Standard syllabus
Machine learning · Graduate · Data science
Topics
Foundations
- Statistical learning framework: risk, ERM, and generalization
- Bias–variance tradeoff and complexity control
- Linear models, kernels, and regularization theory (intro)
- Optimization for ML: GD, SGD, and convexity survey
- Probabilistic models and MLE/MAP intuition
- Representation learning motivation
Core methods
- Trees, boosting, and random forests in depth
- SVMs and kernel methods (course-dependent)
- Neural networks: backprop and architectures survey
- Unsupervised learning: clustering, PCA, embeddings
- Sequence and graph model survey (optional)
- Generative models overview (VAE/GAN/diffusion survey)
Evaluation and theory practice
- Proper scoring rules and calibration
- Cross-validation theory pitfalls
- Multiple testing in model search
- Domain shift and robustness (intro)
- Interpretability methods and limits
- Reproducibility of ML experiments
What each unit includes
Open a unit below for full materials. Typical resources:
- Study guide
- Exam Strategy
- Common Mistakes
- Worksheets
- Word problems
- Mixed Practice
- Multi-Unit Problems
- Review
- Practice test
- Answer key
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- Foundations
Statistical learning framework: risk, ERM, and generalization
Coming soon - Core methods
Trees, boosting, and random forests in depth
Coming soon - Evaluation and theory practice
Proper scoring rules and calibration
Coming soon - Implementation depth
Implementing algorithms from pseudocode
Coming soon - Responsible ML
Dataset documentation and leakage audits
Coming soon
Pricing calculator
Choose materials, tutoring, or both — or book a single session as needed. Customize your plan on the subscribe page.
$1,162 · Machine learning · 18 tutoring hrs
Study guides, worksheets, reviews, practice tests, and answer keys for 1 class. 18 tutoring hours (1 hr / week · semester). Bundle discount applied vs buying separately. Pay in full via Zelle.