LLMs  •  the tech behind GPT

Large Language Models

Understand the AI everyone's talking about — and build with it. Learn how large language models like GPT actually work (tokens, embeddings, attention, transformers), then build real applications using LLM APIs, embeddings and RAG in Python. Live, hands-on, mentor-led.

GPTHow it works
5–8Students per batch
RAGBuild real apps
LiveMentor-led

Quick answer

Modern Age Coders' Large Language Models Course teaches both how LLMs like GPT work and how to build with them. You'll understand tokens, embeddings, attention and the transformer architecture, then build real applications using LLM APIs in Python — prompting, embeddings, retrieval-augmented generation (RAG) and an introduction to fine-tuning. Classes are live in small batches of 5–8 with a mentor, group plans start at ₹1,499/month, and a free demo comes first.

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What You'll Learn

Understand & Build with LLMs

From transformers to shipping a real LLM-powered app.

How LLMs Work

Tokens, embeddings, attention and transformers — a clear mental model of what GPT-style models really do.

Build with LLM APIs

Call LLM APIs from Python, structure prompts, and wire models into real applications.

RAG & Fine-Tuning

Ground LLMs in your own data with retrieval-augmented generation, and understand when and how fine-tuning helps.

The Roadmap

The LLM Roadmap

Four stages from understanding to a working LLM app.

STAGE 01

Transformers

Tokens, embeddings and attention — how LLMs represent and process language.

STAGE 02

Build with APIs

Use LLM APIs in Python to generate, summarise and reason.

STAGE 03

RAG

Add retrieval so the model answers from your own documents.

STAGE 04

App & Fine-Tune

Ship an LLM-powered app and explore fine-tuning.

What's Next

Go Further With LLMs

Tracks that pair with LLM skills.

Why This Course

Why LLM Skills Are the Hottest in Tech

LLMs have created an entirely new category of jobs — and companies are scrambling for people who can build real products with them, not just chat in a browser. Understanding how they work and how to engineer with them is one of the most valuable skills you can have right now.

Beyond using ChatGPT

Anyone can type into a chatbot. The career skill is building applications — RAG systems, assistants, tools — on top of LLM APIs, and knowing the architecture well enough to make good engineering choices. That's what we teach.

Part of the generative-AI stack

This connects directly to prompt engineering, AI agents and generative AI — together they're the modern AI-product toolkit.

Simple Pricing

Course Fees

Transparent monthly plans, no hidden charges. Start with a free demo.

Group Batch

₹1,499per month · 2 classes/week
  • 5–8 learners per batch
  • Live LLM building
  • Recorded class access
  • Completion certificate
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Most Popular

Mini Batch

₹2,499per month · 2 classes/week
  • Only 3–4 learners per batch
  • More personal mentoring
  • Recorded class access
  • Project guidance & certificate
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1-on-1 Personal

₹4,999per month · fully personalised
  • Dedicated personal mentor
  • Custom pace & schedule
  • Recorded class access
  • Priority project & career prep
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Learner Voices

What Learners Say

★★★★★

"Built a RAG chatbot over my own documents. Understanding transformers made every design choice clearer."

Aditya R.
Working professional
★★★★★

"This took me from 'ChatGPT user' to 'I can build LLM apps'. Huge for my career."

Sana M.
Career switcher
★★★★★

"Clear on attention and embeddings, and the hands-on API work was gold."

Vivek K.
College student

Build with the AI everyone's talking about

Book a free demo and build an LLM-powered app with a mentor before you spend a rupee.

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Good To Know

Frequently Asked Questions

What does the Large Language Models Course cover?+

It covers How LLMs Work, Build with LLM APIs, RAG & Fine-Tuning. Understand the AI everyone's talking about — and build with it. Learn how large language models like GPT actually work (tokens, embeddings, attention, transformers), then build real applications using LLM APIs, embeddings and RAG in Python. Live, hands-on, mentor-led.

Who is this course for?+

It's designed for college students, working professionals and serious teens who want practical, job-ready AI and machine-learning skills. After the free demo we place you at the right level for your background.

Do I need prior experience to join?+

No heavy prerequisites — we start from the right point for you and build up. Some Python helps for the more advanced topics, and if you're new we cover what you need. The free demo lets us assess your level first.

Will I work on real, hands-on projects?+

Yes. Every topic is hands-on in Python/Colab and you build real, mentor-reviewed work — not just theory — so you finish with practical skill and something to show.

How much does the course cost?+

Group classes start at ₹1,499 per month for 2 classes a week. A Mini Batch of 3–4 students is ₹2,499 per month, and 1-on-1 mentoring is ₹4,999 per month. A free demo class is available first.

Are the classes live and mentor-led?+

Yes. Classes are live in small batches of 5–8 with a mentor who reviews your work, and every session is recorded so you can revise anytime. It's real-time teaching, not pre-recorded videos.

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