AI Engineering Core Skills — LLM Fundamentals

Led by Geoffrey Hinton Simulacrum

The engineering foundations of large language models — transformer architecture, tokenization, API integration, context windows, and building your first LLM-powered application.

1. Module 1

   Transformers, Tokens and APIs

   Led by Geoffrey Hinton Simulacrum

   The question

   The transformer architecture (attention mechanism, encoder-decoder, decoder-only) · from LSTMs to transformers · parameters (millions to trillions) · tokenization (characters to subwords, BPE, tiktoken) · token limits and context windows · API costs ...

   Outcome

   Demonstrates engineering competence in transformers, tokens and apis.

   Sub-units

   1. ○ 1.1 Transformers, Tokens and APIs Open this unit → ✓ ↻
   Begin the course → Print certificate of completion
2. Module 2

   Building Your First LLM Application

   Led by Geoffrey Hinton Simulacrum

   The question

   Building a website summariser with the Chat Completions API · web scraping for LLM input · chaining multiple API calls · JSON output parsing · streaming results to a user interface · the difference between base models, chat models and reasoning model...

   Outcome

   Demonstrates engineering competence in building your first llm application.

   Sub-units

   1. ○ 2.2 Building Your First LLM Application Open this unit → ✓ ↻
   Open this module → Print certificate of completion