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 engines.
What You'll Learn
- How Transformers process text with tokenization, embeddings, and position information
- 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 we use every day
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