CS109: Probability for Computer Scientists, Winter 2024

Announcements and Updates

  • Sat, Mar 9: Eliza Gallagher is the Co-President of WiCS, and she emailed me to share news of a program they're co-sponsoring: the WiCS x Orca Network Start-up Competition. She included this in her email:

  • This program will run through mid-May and provide many mentorship opportunities. All majors and experience levels are welcome! We are providing a series of workshops and speakers to help you (even if you have never even thought about founding a start-up before).

    Relevant links:
    • The application is right here.
    • The workshop schedule and competition overview is right here.
    • And visit here to let those running the workshop know you're interested, even if you're not really to apply just yet.
  • Let me know if you'd like me to connect you to Eliza over email.

  • Tue, Mar 5: We've decided to give those working on a CS109 Challenge entry to take even more time to submit. The new deadline is March 16th at noon!
  • Thu, February 29: I know it's a while away, but we're planning a final exam review session for Thursday, March 14th at noon, to be held in Huang 018, which is a cute, little room just around the corner from NVIDIA Auditorium. Friday, March 15th during what would have been our normally scheduled lecture. Matt Harvill and Isabel Michel will be leading the session. The session will be recorded for those who can't attend in person.

This Week

Week 10
Topic
Materials
Assignments
Optional Readings
Week 10
Mon, Mar 11
Lecture 26: Deep Learning
Ross: No assigned reading.,
Piech: No assigned reading.
Wed, Mar 13
Lecture 27: Ethics in Probability and AI
Ross: No assigned reading.,
Piech: No assigned reading.
Thu, Mar 14
Section 9: Final Exam Review
Fri, Mar 15
No lecture
PSet 6 In

Schedule

Week 1
Mon, Jan 08
Lecture 1: Introductions
Piech: Counting
Wed, Jan 10
Lecture 2: Permutations and Combinations
PSet 1 Out
Fri, Jan 12
Lecture 3: Axioms of Probability
Ross: Ch 2.1-2.5, 2.7
Piech: Probability, Equally Likely Outcomes
Week 2
Mon, Jan 15
Observance of Martin Luther King Day. No lecture.
Wed, Jan 17
Lecture 4: Conditional Probability and Bayes Rule
Thu, Jan 18
Section 1: Combinatorics and Probability
Fri, Jan 19
Lecture 5: Independence
PSet 1 In, PSet 2 Out
Ross: Ch 3.4-3.5
Piech: Independence
Week 3
Mon, Jan 22
Lecture 6: Random Variables and Expectation
Ross: Ch 4.1-4.4
Piech: Random Variables, Probability Mass Functions
Wed, Jan 24
Lecture 7: Variance, Bernoulli, Binomial
Ross: Ch 4.5-4.6
Piech: Variance, Bernoulli, Binomial
Thu, Jan 24
Section 2: Random Variables and Expectation
Fri, Jan 27
Lecture 8: Poisson and Approximations
Ross: 4.7-4.10
Piech: Poisson
Week 4
Mon, Jan 29
Lecture 9: Continuous Random Variables
PSet 2 In
Ross: Ch 5.1-5.3, 5.5
Piech: Continuous RVs
Wed, Jan 31
Lecture 10: The Normal Distribution
PSet 3 Out
Thu, Feb 01
Section 3: Discrete and Continuous Random Variables
Fri, Feb 02
Lecture 11: Joint Distributions

Week 5
Mon, Feb 05
Lecture 12: Independent Random Variables
Ross: Ch 6.2-6.3,
Piech: Adding Random Variables
Wed, Feb 07
Lecture 13: Joint RV Statistics
Ross: Ch 6.4-6.5,
Piech: Correlation
Thu, Feb 08
Section 4: Normal Distributions and Joint Distributions
Fri, Feb 09
Lecture 14: Conditional Expectation
PSet 3 In, PSet 4 Out, CS109 Challenge Out
Ross: Ch 7.1-7.2,
Piech: No assigned reading
Week 6
Mon, Feb 12
Lecture 15: General Inference
Ross: No assigned reading,
Piech: Inference
Wed, Feb 14
Lecture 16: Continuous Joint Distributions
Ross: Ch 6.1,
Piech: Continuous Joint Distributions
Thu, Feb 15
Section 5: Conditional Expectation
Fri, Feb 16
Lecture 17: Continuous Joint Distributions II
Ross: Ch 7.3-7.4,
Piech: no assigned reading
Week 7
Mon, Feb 19
Observance of Presidents Day. No lecture.
PSet 4 In
Wed, Feb 21
Lecture 18: Central Limit Theorem
Ross: Ch 8.3,
Piech: Central Limit Theorem
Thu, Feb 22
Section 6: Continuous Joint Distributions, Central Limit Theorem
Fri, Feb 23
Lecture 19: Sampling and Bootstrapping
PSet 5 Out
Ross: No assigned reading,
Piech: Sampling, Bootstrapping
Week 8
Mon, Feb 26
Lecture 20: Parameters and MLE
Ross: No assigned reading,
Piech: MLE, MLE Normal, MLE Mixture
Wed, Feb 28
Lecture 21: Beta
Ross: Ch 5.6.1-5.6.4, 7.5-7.6,
Piech: Beta
Thu, Feb 29
Section 7: Boostrapping and MLE
Fri, Mar 01
Lecture 22: Maximum a Posteriori
Ross: No assigned reading.,
Piech: Maximum a Posteriori
Week 9
Mon, Mar 04
Lecture 23: Naive Bayes
PSet 5 In, PSet 6 Out
Ross: No assigned reading.,
Piech: Machine Learning, Naive Bayes
Wed, Mar 06
Lecture 24: Linear Regression, Gradient Ascent
Ross: No assigned reading.,
Piech: No assigned reading.
Thu, Mar 07
Section 8: Parameter Estimation, Beta, and Naive Bayes
Fri, Mar 08
Lecture 25: Logistic Regression
Ross: No assigned reading., Piech: Logistic Regression
Week 10
Mon, Mar 11
Lecture 26: Deep Learning
Ross: No assigned reading.,
Piech: No assigned reading.
Wed, Mar 13
Lecture 27: Ethics in Probability and AI
Ross: No assigned reading.,
Piech: No assigned reading.
Thu, Mar 14
Section 9: Final Exam Review
Fri, Mar 15
No lecture
PSet 6 In

Note that all lectures and assignment deadlines are subject to change.

Our CS109 website imitates that used by University of Washington's CSE373, Spring 2019.