AptAIEnroll — ₹999
AI Engineering Course

Build & ship real LLM apps.
Not just theory.

Go from zero to production: prompting, evaluation, RAG, agents, fine-tuning, and deployment — taught as clear, beautiful lessons with diagrams and four hands-on projects.

Enroll now — ₹999Try a free lesson →

69 lessons · 15 sections · Lifetime access

What you'll be able to build

🧩

Prompt like an engineer

System design, structured output, chain-of-thought, and the patterns that actually ship.

🔍

Build RAG that works

Embeddings, chunking, vector search, reranking, and production retrieval pipelines.

🤖

Ship real agents

Tools, function calling, planning loops, and memory — plus their limits.

📊

Evaluate & deploy

Evals, LLM-as-judge, monitoring, cost/latency, and responsible-AI guardrails.

The full curriculum

15 sections · 69 lessons · 4 projects

01

Course Overview

2 lessons
  • What is AI Engineering?Free
  • How This Course WorksFree
02

Module 0 · Python, APIs & Tooling

5 lessons
  • Python Essentials for AI Work
  • Environments, Packages, and Secrets
  • Calling Your First LLM API
  • JSON, Structured Data, and Errors
  • Tooling: Git, Notebooks, and the CLI
03

Module 1 · Foundations

7 lessons
  • What is a Large Language Model?
  • Tokens and Tokenization
  • Embeddings: A First Look
  • How Models Are Trained
  • Sampling, Temperature, and Decoding
  • Context Windows, Cost, and Latency
  • Failure Modes and Choosing a Model
04

Module 2 · Prompt Engineering

7 lessons
  • Anatomy of a Prompt
  • System, User, and Assistant Roles
  • Zero-shot and Few-shot Prompting
  • Structured Output and Format Control
  • Chain-of-Thought and Reasoning
  • Advanced Prompting Techniques
  • Iterating on Prompts and Common Mistakes
05

Module 3 · Evaluation

6 lessons
  • Why Evaluation Matters
  • Types of Evaluations
  • Building an Evaluation Dataset
  • Metrics and Scoring
  • LLM as a Judge
  • Running Evals and Catching Regressions
06

Project 1 · Prompt Lab

2 lessons
  • Project 1: Prompt Lab · Design
  • Project 1: Prompt Lab · Build and Evaluate
07

Module 4 · Embeddings, Retrieval & RAG

7 lessons
  • Embeddings, in Depth
  • Vector Search and Similarity
  • Chunking Strategies
  • Vector Databases and Indexing
  • Building a RAG Pipeline
  • Reranking and Context Construction
  • Production RAG Patterns
08

Module 5 · Deployment & Monitoring

5 lessons
  • Deploying an LLM App
  • Logging and Tracing
  • Monitoring Cost and Latency
  • Handling Failures and Fallbacks
  • Basic Observability
09

Project 2 · Docs Copilot

2 lessons
  • Project 2: Docs Copilot · Design
  • Project 2: Docs Copilot · Build and Serve
10

Module 6 · Agents

6 lessons
  • What Is an Agent?
  • Tools and Function Calling
  • Planning and Reasoning Loops
  • Agent Memory
  • Agent Architectures and Workflows
  • Multi-Agent Systems and Limitations
11

Project 3 · Research Agent

2 lessons
  • Project 3: Research Agent · Design
  • Project 3: Research Agent · Build and Evaluate
12

Module 7 · Fine-tuning & Dataset Engineering

5 lessons
  • When to Fine-tune (and When Not To)
  • Creating and Cleaning a Dataset
  • Formatting Data for Fine-tuning
  • Fine-tuning Approaches
  • Running and Evaluating a Fine-tune
13

Module 8 · Inference Optimization & LLMOps

5 lessons
  • Inference Performance Basics
  • Batching and Caching
  • Quantization and Model Serving
  • Scaling and Cost Optimization
  • Full LLMOps
14

Module 9 · Responsible AI, Security & Governance

5 lessons
  • Responsible AI Basics
  • Prompt Injection and Jailbreaks
  • Data Privacy and Leakage
  • Access Control and Abuse Prevention
  • Governance and Enterprise Considerations
15

Project 4 · Specialist Model

3 lessons
  • Project 4: Specialist Model · Design
  • Project 4: Specialist Model · Build
  • Project 4: Specialist Model · Evaluate and Ship

Why AptAI

LEARNClear, readable lessons with code-rendered diagrams you actually understand.
PRACTICEEvery module ends with practice questions to lock in what you learned.
BUILDFour full projects: prompt lab, docs copilot, research agent, specialist model.

Join the first learners

AptAI is new — you'll be among the first to learn AI engineering the hands-on way. Try a free lesson and see the quality for yourself.

Read a free lesson →

One price. Everything.

₹999
  • ✓ All 69 lessons across 15 sections
  • ✓ All four hands-on build projects
  • ✓ Lifetime access, including updates
  • ✓ Learn at your own pace
Enroll now — ₹999

🌍 Outside India? Email aptaihq@gmail.com for international payment options (PayPal coming soon) and we'll set up your access.

Questions

Do I need prior AI experience?

No. The course starts from Python and API foundations and builds up to advanced topics. Basic programming familiarity helps.

How long do I have access?

Lifetime access. Enroll once and revisit every lesson whenever you want, including future updates.

Is this hands-on or just theory?

Hands-on. Every module ends with practice, and there are four full build projects (prompt lab, docs copilot, research agent, specialist model).

What do I get for the price?

Full access to all 69 lessons across 15 sections, including all four projects.

How do I pay?

Secure payment via Razorpay (UPI, cards, netbanking). You'll sign in with Google, then complete checkout.

Start building with AI today.

Enroll — ₹999