CSS 1 Syllabus: Fall 2023#

Course Overview#

This course will teach you how to approach research questions in social science from a computational perspective. This includes thinking computationally, as well as developing the skillset to implement the ideas and solutions you think of. Specifically, you will learn to program in Python.

Key Learning Outcomes#

By the end of this course, you should be able to:

  • Design, implement, and execute basic Python programs in Jupyter notebooks.

  • Read, interpret, and debug Python code.

  • Manipulate data in Python and make calculations and visualizations with that data.

Course Logistics#

Teaching Team:#

  • Sean Trott: Assistant Teaching Professor in Cognitive Science and CSS.

  • TA: Anjani Bhamidipati

Teaching Team OH#

Who?

When?

Where?

Sean Trott

Wednesday 10-11

CSB 259

Anjani Bhamidipati

Wednesday 1:30-2:30 (Zoom)

TBD

When/Where?:#

  • Lecture: MW 9-10 AM, CSB 002 (also podcasted).

  • Coding Lab Sections

    • MW 11-12 (Center 222).

    • MW 12-1 (Pepper Canyon Hall 121).

Grading#

Grade Components#

Your grade will be determined by three kinds of assessments: coding labs, problem sets, and a final project.

Grade Component

Percentage of Final Grade

8 Coding Labs

50% (6.25% each)

4 Problem Sets

32% (8% each)

1 Final Project

18%

Letter Grades#

If you’re taking the course for a letter grade, your grade will be determined according to the scale below.

Note that the number on the right-hand side of the range is not included in that range: that is, an “A-” ranges from 90% all the way to 91.99% but does not include 93% (93% is an A).

Percentage

Letter Grade

97%+

A+

93-97%

A

90-93%

A-

87-90%

B+

83-87%

B

80-83%

B-

77-80%

C+

73-77%

C

70-73%

C-

60-69%

D

<60%

F

Extra Credit#

You will have at least one opportunity to earn 2% extra credit by filling out a survey about your:

  • Experience/comfort with programming.

  • Major (or intended major).

  • Other background information.

On Rounding#

Note that my policy is not to round up grades for two reasons:

  1. If rounding is applied selectively (i.e., only to students who ask), it is unfair to other students.

  2. If rounding is applied across the board, it simply redefines the boundary between two letter grades (e.g., making an 89% the cut-off for an A-).

Late submissions#

Students may submit late assignments up to 48 hours after the submission deadline, for 75% credit of what you would’ve received (i.e., if you scored 90%, you’d get 67.5% with the late penalty).

Questions, feedback, and communication#

Instructors can be reached in the following ways:

  • Office hours.

  • Public question on Piazza.

  • Private message over Piazza.

  • Email.

The course Piazza can be found here: https://piazza.com/ucsd/fall2023/css1

Note that in general, we prefer communication over Piazza as opposed to email.

Other Information#

Academic Integrity#

Please turn in your own work. While you are encouraged to work together on some assignments (e.g., on labs), you should still understand the code you’ve submitted. Problem sets and final project should be completed independently.

Please review academic integrity policies here. Cheating and plagiarism are unfair to other students and ultimately to yourself, and you will be penalized if caught. Instead, if you’re struggling with something, please come to office hours and ask for help!

Class Conduct#

All of us (instructors + students) should treat others with respect and follow the UC San Diego Principles of Community. This class should be a welcoming and inclusive environment for everyone, regardless of gender, gender identity and expression, sexual orientation, physical appearance, disability, race, or ethnicity.

Please be considerate and respectful of your fellow classmates (and instructors), refrain from discriminatory language and harassment, and interact with good faith.

Schedule of Course Content#

See the schedule here.