstone presentations
- Working links shared
- Certificates
- Next steps
How can I enroll for this course?
OR
For any other details, Call me or Whatsapp me on +91-9133190573
Live Sessions Price:
For LIVE sessions – Offer price after discount is 300 USD 259 109 USD Or USD13000 INR 12900 INR 8900 Rupees
Sample Course Completion Certificate:
Your course completion certificate looks like this….
Important Note:
To maintain the quality of our training and ensure a smooth learning experience for all participants, we do not allow batch repetition or switching between courses.
To reiterate, moving from one course to another or shifting from one trainer to another (even if it is the same course) is not possible. Changing batches or trainers in any form is strictly not permitted.
We request all learners to attend the scheduled sessions regularly and make the most of their learning journey. Thank you for your understanding and continued support.