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Applied Machine Learning — Cohort #0

14 chapters · 16 content weeks · 3 breaks
16 weeksNov 2 – Mar 8, 2027
Wednesdays, 5:00 pm PacificLive office hours with Uri. Tentative: we will set the real slot with the cohort in week 1.
One chapter a weekwith two exceptions, below
WeekBeginsWhat you're working throughOpens
Week 1Nov 2, 2026Chapter 1 — Orientation to Machine Learning · 15 sectionsNov 2, 2026Chapter 1: Orientation to Machine LearningCh 1free to read now
Week 2Nov 9, 2026Chapter 2 · Part 1 · 19 sectionsNov 9, 2026Chapter 2: The ML Workflow and Gradient DescentCh 2free to read now
Week 3Nov 16, 2026Chapter 2 · Part 2 · 15 sectionsNov 16, 2026Chapter 2 · Part 2: The Theory of Learning
Nov 23, 2026Thanksgiving breakNov 23, 2026
Week 4Nov 30, 2026Chapter 3 · 36 sectionsNov 30, 2026Chapter 3 · Part 1: Shaping the Data, from Missing Values to Scaling · Chapter 3 · Part 2: Reducing the Hypothesis Space with Feature Selection, Regularization and Cross-ValidationCh 3
Week 5Dec 7, 2026Chapter 4 · 15 sectionsDec 7, 2026Chapter 4: Logistic Regression, from Intuition to MLECh 4
Week 6Dec 14, 2026Chapter 5 · 33 sectionsDec 14, 2026Chapter 5 · Part 1: Evaluation, or Choosing What to Measure · Chapter 5 · Part 2: Softmax and Multiclass ClassificationCh 5
Dec 21, 2026Winter breakDec 21, 2026
Dec 28, 2026Winter breakDec 28, 2026
Week 7Jan 4, 2027Chapter 6 · 35 sectionsJan 4, 2027Chapter 6 · Part 1: Classic ML on Tabular Data with kNN, Trees and Ensembles · Chapter 6 · Part 2: The Classic Machine Learning Algorithms (kNN, Trees, Ensembles) Through the Domingos TriadCh 6
Week 8Jan 11, 2027Chapter 7 · 18 sectionsJan 11, 2027Chapter 7: Clustering, from k-Means to Gaussian MixturesCh 7
Week 9Jan 18, 2027Chapter 8 · 30 sectionsJan 18, 2027Chapter 8 · Part 1: Feed-Forward Networks, from a Linear Equation to a Universal Approximator · Chapter 8 · Part 2: Building a Feed-Forward Neural Network, from make_moons to MNISTCh 8
Week 10Jan 25, 2027Chapter 9 · 18 sectionsJan 25, 2027Chapter 9: Dimensionality Reduction, from PCA to AutoencodersCh 9
Week 11Feb 1, 2027Chapter 10 · Parts 1-2 · 29 sectionsFeb 1, 2027Chapter 10 · Part 1: Text Embeddings, from Bag of Words to Pretrained Language Models · Chapter 10 · Part 2: Opening the Black Box of Attention and the TransformerCh 10
Week 12Feb 8, 2027Chapter 10 · Part 3 · 14 sectionsFeb 8, 2027Chapter 10 · Part 3: Fine-Tuning a Pretrained Encoder to Detect Toxic Comments
Week 13Feb 15, 2027Chapter 11 · 22 sectionsFeb 15, 2027Chapter 11: Convolutional Neural NetworksCh 11
Week 14Feb 22, 2027Chapter 12 · 20 sectionsFeb 22, 2027Chapter 12: Neural Network Architecture DesignCh 12
Week 15Mar 1, 2027Chapter 13 · 16 sectionsMar 1, 2027Chapter 13: Recommendation EnginesCh 13
Week 16Mar 8, 2027Chapter 14 · 29 sectionsMar 8, 2027Chapter 14 · Part 1: Fairness & the Ethics of Prediction · Chapter 14 · Part 2: The Fairness AuditCh 14

Chapters 1 and 2 are free for anyone to read now. The rest open to the cohort on the dates above and stay open — nothing is taken away. Where a chapter spans two weeks, the whole chapter opens on the first of them; the second week is pacing, not a second gate.