CS 051A PO - Intro to CS with Topics in AI

Special Circumstances for Spring 2020

We're going to be tweaking our format some for the remainder of the semester. In particular, we're switching to a more "learner-centered" model where our implicit "contract" between instructors and students is shifting. We want to make our new arrangement very explicit, but we also want you to have a role in coming up with these terms. So here's our proposal, which we're going to commit some time on Monday March 30th to address and receive feedback on.

We the instructional team commit to the following actions:

We will have course notes and assignments posted no less than one week in advance.

Prof. Osborn will expand course notes to the extent that they can serve as useful tools for self-study; in particular we will always include learning outcomes in the form of key questions.

Prof. Osborn will provide study guides for the second mid-semester test and the final exam which comprehensively discuss every topic to be covered on the tests, two weeks in advance of the test.

Prof. Osborn will conduct two class sessions of no more than an hour each starting at the currently specified class time; both will be recorded. These will focus mainly on activities and question-and-answer.

Besides our virtual office hours (at the times listed below), (at least) Prof. Osborn will be available for chat during the entire 9 AM–4 PM Pacific Time period, except when teaching other courses. More details on this later.

We will assign every student to an instructional team member (faculty or possibly TA) and check in weekly in a one-on-one meeting.

We will do the best we can to try out this new arrangement, and improve it in whatever ways it is lacking.

During this period, each of us will need to put in extra effort to get as much benefit as possible out of the course. In particular, we ask you the students to commit to these actions:

Attend (as regularly as possible) the scheduled class sessions.

No later than the beginning of each week's class sessions, read the week's course notes and any other specific readings (e.g., handouts, videos, chapters). This includes attempting the exercises, if any, supplied in the readings.

Come to class sessions prepared to ask questions about the week's readings.

Join the class chat channel and participate during and potentially between lectures.

Meet weekly with your assigned instructional team member.

Continue to conduct homework assignments honestly and diligently. We want to ensure that you are able to complete the homeworks successfully, since the practice they offer is the main way to ensure the course material will stick.

Continue to read and discuss ethical and technical topics in AI, as we have done for the first half of the semester.

Finally, to talk to us if you feel stuck, lost, isolated, or are worried about falling behind. The social occasion of our class will be completely changed, and while we have committed to fixing anything that's broken we need you to tell us when they're broken for you.

This isn't what any of us signed up for, but we are confident that we can still provide a high-quality educational experience centered on your needs as students and people. Thank you for working with us to make it as effective as possible.

Instructors

Lab TAs

Mentor Sessions TBD

Class Information

Schedule

Note: This is a tentative schedule and will likely change

Date	Topic	Reading	Assignment	Misc
1/22	introduction and functions	Ch 1-3	Assignment 1	Lab 1
1/27	turtle, for	Ch. 4-4.7
1/29	turtle, for, booleans	Remainder of Ch. 4; Ch. 5	Assignment 2	Prof. Osborn's office hours delayed 12/30, 10:30–12:30. practice 1
2/3	dot syntax and control flow	Ch. 7		practice 2
2/5	lists	Ch 10-10.6, 10.8	Assignment 3 and starter code	practice 3
2/10	nested sequences	Ch Ch. 9, 10-10.8		practice 4
2/12	functions in depth, sequence operations	Ch 3 (again!), Ch. 6.1-6.7	Assignment 4
2/17	debugging, reading files	Appendix (Debugging), Ch 8, 11-11.4		practice 5
2/19	dictionaries	Ch. 12	Assignment 5	practice 6
2/24	recursion	Ch. 16		practice 7
2/26	contexts, more recursion, sequence comprehensions	Ch. 16, Ch. 10.22	Assignment 6	practice 8
3/2	test 1			sample problems
3/4	machine learning, naive bayes handout		Assignment 7
3/9	intro ai, neural net basics, handout	article (through first column, pg. 36)
3/11	perceptron learning, backpropagation, handout		NN lab
3/16–3/20	spring break
3/23–3/27	spring break
3/30–4/3	classes, "object orientation"	See notes	Assignment 8 (lab video)	video 1, code 1, video 2, code 2
4/6–4/10	matrices, evolutionary algorithms	See notes	Assignment 9 (notes, video)	video 1, video 2 (hires), video 2 (zoom)
4/13–4/17	trees, search		Assignment 10 (reading ahead to week 12 couldn't hurt)	video 1, video 2, search problems
4/20–4/24	informed search, adversarial search	About the final exam	Assignment 11 video	video 1, video 2
4/27–5/1	big-O and runtime analysis, sorting, higher order functions		Performance Analysis Lab video	video 1, video 2
5/4–5/6	exam prep, the shell and system administration, software as a social process		No homework!	video 1,video 2

Department of Computer Science
Pomona College
CS 051A PO—Intro to Computer Science with Topics in AI
Spring 2020

About the final exam

Special Circumstances for Spring 2020

Instructors

Lab TAs

Mentor Sessions TBD

Class Information

Schedule

Department of Computer Science Pomona College CS 051A PO—Intro to Computer Science with Topics in AI Spring 2020

About the final exam

Special Circumstances for Spring 2020

Instructors

Lab TAs

Mentor Sessions TBD

Class Information

Schedule

Department of Computer Science
Pomona College
CS 051A PO—Intro to Computer Science with Topics in AI
Spring 2020