Week Monday Wednesday Friday
1 1/5
Administriva, Counting
1/7
Permutations and Combinations
1/9
Intro to Probability
2 1/12
Conditional Probability
1/14
Independence
1/16
Conditional Independence, Discrete Random Variables, Probabilty Mass Functions, and Expected Value
3 1/19
Martin Luther King Day - No Class
1/21
Variance & Discrete Distributions
1/23
More Discrete Distributions
4 1/26
Continuous Random Variables
1/28
Normal Distribution
1/30
Joint Distribution Functions
5 2/2
Independent Random Variables
2/4
Conditional Distributions
2/6
Properties of Expectation & QuickSort
6 2/9
Covariance & Correlation
2/11
Conditional Expectation
2/13
Moment Generating Functions
7 2/16
President's Day - No Class
2/18
Helpful Inequalities and theorems
2/20
Laws of Large Numbers (weak and strong), Central Limit Theorem
8 2/23
Central Limit Theorem, Parameter Estimation
2/25
Parameter Estimation, Maximum Likelihood Estimation
2/27
Maximum Likelihood Estimation, Bayesian Prediction
9 3/2
Introduction to Machine Learing and Naive Bayes
3/4
Logistic Regression
3/6
Modeling Uncertainty and Utilitiy
10 3/9
Simulating Probabilities and Monte Carlo Simulation
3/11
Final Review
3/13
Final Review
  • Reading: N/A