- Week 1 - Undirected Graph & Directed Graph
- Week 3 - Maximum Flow and Minimum Cut & Radix Sort
- Week 4 - Tries & Substring Search

- Week 1 - Union-Find & Analysis of Algorithms
- Week 2 - Stacks and Queues & Elementary Sorts
- Week 3 - Mergesort & Quicksort
- Week 4 - Priority Queues & Elementary Symbols
- Week 5 - Balanced Search Trees
- Week 6 - Hash Tables

- Week 1 - Sequences
- Week 2 - Series
- Week 3 - Convergence Tests
- Week 4 - Alternating Series
- Week 5 - Power Series
- Week 6 - Taylor Series

- Week 1 - Vectors in Linear Algebra
- Week 2 - Linear Transformations and Matrices
- Week 3 - Matrix-Vector Operations
- Week 4 - Matrix-Vector to Matrix-Matrix Multiplication
- Week 5 - Matrix- Matrix Multiplication
- Week 6 - Gaussian Elimination
- Week 7 - More Gaussian Elimination and Matrix Inversion
- Week 8 - More on Matrix Inversion
- Week 9 - Vector Spaces
- Week 10 - Vector Spaces, Orthogonality, and Linear Least-Squares
- Week 11 - Orthogonal Projection, Low Rank Approximation, and Orthogonal Bases
- Week 12 - Eigenvalues and Eigenvectors

- Week 1 - Introduction
- Week 2 - Linear Regression with Multiple Variables
- Week 3 - Logistic Regression & Regularization
- Week 4 - Neural Networks: Representation
- Week 5 - Neural Networks: Learning
- Week 6a - Advice for Applying Machine Learning
- Week 6b - Machine Learning System Design
- Week 7 - Support Vector Machines
- Week 8 - Unsupervised Learning & Dimensionality Reduction
- Week 9a - Anomaly Detection
- Week 9b - Recommender Systems
- Week 10 - Large Scale Machine Learning
- Week 11 - Application Example: Photo OCR

- Week 2-3 - Functions & Limits
- Week 4 - The Beginning of Derivatives
- Week 5 - Techniques of Differentiation
- Week 6 - Chain Rule
- Week 7 - Derivatives of Trigonometric Functions
- Week 8 - Derivatives in the Real World
- Week 9 - Optimization
- Week 10 - Linear Approximation
- Week 11-12 - Antidifferentiation & Integration
- Week 13 - Fundamental Theorem of Calculus
- Week 14 - Substitution Rule
- Week 15 - Techniques of Integration
- Week 16 - Applications of Integration

- Lecture 1 - Optimization and Knapsack Problem
- Lecture 2 - Decision Trees and Dynamic Programming
- Lecture 3 - Graphs
- Lecture 4-5 - Plotting
- Lecture 6-7 - Stochastic Programs & Inferential Statistics
- Lecture 8 - Monte Carlo Simulation
- Lecture 9 - Sampling and Standard Error
- Lecture 10-11 - Experimental Data
- Lecture 12 - Machine Learning
- Lecture 13 - Statistical Abuses

- Week 1 - C
- Week 2 - Arrays
- Week 3 - Algorithms
- Week 4 - Memory
- Week 5 - Data Structures
- Week 6 - HTTP
- Week 7-10 - Machine Learning/Python/SQL/Javascript