Overview
Curriculum
This course breaks down how Transformers and attention mechanisms work — the backbone of today’s most advanced language models. We’ll learn how text is turned into numbers with tokenization and embeddings, how positional encoding adds word order, and how self-attention, scaled dot-product attention, and multi-head attention help models focus on what matters. By the end, we’ll understand how these pieces come together to power real-world AI applications like chatbots, translation tools, and semantic search.
What You'll Learn
- How Transformers process text with tokenization, embeddings, and position info
- See how attention decides what parts of text to focus on
- Understand how multi-head attention adds depth and context
- Explore how these ideas power real AI tools you use every day
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