CS109 | Schedule

All times listed are Pacific Time.
Lecture Notes for future lectures are drafts and may be updated as the course progresses.
Optional readings are from Sheldon Ross, A First Course in Probability (10th Ed.), Prentice Hall, 2018. The textbook's 8th and 9th editions have the same readings and corresponding section headers.

Date	Lecture contents	Assignments
Week 1
Mon Sep 14	1 Counting Concept Check Lecture Notes Welcome/Logistics Sum Rule, Product Rule Inclusion/Exclusion Principle General Rule of Counting Slides (Blank) (Annotated) Syllabus , Honor Code Policy Read: Ch 1.1-1.2. Lecture Notes have end-of-lecture exercises
Wed Sep 16	2 Permutations and Combinations Concept Check Lecture Notes Permutations Combinations Buckets and dividers Slides (Blank) (Annotated) Read: Ch 1.3-1.6	Out: PSet #1
Fri Sep 18	3 Axioms of Probability Concept Check Lecture Notes Frequentist definition of probability Axioms and corollaries of Probability Probability of equally likely outcomes Slides (Blank) (Annotated) Python for Probability , Calculation Ref , Full Probability Reference Serendipity Read: Ch 2.1-2.5, 2.7
Week 2
Mon Sep 21	4 Conditional Probability and Bayes Concept Check Lecture Notes Conditional probability Chain Rule Law of Total Probability Bayes' Theorem Monty Hall Problem Slides (Blank) (Annotated) Medical Bayes Read: Ch 3.1-3.3
Wed Sep 23	5 Independence Concept Check Lecture Notes Generalized Chain Rule Independence Independent Trials deMorgan's Laws Slides (Blank) (Annotated) Read: Ch 3.4-3.5
Fri Sep 25	6 Random Variables and Expectation Concept Check Lecture Notes Conditional independence Random variables Probability Mass Function (PMF) Cumulative Distribution Function (CDF) Expectation Slides (Blank) (Annotated) Read: Ch 4.1-4.4	Due: Pset #1, 1PM Out: PSet #2
Week 3
Mon Sep 28	7 Variance, Bernoulli, Binomial Concept Check Lecture Notes Variance Properties of variance Bernoulli RV Binomial RV Slides (Blank) (Annotated) Galton Read: Ch 4.5-4.6
Wed Sep 30	8 Poisson and More Concept Check Lecture Notes Poisson RV Geometric RV and Negative Binomial Poisson approximation to the Binomial Modeling exercise: Hurricanes Slides (Blank) (Annotated) Latex Cheat Sheet Read: Ch 4.7-4.10
Fri Oct 2	9 Continuous Random Variables Concept Check Lecture Notes Probability Density Function Uniform RV Exponential RV Properties of the CDF Slides (Blank) (Annotated) Jurors Read: Ch 5.1-5.3, 5.5
Week 4
Mon Oct 5	10 The Normal Distribution Concept Check Lecture Notes Normal (Gaussian) RV Normal Symmetry, Linear Transforms Standard Normal RV Sampling to compute probabilities involving two Normal RVs Slides (Blank) (Annotated) Standard Normal Table , Normal CDF Calculator ELO scores Read: Ch 5.4	Due: PSet #2, 1PM Out: PSet #3
Wed Oct 7	11 Joint Distributions Concept Check Lecture Notes Normal approximation to the Binomial Discrete joint random variables Multinomial RV Proving Linearity of Expectation Slides (Blank) (Annotated) Read: Ch 6.1	Quiz #1
Fri Oct 9	12 Independent Random Variables Concept Check Lecture Notes Independent discrete RVs Sum of Independent Binomial RVs Sum of independent Poisson RVs Discrete Convolution Slides (Blank) (Annotated) Read: Ch 6.2-6.3
Week 5
Mon Oct 12	13 Joint RV Statistics Concept Check Lecture Notes Coupon Collecting Problems Covariance Variance for Independent RVs Correlation Slides (Blank) (Annotated) Read: Ch 6.4-6.5
Wed Oct 14	14 Conditional Expectation Concept Check Lecture Notes Conditional distributions Conditional expectation Law of Total Expectation Analyzing Recursive Code Slides (Blank) (Annotated) Read: Ch 7.1-7.2
Fri Oct 16	15 General Inference Concept Check Lecture Notes Bayesian Networks Inference from first principles Inference with Rejection Sampling Slides (Blank) (Annotated) WebMD Lecture Notes	Due: PSet #3, 1PM Out: PSet #4
Week 6
Mon Oct 19	16 Continuous Joint Distributions Concept Check Lecture Notes Continuous joint distributions Joint CDFs Independent continuous joint RVs Bivariate (Multivariate) Gaussian RVs Slides (Blank) (Annotated) Read: Ch 6.1
Wed Oct 21	17 Continuous Joint Distributions II Concept Check Lecture Notes Continuous Convolution Sum of Independent Uniforms Sum of Independent Normal RVs Continuous Conditional Distributions Tracking in 2-D space Slides (Blank) (Annotated) Read: Ch 7.3-7.4
Fri Oct 23	18 Central Limit Theorem Concept Check Lecture Notes i.i.d. Random Variables: Independent and Identically Distributed Central Limit Theorem Slides (Blank) (Annotated) CLT Read: Ch 8.3
Week 7
Mon Oct 26	19 Sampling/Bootstrapping Concept Check Lecture Notes Population mean/variance, Sampling mean/variance Unbiased estimators Standard Error Bootstrap for Standard Error Bootstrap for Hypothesis Testing Slides (Blank) (Annotated) Bootstrap Read: Lecture Notes	Due: Pset #4, 1PM Out: Pset #5
Wed Oct 28	20 Parameters and MLE Concept Check Lecture Notes Intro to Parameter Estimation Maximum Likelihood Estimator Argmax and log-likelihood MLE: Bernoulli MLE: Poisson, Uniform, and Gaussian Slides (Blank) (Annotated) MLE Uniform Read: Lecture Notes	Quiz #2
Fri Oct 30	21 Beta Concept Check Lecture Notes MLE: Multinomial Bayesian Definition of Probability Beta Random Variable Beta and flipping a coin with unknown probability Slides (Blank) (Annotated) Beta Read: Ch 5.6.1-5.6.4, 7.5-7.6
Week 8
Mon Nov 2	22 Maximum a Posteriori Concept Check Lecture Notes Maximum a Posterior Estimator Bernoulli MAP: Choosing a prior Conjugate distributions for common RVs Laplace smoothing Bayesian Envelope demo Slides (Blank) (Annotated) Read: Lecture Notes
Wed Nov 4	23 Quicksort Lecture Notes Runtime analysis of Quicksort Optional content for Fall 2020 This lecture will not show up in any graded material. Slides (Blank) (Annotated) Read: Nothing!
Fri Nov 6	24 Naive Bayes Concept Check Lecture Notes Strawman: 'Brute Force Bayes' Naive Bayes Classifier Naive Bayes example: MLE and MAP Naive Bayes: MAP with email classification Slides (Blank) (Annotated) Read: Lecture Notes	Due: Pset #5, 1PM Out: Pset #6
Week 9
Mon Nov 9	25 Gradient Ascent and Linear Regression Concept Check Lecture Notes Linear Regression Minimum Squared Error Gradient Ascent Slides (Blank) (Annotated) Gradient Ascent Read: Lecture Notes
Wed Nov 11	26 Logistic Regression Concept Check Lecture Notes Logistic Regression Training a classifier Testing a classifier Slides (Blank) (Annotated) Read: Lecture Notes
Fri Nov 13	27 Deep Learning Lecture Notes Optional content: Intro to neural networks No concept check Slides (Blank) (Annotated)
Week 10
Mon Nov 16	28 Probability Bounds Lecture Notes Optional content: Probability Bounds No concept check Markov's Inequality Chebyshev's Inequality Jensen's Inequality Strong and Weak Law of Large Numbers Slides (Blank) (Annotated)	Due: Pset #6, 1PM
Wed Nov 18	29 Simulating Probabilities Slides (Blank) (Annotated) Simulating Probabilities	Quiz #3
Fri Nov 20	30 Beyond CS109 Slides (Blank)

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