Free & Open Source20 LessonsReal Code

AI Engineering from First Principles

Go from zero to production AI systems. Every technique you learn, you prove with benchmarks. No fluff, no theory-only lectures. Working code with SOTA results.

5
Levels
20
Lessons
50+
Code Examples
SOTA
Benchmarks
Start LearningView Roadmap

What You'll Build

Level 2

Voice Assistant

Whisper + LLM + TTS. 2-second response time.

Level 3

Production RAG

Hybrid search + reranking. RAGAS score >0.8.

Level 4

AI Agent Pipeline

Tool calling + multi-agent orchestration.

Learning Roadmap

0

Foundations

No AI experience required

0.1

What is an Embedding?

Vectors that capture meaning. Interactive visualization.

0.2

APIs vs Local Models

Cloud or self-hosted? Cost calculator included.

0.3

Tokens & Context Windows

How LLMs read text. Pricing per million tokens.

0.4

Environment Setup

Python, API keys, GPU setup, Docker.

1

Single Blocks

Master individual building blocks

1.1

Text Embeddings

MTEB benchmarks. BGE, OpenAI, Cohere comparison.

1.2

Image Search with CLIP

Zero-shot classification. Cross-modal search.

1.3

Speech Recognition

Whisper. WER benchmarks. Speaker diarization.

1.4

Text Classification

Zero-shot vs fine-tuned. GLUE/SST-2 benchmarks.

1.5

Object Detection

YOLO v11, RT-DETR, Grounding DINO. COCO mAP.

1.6

Image Segmentation

SAM 2. Point prompts, automatic masks.

1.7

Text-to-Speech

OpenAI TTS, ElevenLabs, Coqui, Bark.

1.8

Document Parsing

Docling, Marker, VLM OCR. OmniDocBench.

2

Pipelines

Chain 2-3 blocks together

2.1

Caption + Search

Image captioning + embeddings for visual search.

2.2

Voice Assistant

Whisper → LLM → TTS. Latency optimization.

2.4

Basic RAG

Chunk, embed, retrieve, generate.

3

Production

Real-world patterns

3.1

Hybrid Search

BM25 + vector. Reciprocal Rank Fusion.

3.2

Reranking

Cross-encoder reranking. NDCG improvements.

3.3

Document RAG

Chunking strategies, citations, RAGAS eval.

3.4

Hallucination Detection

NLI verification, self-consistency, faithfulness.

4

Advanced

Complex compositions

4.1

Multi-modal RAG

RAG over images, tables, and text. ColPali.

4.2

Agent Pipelines

ReAct, tool calling, multi-agent orchestration.

4.3

Video Understanding

Frame sampling, Video-LLMs, temporal analysis.

4.4

Real-time Systems

Streaming, vLLM, latency optimization.

Why This Course

Other Courses

  • "Week 1: Introduction to AI" (calendar-locked)
  • Toy examples that don't work in production
  • "Trust us, this works" - no benchmarks
  • Outdated by the time you finish

This Course

  • Self-paced. All 20 lessons available now.
  • Production code you can copy-paste
  • Every technique linked to SOTA benchmarks
  • Updated with latest models and techniques

Start Now

Begin with embeddings. Build up to production RAG and agent pipelines.

Start Lesson 0.1Explore Building Blocks