NO CODING EXPERIENCE REQUIRED. NO PREREQUISITES.

USE CHATGPT.

BUILD YOUR OWN CHATGPT.

Learn how GPT works from scratch: tokens, embeddings, causal attention, and transformers. Train your own ChatGPT using a pre-written notebook based on Sebastian Raschka's seminal book.

// DURATION 2 Days • 3 Hours/Day (6h Total)

EXPLORE SYLLABUS

CAUSAL ATTENTION MECHANICS VISUALIZER (INTERACTIVE) GPT-2 ARCHITECTURE SIMULATION

[HOVER / TAP ANY TOKEN ABOVE TO INSPECT QUERY VECTORS & ATTENTION WEIGHTS] SEBASTIAN RASCHKA ARCHITECTURE REFERENCE

// TOKENS & VOCABULARY • HIGH-DIMENSIONAL EMBEDDINGS • CAUSAL SELF-ATTENTION (Q, K, V) • MULTI-HEAD ATTENTION • TRANSFORMER BLOCKS • CHATGPT TRAINING LOOP • LOSS & OVERFITTING • TEMPERATURE & TOP-K SAMPLING • RLHF & FINE-TUNING OVERVIEW • // TOKENS & VOCABULARY • HIGH-DIMENSIONAL EMBEDDINGS • CAUSAL SELF-ATTENTION (Q, K, V) • MULTI-HEAD ATTENTION • TRANSFORMER BLOCKS • CHATGPT TRAINING LOOP • LOSS & OVERFITTING • TEMPERATURE & TOP-K SAMPLING • RLHF & FINE-TUNING OVERVIEW

THE REALITY CHECK

“Only 1% of students can build this.”

The other 99% are merely writing prompts into a web chatbot.

Soon your resume will say:
I built GPT from scratch.

In any tech interview, reciting prompt engineering tips gets ignored. Explaining how queries and keys calculate dot-product attention scores makes you stand out immediately.

// THE 99% (CONSUMERS)

× Uses OpenAI APIs as a black box without understanding tokens.
× Confuses temperature with intelligence.
× Cannot explain why causal masking is required for autoregression.
× Resumes look identical to every other applicant.

// THE 1% (ARCHITECTS)

✓ Knows exactly how tokens map to high-dimensional embedding vectors.
✓ Can calculate scaled dot-product attention step-by-step by hand.
✓ Trained a functional ChatGPT model and monitored loss convergence live.
✓ Can articulate transformer internals in any engineering interview.

RIGOROUS CURRICULUM

2 DAYS. 6 HOURS. FULL BREAKDOWN.

Constructed for deep comprehension without fluff. We spend 3 hours understanding how a model reads and focuses, and 3 hours building, training, and running inference.

PART 1 // DAY 01 (3 HOURS) FOUNDATIONS & ATTENTION

How a Model Reads and Focuses

MODULE 1.1

What an LLM Really Is

MODULE 1.2

Text to Numbers (Tokens & Embeddings)

MODULE 1.3

The Attention Mechanism Worked By Hand

PREREQUISITES: NONE 3 HOURS LIVE

PART 2 // DAY 02 (3 HOURS) ARCHITECTURE & TRAINING

Building, Training, and Using the Model

MODULE 2.1

The Transformer Block & Stacking

MODULE 2.2

Training Your ChatGPT Model

MODULE 2.3

Text Generation & Sampling

OUTPUT: TRAINED CHATGPT 3 HOURS LIVE

ZERO PREREQUISITES

NO CODING REQUIRED DURING SESSIONS.

You do not need prior machine learning experience, advanced mathematics, or coding proficiency. The code is pre-written and curated from Sebastian Raschka's proven architecture.

// HARDWARE REQUIREMENTS:

A standard web browser (Chrome, Brave, Edge, Safari). All training runs on Google Colab's cloud GPUs. No expensive Mac or RTX GPU required.

ALL-INCLUSIVE ENROLLMENT

INR 999

ORIGINAL FEE: INR 4,999

ONE-TIME PAYMENT NO SUBSCRIPTIONS

✓ 2 Days of Live Interactive Technical Instruction (6 Total Hours)

✓ Full Pre-written PyTorch ChatGPT Notebook (Colab Ready)

✓ Certificate of Completion for LinkedIn & Resume

Encrypted payment processed through Razorpay. UPI, Debit/Credit Card, and Netbanking accepted.

CLARIFICATIONS

FREQUENTLY ASKED QUESTIONS.

Do I need to know Python or machine learning beforehand? +

No. The code is entirely pre-written and designed for conceptual comprehension. You do not write raw code from a blank screen during the session. We walk through how tokens turn into matrices, calculate attention dot-products by hand, and execute the training notebook in Google Colab with one click.

What kind of ChatGPT will I build, and how does it work? +

You will build and train the exact autoregressive Transformer decoder architecture that powers ChatGPT. We implement tokens, embeddings, causal multi-head attention, and feedforward blocks in PyTorch, then execute the full training loop directly in Google Colab so you see your model predict and generate text in real time.

How will I join the live classes after registering? +

As soon as your payment is verified, you receive immediate confirmation on screen, an email receipt, and a direct link to join the private WhatsApp cohort community where meeting links and notebooks are shared.