Department of Computer Science
Pomona College
CS 051A PO—Intro to Computer Science with Topics in AI
Spring 2022

Lecture Instructors

Dave Kauchak
office hours: Edmunds 224
M-Th 2:30-3:30pm via Zoom

Alexandra Papoutsaki
office hours: Edmunds 222
TRF 2-4pm (in person and Zoom)

Lab Instructors

Zilong Ye
office hours: T 12:30pm-2pm (Zoom)

Final Exam Mentor Session

Sunday 12-2pm (Sarah) via Zoom

Class Information

Class time: MW 11am-12:15pm (Section 1) and MW 1:15-2:30pm (Section 2)
Class location: Edmunds 114 (Section 1) and Seaver Commons 102 (Section 2)

Lab time: M 7-9:50pm (Sections 1 and 2) and T 7-9:50pm (Sections 3 and 4)
Lab location: Edmunds 219 and 229
Lab TAs: Edmunds 229

Assignment submission: Section 1 and Section 2

Web page:

Textbook: How to Think Like a Computer Scientist: Interactive Edition. Brad Miller and David Ranum, based on original work by Jeffrey Elkner, Allen B. Downey, and Chris Meyers. It is available online for free.

Final exam: Monday, May 9, 9am-12pm (Section 1) and Thursday, May 12 2-5pm (Section 2)

Other information:


Note: This is a tentative schedule and will likely change
1/19introduction (notes)Ch 1-2  
1/24functions (notes)Ch 1-2 Assignment 1Lab 1
1/26turtle, for loops (notes)Ch 4, 5practice 1 (solutions)
1/31booleans, randomCh 7-8 Assignment 2 practice 2 (solutions)
2/2while loopsCh 8 practice 3 (solutions)
2/7sequences (notes)Ch 9-10 Assignment 3 practice 4 (solutions)
2/9boolean variables, aliasing, parameter passing (notes) Ch 6
2/14scoping and debugging (notes) Appendix (Debugging) Assignment 4 practice 5 (solutions)
2/16reading files (notes)Ch 11
2/21dictionaries, recursion (notes)Ch 16Assignment 5 practice 6 (solutions)
2/23more recursion (notes) practice 7 (solutions) practice 8 (solutions)
2/28Midterm 1 Assignment 6 sample problems
partial solutions)
3/2intro AI/NN Basicsarticle (through first column, pg. 36)
3/7preceptron learning, backpropogationNN Lab
3/9machine learning/naïve bayes
3/21ethics presentationsAssignment 7
3/28more classesAssignment 8
3/30search (ppt)
4/4matrices, problem solving via search (ppt)Assignment 9
4/6informed search (ppt)
4/11informed 2 (ppt), adversarial search (ppt)Assignment 10
4/13adversarial search 2 (ppt)
4/18Midterm 2Assignment 11sample problems (solutions)
4/20web pages
4/25exceptions and setsAssignment 12
4/27higher order functions
5/2big O
5/4philosophy (ppt)final sample problems (solutions)