Department of Computer Science
Pomona College
CS 051A PO—Intro to Computer Science with Topics in AI
Spring 2023

Lecture Instructor

Alexandra Papoutsaki
e-mail: Alexandra.last_name@pomona.edu
office hours: Edmunds 222
TR 1:30-4pm and R 11am-12pm (in person and Zoom)

Lab Instructor

Zilong Ye
e-mail: Zilong.last_name@pomona.edu
office hours: M 4-5pm (Edmunds 256) and W 4-5pm (Zoom)

Mentor Sessions

Wesnesday 6-8pm (Caleb and Chau)
Thursday 4:30-6:30pm (Alej)
Friday 1-3pm (Rachel)
Friday 2-4pm (Hasana and Catherine)
Saturday 1-2pm (Caleb and Chau)
Sunday 2-4pm (Sarah)
Sunday 4-6pm (Elshiekh)
Mentor sessions will be held in Edmunds 229

Class Information

Class time: MW 11am-12:15pm (Section 1) and MW 2:45-4:00pm (Section 2)
Class location: Edmunds 114 (Sections 1 and 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: http://www.cs.pomona.edu/classes/cs51a/

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: Wednesday, May 10, 9am-12pm (Section 1) and Wednesday, May 10 2-5pm (Section 2)

Other information:



Schedule

Note: This is a tentative schedule and will likely change
DateTopicReadingAssignmentMisc
1/18introduction (notes)Ch 1-2  
1/23functions (notes)Ch 1-2 Assignment 1Lab 1
1/25turtle, for loops (notes)Ch 4, 5practice 1 (solutions)
1/30booleans, random (notes)Ch 7-8 Assignment 2 practice 2 (solutions) Style Guide
2/1while loops (notes)Ch 8 practice 3 (solutions)
2/6sequences (notes)Ch 9-10 Assignment 3 practice 4 (solutions)
2/8boolean variables, aliasing, parameter passing (notes) Ch 6
2/13scoping and debugging (notes) Appendix (Debugging) Assignment 4 practice 5 (solutions)
2/15reading files (notes)Ch 11
2/20dictionaries (notes)Ch 12Assignment 5 practice 6 (solutions)
2/22recursion (notes)Ch 16 practice 7 (solutions) practice 8 (solutions)
2/27Midterm 1 Assignment 6 sample problems
(
partial solutions)
3/1intro to AI and NNarticle (through first column, pg. 36)
3/6perceptron learning and backpropagationNN Lab
3/8machine learning and naïve bayes
3/13spring break
3/15spring break
3/20ethics presentationsAssignment 7
3/22classesCh. 17
3/27more classesCh. 18Assignment 8
3/29search
4/3problem solving via search and matricesAssignment 9
4/5informed search
4/10informed and adversarial searchAssignment 10
4/12More adversarial search
4/17Midterm 2 (study guide)Assignment 11 sample problems (solutions)
4/19web pages
4/24exceptions and setsCh. 3, 13Assignment 12
4/26higher order functions
5/1big O
5/3Final exam study guide final sample problems (solutions)