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AI Interview MasteryIntermediate → SeniorNEW
Transformer Architecture Q&A
Attention, encoders, decoders, and the math behind transformers. 60 questions covering every aspect of transformer architecture — from multi-head attention to positional encoding to the training objective.
4.9rating2,560 students2h total23 lessons
What you'll learn
Draw and explain the full transformer architecture from memory
Derive the scaled dot-product attention formula and explain each term
Explain multi-head attention and why multiple heads help
Describe encoder-only, decoder-only, and encoder-decoder models with examples
Explain positional encodings: sinusoidal, learned, RoPE, ALiBi
Walk through the training objective: cross-entropy on next-token prediction
Final Project
Whiteboard the full transformer architecture and answer 10 follow-up questions from an interviewer
Curriculum
23 lessons · 2hCourse Info
Lessons23 lessons
Total time2h
LevelIntermediate → Senior
Students2,560
Rating4.9 / 5.0