Included with the couse

1. Complimentary eBook
Python from Scratch – A Practical Guide for AI Beginners
A structured refresher designed to help learners align Python skills with GenAI system development.

2. Comprehensive Course Material
Well-structured learning resources for every module, including explanations, architecture notes, and fully working code used during the sessions.

3. Alumni Status on Completion
Upon successful course completion, participants become part of the AI Mentorship Hub alumni network.

4. Free Course Upgrades
Any enhancements or updates made to this course in future batches will be available at no additional cost to alumni.

5. Ongoing Industry Updates & Job Opportunities
Alumni receive continuous updates on industry trends, emerging GenAI roles, and relevant job opportunities shared through the community.

6. Alumni Privileges & Discounts
Eligible alumni discounts on future courses and advanced programs, as applicable.

Future of GenAI Engineering

Explosive Demand for GenAI & AI Engineering Roles

GenAI skills are now core requirements across tech, analytics, and product teams. Companies are hiring professionals who can build and control LLM-powered systems, not just use AI tools.

GenAI Is Becoming Core to Every Business Function

LLMs, RAG pipelines, and AI agents are moving from experiments to production systems. Organizations are embedding GenAI directly into analytics, operations, and decision-making workflows.

High-Impact Career Path for System-Level AI Builders

Professionals who understand end-to-end GenAI systems — prompts, retrieval, control layers, and agents — are trusted with higher-impact roles across startups and enterprises in India.

"The future belongs to those who engineer AI systems, not just interact with them"

Who This Course Is For

• Data analysts & BI professionals moving into AI

• Software engineers building GenAI features

• Tech leads, architects, startup builders

• Serious professionals transitioning into AI engineering

What You Will Build

• Prompt-Controlled Analytics Assistant: Create AI outputs that are structured, consistent, and usable — not random text

• Data-Grounded AI Analyst (RAG System): Build an AI system that answers only from your data, not imagination.

• Decision-Making AI Agent: Design an agent that decides what action to take next using tools and logic

• Capstone: Analyst Agent

         Create an AI Analytics Agent that:

• Reads CSV business data

• Performs analysis using tools

• Generates factual insights and reports

• Takes analytical decisions on your behalf

Course Journey

   LLM Foundations
→ Prompt Engineering
→ GenAI Features
→ RAG Systems
→ AI Agents
→ Analyst Agent (Capstone)
→ LangChain Mapping

Why GenAI and LLM Engineering With Us

Build your GenAI engineering career the right way — by designing real AI systems, not just learning tools. This program focuses on hands-on system building, practical GenAI applications, and a learning experience that mirrors how AI solutions are actually developed and deployed in industry.

Real-World Projects

Expert Mentorship

Personalized Learning

Learn directly from data leaders with decades of real business and technical experience.

Small batches, focused guidance, and a completion certificate that boosts your career.

Apply every concept to live, industry-based projects and build a job-ready analytics portfolio

Frequently asked questions

Is this a beginner-level course?

No. This course is designed for professionals who already have basic technical exposure. You should be comfortable with Python fundamentals and working with data. This is a system-building course, not an introduction to programming.

Is this course only about prompt engineering?

No. Prompt engineering is just one part. The course focuses on end-to-end GenAI systems, including RAG pipelines, control layers, and AI agents that analyze data and make decisions.

Will we use frameworks like LangChain?

The core of the course is framework-agnostic. You will first learn how GenAI systems work at a fundamental level. A bonus module maps these concepts to LangChain, so you can use frameworks confidently without being dependent on them

What kind of projects will I build?

You will build multiple practical systems, including a data-grounded AI analyst and a decision-making Analyst Agent that reads data, reasons over it, and generates business-ready insights.

Is this course focused on jobs or real-world skills?

The course is designed around industry use cases and production thinking. The skills you learn directly apply to roles involving GenAI engineering, analytics automation, and AI-powered decision systems.

Will this help me even if I’m already working?

Yes. The course is structured for working professionals and focuses on practical upgrades to your existing role, especially for those in analytics, engineering, or technical leadership positions.

Do I need deep machine learning or math knowledge?

No. You do not need ML theory or heavy mathematics. The course focuses on how to design, control, and deploy GenAI systems, not how to train models.

How many seats are available per cohort?

Each cohort is intentionally limited to around 20 participants to maintain interaction quality and hands-on guidance.

Will this course cover deployment of AI systems?

Yes, at a practical level. You will learn how to expose your AI agent as a usable application using a simple API setup, handle environment variables, and run the system as a service. The focus is on making your AI system usable in real-world scenarios, not on heavy DevOps or MLOps tooling.