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The full curriculum

23 learning units live now. 176 exercises. Every concept taught through a live playground, not slides.

50 free exercises
126 paid exercises
₹499 full access

Concepts

74 exercises
01

Meet the LLM: How Prompting Actually Works

Free

Interact with an LLM for the first time and build a working mental model of how prompting works.

LLM fundamentals Prompting basics Mental models
13 ex
09

What Is an LLM? Building Your Mental Model

Explore the behavioral architecture of a Large Language Model.

LLM architecture Transformers Neural networks
10 ex
10

How LLMs Are Built: Training, Fine-Tuning & Model Families

Understand how LLMs are trained and the differences between model families.

Training Fine-tuning Model families RLHF
10 ex
11

Tokens: The Atomic Unit of Every LLM Interaction

Master tokenization, token limits, and how they affect cost and context.

Tokenization Token limits Cost calculation
9 ex
12

Context Windows: Memory, Limits & What Gets Forgotten

Understand context window limitations and how to work within them.

Context window Memory limits Long context
8 ex
13

Temperature & Sampling: Dialing Consistency vs. Creativity

Control randomness and creativity with temperature and sampling parameters.

Temperature Top-K Top-P Sampling
9 ex
14

Hallucinations: Why LLMs Lie Confidently and How to Fight Back

Understand why models hallucinate and strategies to reduce it.

Hallucinations Factuality Grounding
9 ex
15

Safety, Ethics & Alignment: Guardrails, Attacks & Responsible Deployment

Learn about AI safety, bias, and responsible deployment practices.

Safety Ethics Bias Alignment Jailbreaking
6 ex

Engineering

57 exercises
02

The Anatomy of a Prompt: 5 Building Blocks

Free

Decompose prompts into Task, Context, Examples, Format, and Constraints.

Prompt structure Building blocks Minimum viable prompt
15 ex
03

Clarity and Specificity: Killing Vague Prompts

Free

Rewrite vague, fuzzy prompts into concrete, specific, measurable instructions.

Clarity Specificity Concrete language
11 ex
04

Showing, Not Telling: Examples and Few-Shot Prompting

Free

Use examples to control output style, format, and quality without writing long instructions.

Few-shot prompting Zero-shot Example quality
11 ex
05

Shaping the Output: Format, Length, and Tone

Reliably produce output in a target format, length, and tone.

Output formatting Length control Tone matching
5 ex
06

The Prompting Loop: Iteration and Debugging

Treat prompting as an iterative loop—diagnose failures and fix the right layer.

Iteration Debugging Failure modes
5 ex
07

Roles, Personas, and Reasoning Scaffolds

Apply persona prompts and reasoning scaffolds appropriately.

Personas Chain-of-thought Reasoning scaffolds
5 ex
08

Capstone: Build It End-to-End + Bridge to Module 2

Synthesize every Module 1 concept into one real, multi-part prompt.

Integration Multi-step prompts Self-assessment
5 ex

Advanced

45 exercises
16

RAG: Giving LLMs a Knowledge Base They Were Never Trained On

Build Retrieval-Augmented Generation systems to extend LLM knowledge.

RAG Retrieval Vector search Embeddings
7 ex
17

From Prompts to Systems — The Advanced LLM Landscape (2026)

Map the full advanced LLM ecosystem across architectural layers.

LLM stack Architecture layers System design
10 ex
18

Advanced Prompt Engineering — Chain-of-Thought, Meta-Prompting & Prompt Chaining

Master advanced prompting techniques for complex tasks.

CoT Meta-prompting Prompt chaining Tree-of-Thought
10 ex
19

System Prompts & Structured Outputs — Production-Grade Prompt Architecture

Architect production-ready system prompts with structured JSON outputs.

System prompts JSON mode Schema validation
10 ex
20

LLM APIs in Production — OpenAI, Anthropic & Gemini Deep Dive

Build resilient, production-grade LLM API integrations.

API integration Streaming Rate limiting Multi-modal
2 ex
21

Advanced RAG Architecture — HyDE, Re-ranking, Hybrid Search & Multi-hop Retrieval

Build production-grade RAG systems with advanced techniques.

HyDE Re-ranking Hybrid search Multi-hop
2 ex
22

Vector Databases & Embeddings — Choosing, Indexing & Scaling for Production

Design and scale vector database infrastructure.

Vector DBs Embeddings HNSW Multi-tenancy
2 ex
23

LLM Agents & Tool Use — ReAct, Function Calling & Multi-step Reasoning

Build autonomous agents with tool use and multi-step reasoning.

ReAct Function calling Tool use Agents
2 ex

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