AI / LLM Engineering

Go from LLM fundamentals to production RAG systems, fine-tuning, and LLM system design for engineering interviews.

35h estimated7 modules
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Modules

1Lesson

LLM Fundamentals

Transformers, tokenisation, temperature, context windows, and how LLMs actually work.

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2Quiz

LLM Fundamentals Quiz

15 questions on transformers, tokenisation, temperature, context windows, and inference.

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3Lesson

Prompt Engineering

Few-shot prompting, chain-of-thought, structured output, system prompts, and prompt injection defenses.

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4Quiz

Prompt Engineering Quiz

15 questions on few-shot prompting, CoT, structured output, and prompt injection.

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5Lesson

RAG Systems

Retrieval-Augmented Generation: chunking, embeddings, vector stores, retrieval strategies, and evaluation.

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6Coding

Coding: Semantic Search with Embeddings

Build a simple in-memory semantic search over a document corpus using cosine similarity.

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7System Design

System Design: Production RAG Pipeline

Design a production-grade RAG system: ingestion, indexing, retrieval, generation, evaluation, and monitoring.

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