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CS 59 — Beginning Programming: Python

Quarter: Fall
Day(s): Fridays
Course Format: On campus
Duration: 6 weeks
Date(s): Sep 30—Nov 11
Time: 7:00—8:50 pm
Drop Deadline: Oct 13
Unit(s): 1 Units
Tuition: $315
Limit: 20
Status: Closed
Please Note: This course has a different schedule than what appears in the print catalogue. The final on-campus session will be on Friday, November 11. There will be no class on October 21.
Fall
On campus
Fridays
7:00—8:50 pm
Date(s)
Sep 30—Nov 11
6 weeks
Drop By
Oct 13
1 Units
Fees
$315
Limit
20
Closed
Please Note: This course has a different schedule than what appears in the print catalogue. The final on-campus session will be on Friday, November 11. There will be no class on October 21.
This hands-on course will provide a gentle, yet rigorous, introduction to programming using Python. Designed for highly motivated students with little or no prior experience in programming, the course will show how to tackle a real-world problem, design an efficient solution, and finally, implement it in Python.

Topics will include Python installation, basic programming concepts, IF conditions, repetitive tasks/ loops, arrays, lists, and functions. This course will be very interactive, and will explore real-world applications. For example, we will design and implement a calculator or simple games such as Hangman and Snake. By the end of the course, students will have acquired direct experience with computer programming in Python, which will help them learn and understand other programming languages.

No programming experience is necessary.

Students must be familiar with computer basics. Students are required to bring a Mac or Windows-based laptop computer to class.

CS 57 and CS 59 will cover similar introductory content. As these courses will be taught by different instructors, their structure and format will vary slightly.

Mohammad Shokoohi-Yekta, Data Scientist, Apple

Mohammad Shokoohi-Yekta has worked on predictive modeling projects for Samsung, Bosch, UCLA, and General Electric and has taught at UC Riverside and Cal Poly Pomona. He received a PhD in computer science from UC Riverside with an emphasis on data mining, machine learning, and time series analysis.

Textbooks for this course:

No required textbooks
DOWNLOAD THE PRELIMINARY SYLLABUS » (subject to change)