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AI Engineering & LLMs
Implement the internals of modern language models from scratch — attention, sampling, tokenisation, embeddings, retrieval, fine-tuning maths and evaluation. The skills behind every AI engineer job posting.
AI EngineerLLM EngineerML EngineerApplied Scientist
Track progress0 / 147
0/24Unit 1: 3 to go
Foundations
Unit 1
LLMs
0 / 5 solved
Start
Unit 2
RAG & LLMs
0 / 5 solved
Unit 3
RAG I
0 / 5 solved
Unit 4
Fine-Tuning & Evaluation
0 / 2 solved
Unit 5
Evaluation & Embeddings
0 / 5 solved
Unit 6
Agents & Inference
0 / 5 solved
Unit 7
Safety & Prompting
0 / 5 solved
Unit 8
Decoding
0 / 5 solved
Unit 9
KV Cache
0 / 5 solved
Unit 10
Training Data
0 / 5 solved
Intermediate
Unit 11
Transformers
0 / 2 solved
Unit 12
LLMs & Tokenization
0 / 3 solved
Unit 13
Evaluation I
0 / 3 solved
Unit 14
Evaluation II
0 / 5 solved
Unit 15
Inference I
0 / 1 solved
Unit 16
Inference II
0 / 3 solved
Unit 17
RAG II
0 / 5 solved
Unit 18
Agents
0 / 5 solved
Unit 19
Streaming
0 / 5 solved
Unit 20
RLHF & Embeddings
0 / 3 solved
Unit 21
APIs & Retrieval
0 / 2 solved
Unit 22
Distillation
0 / 2 solved
Unit 23
Structured Output
0 / 3 solved
Unit 24
Calibration
0 / 4 solved
Advanced
Unit 25 · Pro
Inference III
0 / 0 solved
Unit 26 · Pro
Vector Search
0 / 0 solved
Unit 27 · Pro
Quantization
0 / 0 solved
Unit 28 · Pro
Tokenization
0 / 0 solved
Unit 29 · Pro
Safety
0 / 0 solved
Course complete
Clear every milestone to finish AI Engineering & LLMs.