USAAIO Prep: Deep Learning & Advanced AI: Visual-First Guide to the USA AI Olympiad — Volume 2

Conquer USAAIO Round 2 With the Deep Learning Prep Book Built for the Bridge ExamThe deep learning and advanced AI prep book for the USA Artificial Intelligence Olympiad.Round 2 of USAAIO is where qualifiers separate from finalists. The exam expects PyTorch fluency, transformer math you can derive by hand, attention computations under timed pressure, and generative model derivations. Volume 2 covers the deep learning half of the official syllabus that Volume 1 began.This 472-page workbook walks you through PyTorch fundamentals, neural network theory, CNNs, transformers, NLP, and generative AI — every architecture explained with diagrams first, math derived in full, and code verified against working PyTorch implementations.What You Get Inside Volume 210 chapters, 472 pages covering PyTorch, MLP foundations, CNNs, transformers and attention, NLP, generative AI (autoencoders, VAE, GAN, DDPM, Stable Diffusion, CLIP), Round 2 strategyTwo full mock exams — a 355-point Round 2 Bridge Exam and a 320-point Round 1 mock — both with detailed worked solutionsLinear attention from scratch with truncated Taylor expansion derivation, mirroring 2026 Round 2 Day 1 Problem 1DDPM full derivation from variational bound to simplified MSE loss — the KL-to-MSE collapse that Round 2 graders look forBackpropagation by hand with a complete numerical worked example, every intermediate value verifiedMulti-head attention computation by hand — small matrices, exact arithmetic, the way you must compute on the examInverse problems via CNNs — the physics-recovery problem pattern Round 2 picks deliberately to test framing skillsSemi-supervised learning and EM with monotonicity proof — the latent mixture pattern from recent Round 2 examsPyTorch and Transformer quick reference cards in the appendix for exam-day cramming Who This Book Is ForStudents who passed USAAIO Round 1 and need to prepare for the Round 2 in-person examHigh schoolers building portfolios in deep learning competitions and researchAnyone moving from following PyTorch tutorials to deriving and implementing models from first principlesCoaches and tutors looking for a Round 2 curriculum with full solutions Frequently Asked QuestionsDo I need Volume 1 first?Yes. Volume 1 covers the math foundations (linear algebra, probability, calculus, optimization) and classical ML that Volume 2 assumes you know. Read Volume 1 first or have equivalent preparation.Does this book cover the full USAAIO syllabus?Together with Volume 1, yes. Volume 2 covers every advanced topic: advanced coding for deep learning, deep learning foundation, transformers, NLP, computer vision, and generative AI. Every syllabus item gets a dedicated section.Is the code current with PyTorch 2.x?Yes. All code uses current PyTorch and HuggingFace APIs as of 2026 — no deprecated patterns. Code blocks are tested and verified.How realistic are the mock exams?Both mocks mirror the actual USAAIO format down to point allocation and time pressure. Bridge Exam Problems 2 and 3 directly mirror 2026 Round 2 Day 1 problem patterns. Solutions are graded on the rubric structure Round 2 actually uses.What if I have not done deep learning before?Chapter 10 starts from torch.tensor and walks through autograd, modules, and the training loop. If you can write a Python class, you can follow the progression.Pair with Volume 1 for full USAAIO syllabus coverage. Read more