Generative AI & Agentic AI Engineer Master Program RAG, MCP, LangChain & AI Automation – Live Training Demo

Generative AI & Agentic AI Engineer Master Program RAG, MCP, LangChain & AI Automation – Live Training

(Generative AI, LLMs, Prompt Engineering, AI Agents, Tool Calling, RAG, Embeddings, Vector Databases, MCP, LangChain, Python, n8n, API Integrations, Docker, Git/GitHub, Production Readiness & Deployment.)

 

This Generative AI & Agentic AI Engineer Master Program is designed to help you build, integrate, and deploy production-ready Generative AI and Agentic AI applications from LLM fundamentals to advanced AI engineering implementation. You will learn Generative AI concepts, Agentic AI, LLM architecture, prompt engineering, context engineering, API integration, JSON and structured outputs, tool calling, n8n AI automation, Python for AI engineering, LangChain, AI agents, function calling, Streamlit applications, and agent orchestration. The program also provides hands-on experience with RAG, embeddings, semantic search, chunking, metadata, Supabase vector databases, PDF-based RAG, voice integrations, webhooks, Docker, Pydantic structured outputs, Git, GitHub, and cloud deployment.

The course also covers advanced Agentic AI and enterprise AI engineering, including Model Context Protocol (MCP), MCP tools, resources and prompts, Python MCP servers, LangChain-MCP integration, AI IT Helpdesk automation, human-in-the-loop approval workflows, LangSmith tracing, FastAPI backend development, SQLite-based ticket management, Streamlit interfaces, and Docker-based production packaging. Through hands-on labs, real-world AI automation workflows, RAG projects, MCP implementations, and an end-to-end AI IT Helpdesk capstone project, you will design, build, deploy, troubleshoot, and productionize intelligent AI systems while developing practical skills for Generative AI, Agentic AI, AI Automation, RAG Engineering, LLM Application Development, and AI Engineering roles.

 

About The Instructor:

Shashank Gupta is an experienced Generative AI, Agentic AI, AI Automation, and AI Engineering professional and trainer with extensive industry experience in Generative AI, Large Language Models (LLMs), Agentic AI, Python, LangChain, RAG, MCP, AI agents, API integration, and enterprise AI applications. He brings practical industry expertise in designing, building, integrating, deploying, and managing intelligent AI-powered solutions and automation workflows. He has hands-on expertise across LLMs, Prompt Engineering, Context Engineering, n8n, LangChain, AI Agents, Tool Calling, Function Calling, RAG, Embeddings, Semantic Search, Supabase, Vector Databases, Streamlit, FastAPI, Docker, MCP, Git, GitHub, LangSmith, and AI automation workflows. His training approach focuses on connecting AI concepts with practical engineering implementation, covering key areas such as automation, agent orchestration, RAG, tool integration, structured outputs, deployment, observability, troubleshooting, and production-ready AI application development. With experience delivering 30+ training programmes and mentoring 200+ students, Shashank Gupta delivers practical, hands-on sessions using real-world projects, industry scenarios, AI automation workflows, and project-based learning. His learner-focused approach helps professionals develop industry-ready skills for careers in Generative AI, Agentic AI, AI Engineering, AI Automation, RAG Engineering, LLM Application Development, and AI Solutions Engineering.

Sample Videos:

Live Sessions Price:

For LIVE sessions – Offer price after discount is 200 USD 159 USD 119 USD Or 15000 INR 13000 INR 9900 Rupees.

 

Enroll For Free Demo

OR

WhatsApp

 

Free Demo Session:

16th September @ 9:00 PM – 10:00 PM (IST) (Indian Timings)

16th September@ 11:30 AM – 12:30 PM (EST) (U.S Timings)

16th September @ 4:30 PM – 5:30 PM (BST) (UK Timings)

 

Class Schedule:

For Participants in India: Monday, Wednesday & Friday @ 9:00 PM – 10:00 PM (IST)

For Participants in the US:  Monday, Wednesday & Friday @ 11:30 AM – 12:30 PM (EST)

For Participants in the UK:  Monday, Wednesday & Friday @ 4:30 PM – 5:30 PM (BST)

 

What student’s have to say about Trainer :

⭐ 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. – Rahul 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..– Priya ⭐ The MCP 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.– Michael Anderson ⭐ Joined from the US batch — the timing worked perfectly. The Telegram AI assistant project was the best part. I deployed a fully working AI assistant for my team within a week of completing the course.– Sneha ⭐ From n8n automation to a full FastAPI and LangChain backend — this program is genuinely end-to-end. The capstone I built is something I’m proud to show in interviews. This training changed the direction of my career. – Ayaan Khan

What will I Learn by end of this course?

Explain Generative AI vs Agentic AI, workflows vs agents, and the brain–tools–memory–goal loop.

• Use tokens, context windows, prompt roles, system prompts, zero-shot, few-shot, and ReAct patterns correctly.
• Set up API keys safely, read JSON responses, and traverse response objects without guessing.
• Build n8n workflows with triggers, nodes, credentials, expressions, Telegram, Google services, and memory.
• Write practical Python using variables, lists, dictionaries, loops, functions, files, JSON, packages, and .env.
• Create LangChain prompt templates, chains, parsers, tools, agents, and LangSmith-observable runs.
• Build a Streamlit app that captures input, validates it, calls an agent, and returns a useful response.
• Design a FastAPI backend layer for AI apps with request schemas, response contracts, and clean service boundaries.
• Use advanced LangChain patterns for tool calling, agent orchestration, routing, and multi-agent workflows.
• Implement RAG with chunking, embeddings, metadata, Supabase pgvector retrieval, and grounded generation.
• Process multi-page PDFs containing text, tables, and image-derived content before retrieval and answering.
• Run local n8n with Docker and understand volumes, containers, localhost, and import/export workflows.
• Use Pydantic structured outputs so model responses become validated fields for applications and databases.
• Build MCP tools, resources, and prompts, inspect them, and connect them into agent workflows.

Salient Features:

• 30 Hours of Live Training with real-time project demonstrations
• 1 Year Access to All Recorded Sessions for continuous learning and revision
• Industry-Recognized Course Completion Certificate upon successful completion

Who can enroll in this course?

• Software & Python Developers – Developers who want to build AI agents, integrate LLM APIs, create FastAPI backend services, and develop Python-based AI applications.
• QA & Automation Engineers – QA and automation professionals interested in AI-powered test automation, support triage, structured outputs, tool calling, and intelligent workflows.
• DevOps & Cloud Engineers – DevOps, cloud, and platform engineers looking to work with AI automation, Docker, APIs, observability, and production AI systems.
• AI/ML & Data Professionals – AI, ML, and data professionals seeking hands-on experience with RAG, embeddings, LangChain, agent orchestration, and AI application development.
• Solution Architects & Tech Leads – Architects and technical leaders who want to understand AI agent architecture, MCP, backend integration, retrieval systems, and production AI design.
• Automation & AI Enthusiasts – Professionals interested in workflow automation who want to build practical AI solutions using n8n, APIs, agents, tools, and integrations.
• Fresh Graduates & Beginners – Beginners with basic technical knowledge who want a structured, hands-on learning path covering AI workflows, Python, RAG, agents, and deployment.

 

Course syllabus:

 

 

Enroll For Free Demo

OR

For any other details, Call me or Whatsapp me on +91-9133190573

 

Live Sessions Price:

For LIVE sessions – Offer price after discount is 200 USD 159 USD 119 USD Or 15000 INR 13000 INR 9900 Rupees.

 

FAQ –AI & Machine Learning Engineering Master Program:

1️⃣ What will I learn in this course?

You will learn Generative AI, Agentic AI, LLMs, Prompt Engineering, APIs, n8n, Python, LangChain, RAG, MCP, Docker, Streamlit, FastAPI, and AI application deployment, along with an end-to-end AI IT Helpdesk capstone project.

---

2️⃣ Is this course suitable for beginners?

Yes. The curriculum includes a Python Basics Bridge covering variables, strings, lists, dictionaries, loops, functions, files, JSON, environment variables, and project structure before moving into advanced AI engineering topics.

---

3️⃣ Do I need prior Python knowledge?

No advanced Python knowledge is required. The course includes dedicated Python sessions to build the foundation needed for AI application development.

---

4️⃣ What is Agentic AI, and will I learn how to build AI agents?

Yes. You will learn Agentic AI concepts, workflows, tools, memory, goals, ReAct, agent types, tool calling, and agent orchestration, with practical implementations using n8n and LangChain

---

5️⃣ Will I learn Prompt Engineering?

Yes. You will cover zero-shot and few-shot prompting, ReAct prompting, context engineering, system prompts, and tool calling with practical business examples.

---

6️⃣ Will I learn how to work with LLM APIs?

Yes. The course includes an API Lab covering API keys, OpenAI setup, JSON, model calls, structured outputs, native tool calling, and streaming.

---

7️⃣ What is n8n, and how is it used in this course?

You will use n8n for AI automation and agent development, including Telegram AI agents, memory, workflow automation, RAG workflows, webhooks, and local n8n setup

---

8️⃣ Will I learn LangChain?

Yes. You will learn LangChain chains, agents, tools, function calling, LCEL, prompt templates, structured tool calls, agent orchestration, and LangSmith tracing.

---

9️⃣ Will I build RAG applications?

Yes. The RAG module covers embeddings, semantic search, chunking, metadata, Supabase vector storage, pgvector, document ingestion, retrieval, and grounded question-answering.

---

🔟 Will the course cover PDF-based RAG?

Yes. You will build multi-page PDF RAG applications, including PDF processing, text/table/image handling, chunking, citations, and a Streamlit upload-train-ask workflow.

 

Sample Course Completion Certificate:

Your course completion certificate looks like this……

 

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.