Retrieval Augmented Generation (RAG) Document Loaders (PDF, CSV, JSON, Notion, Web) Text Splitters (RecursiveCharacter, Token-based) Embeddings (OpenAI, HuggingFace, Cohere) Vector Stores (Chroma, FAISS, Pinecone) Conversational RAG (memory + retrieval)

What is an AI Agent? (Definition + Use cases) Tool Calling (functions, APIs, SQL, web scraping) Planning (task breakdown, planner-executor) Memory (Buffer, Summary, Entity, Combined) State Management (session context, chat history) Observability (logging, debugging agents)

LangChain Components PromptTemplate ChatModels Chains (Simple, Sequential, Router) Tools Agents (ReAct, Zero-shot, Plan-and-Execute) Runnables (for modular flow control) AgentExecutor (how LangChain runs agents) Output Parsers + Validators

LangGraph (stateful workflows & agents) Role Assignment (writer, reviewer, planner) Task Planning vs Role Collaboration

PG Certification In Generative AI

Q: Foundation (LLMs + GenAI Basics)

What is Agentic AI? (vs traditional GenAI, vs RAG) LLMs (ChatGPT, Claude, Gemini, open models) Prompt Engineering (static vs dynamic prompts) Output Parsers (Dict, JSON, Markdown, etc.)

This program is a specialized certification designed to combine in-depth knowledge with practical applications of AI system development. This course focuses on equipping learners with the skills to design, build, and deploy intelligent, agent-based AI solutions using Large Language Models, Retrieval-Augmented Generation, and LangChain frameworks, preparing them to become proficient AI professionals in the industry.

Program Key Strengths :

Enquiry form

Program Overview at a Glance

Delivery Type

Online Live Interactive

Learning Hours

40+ Hrs

Program Fee

40,000/- + GST

Starting on

06 December 2025

Batch Days

Weekday (Evening)

Program description

Build Agentic AI Systems: From LLMs to RAG & LangChain Agents

This comprehensive, hands-on course is designed to equip you with end-to-end skills to build next-generation Agentic AI systems powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and LangChain. Whether you’re an AI enthusiast, software engineer, data scientist, or tech entrepreneur, this course will take you from the foundations of LLMs and prompt engineering to building real-world, multi-agent applications that can plan, reason, retrieve, and act autonomously.

You'll explore how Agentic AI differs from traditional chatbots and RAG systems, understand the LangChain ecosystem, and implement powerful use cases like HR assistants, SQL generators, and BPM ticket resolvers. The course also covers backend/frontend integration, deployment using FastAPI + Streamlit, and enterprise-readiness concepts like DPDP compliance, guardrails, and cost control.

Key Features:

End-to-End project-based learning
Latest LLM tools like LangChain, ChromaDB, FAISS, LangGraph
Enterprise-relevant use cases in HR, BPM, SQL, Travel, EdTech
Fully hands-on code demos + deployment with FastAPI & Streamlit
Covers governance, DPDP compliance, cost control
Assignments, quizzes & mock projects for learners

Target Audience

Data Scientists & ML Engineers – looking to go beyond basic chatbots into intelligent agents that can retrieve, plan, and execute tasks.
Backend Developers / Full Stack Engineers – who want to integrate LLMs, APIs, and memory/state into robust AI applications.
Tech Leads & AI Architects – aiming to design scalable, agent-based systems for enterprise or startup use cases.
AI Enthusiasts & Students – with Python knowledge, who want to explore the world of LLMs, prompt engineering, and AI agents.
Corporate Trainers / EdTech Professionals – who want to implement GenAI-driven education or productivity tools.

Your Road to Mastery Starts Now

What You Will Learn

Foundation (LLMs + GenAI Basics)

RAG Concepts

Retrieval Augmented Generation (RAG)
Document Loaders (PDF, CSV, JSON, Notion, Web)
Text Splitters (RecursiveCharacter, Token-based)
Embeddings (OpenAI, HuggingFace, Cohere)
Vector Stores (Chroma, FAISS, Pinecone)
Conversational RAG (memory + retrieval)

Agent Core Concepts

What is an AI Agent? (Definition + Use cases)
Tool Calling (functions, APIs, SQL, web scraping)
Planning (task breakdown, planner-executor)
Memory (Buffer, Summary, Entity, Combined)
State Management (session context, chat history)
Observability (logging, debugging agents)

LangChain Toolkit

LangChain Components
PromptTemplate
ChatModels
Chains (Simple, Sequential, Router)
Tools
Agents (ReAct, Zero-shot, Plan-and-Execute)
Runnables (for modular flow control)
AgentExecutor (how LangChain runs agents)
Output Parsers + Validators

Multi-Agent Systems

Deployment & API Integration

Governance & Enterprise-Readiness

DPDP Act compliance (for India-based users)
Guardrails & Safety (output filtering, prompt injection protection)
Rate limiting, retry logic
Human-in-the-loop supervision (where needed)
Cost & token management (LLM billing control)

Projects & Real-World Use Cases

Personal Assistant Agent (email, notes, reminders)
HR Agent (fetch policy, send email, answer HRQ)
BPM Ticket Resolver Agent (SQL + RAG + steps)
Travel Planner Agent (flight + hotel + route planner)
Resume Screener + Feedback Generator
Meeting Minutes Generator with PDF summary
SQL Query Generator from plain English

Your Future in Data Starts Here – Click to Transform!

Note* : Certain Modules will be delivered in Self-Paced Video mode and Confirmation for the same will be communicated in your admission letter .

Tools You Will Learn

Essential Tools You Will Gain Proficiency In

Learn What Employers Want – Generative AI = Your New Edge!

Note* : Few tools will be in self-paced video mode

Capstone Projects

Industry Collaboration Projects

Amazon Fashion Discovery Engine Learn to build a recommendation engine which suggests similar apparel products to a given apparel product on any e-commerce websites such as Amazon.

Ecommerce Domain : Ecommerce

Tag predictions for questions Learn to develop a high-performance automated tagging system to aid topic discovery in Stack Overflow, a popular online community to learn and share knowledge.

Web analytics Domain : Web analytics

Cancer Prediction Learn to model the progression and treatment of cancerous conditions using patients medical records using supervised Machine learning Algorithms

Life Sciences and Health care Domain : Life Sciences and Health care

HR Analytics Employee Attrition & Performance. Uncover the factors that lead to employee attrition and explore important questions such as ‘show me a breakdown of distance from home by job role and attrition’ or ‘compare average monthly income by education and attrition’

HR Analytics Domain : HR Analytics

Machine Learning for Dynamic Pricing Machine Learning enhances dynamic pricing by continuously learning from data to identify patterns, detect changing demands, and adapt to market trendsultimately helping improve your KPIs.

Ecommerce Domain : Ecommerce

Sales conversion optimization. Social Media Ad Campaign marketing is a leading source of Sales Conversion and in this project learners will have to work on the optimization of the sales conversions

Campaign management Domain : Campaign management

Claim Prediction . The insurance companies are extremely interested in the prediction of the future. Accurate prediction gives a chance to reduce financial loss for the company. The insurers use rather complex methodologies for this purpose

Banking and Financials Domain : Banking and Financials

Course Certificate

Recognized Certificate of Achievement

Upon successful completion of the program, participants will receive a Recognized Certificate of Achievement, serving as official validation of their dedication, knowledge, and skills acquired throughout the course. This certificate can be proudly showcased to employers, institutions, or peers as a testament to their accomplishment.

Fuel Your Career with Data Power!

Learning Path

Limited-Time Bonus

Note* : In the Learning Path, the stages of the tools may be reshuffled, and some of the tools are in self-paced video mode.

Potential Recruiters

Industries Potential Recruiter’s

Outcomes

What You'll Build By End of Program

Design and build your own Agentic AI systems
Use LangChain to integrate tools, memory, agents, APIs, and RAG
Deploy end-to-end GenAI apps with frontend/backend integration
Build enterprise-grade assistants that retrieve, plan, and act
Implement multi-agent workflows using LangGraph
Ensure AI safety, governance, and cost-efficiency

Success stories

Stories of Excellence

Testimonials

Experience Of Our Alumni

Geetika Puri Associate Consultant (Senior Data Analysts) at Capgemini

â€œI rarely come across real talents who stand out like Rahul. I had the pleasure of working with Rahul on Machine Learning algorithm specifically.

Don Nachtwey Data Warehouse Analyst at GDIT ( Washington)

Rahul was my course instructor for Tableau. I am pleased to gain knowledge and skills in such a powerful and flexible tool.

Mayur Korde

It was a very nice and quality experience to learn data science with The Scholar . The course is well designed and our trainer was experienced and good at presenting the concept clearly by presenting the real time examples.

Sanjay Yadav IT Analyst at TCS

I personally recommend data scientists or BI enthusiast to for this course. Rahul is very good at explaining each and every topic with so ease that learning becomes fun

Dinkar Ji Consultant

Rahul was my instructor for data science learning using python. His command over the subject is outstanding and he makes sure he is able to impart his knowledge.

SB Subhaprakash Entrepreneur In Residence - Wakefit Gift Cards | IIM Rohtak

I have attended Rahul's Tableau and Python sessions. I have to say, those sessions were real gem. Rahul's sessions were full of interactions and insightful.

Mahima K.

Rahul has played a major role in my journey of learning data science. His approach towards teaching makes it very conducive for the students to quickly understand the complex concepts.

Jagjit Hanspal Sr BI/ETL Consultant at Intact

Rahul was my Mentor for Tableau Certification Training. He has in depth knowledge in Tableau and is a brilliant teacher. I appreciate his help.

Rakshit Pophali

I started my data science journey with the guidance of The Scholar. The mentors from The Scholar taught me tableau, python and data science.

Shimelis Kitancho

The Scholar is a Data Science Experts : They are an excellent teacher, guide, expert, or master in the field.