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CS 59 — Beginning Programming: Python

Quarter: Fall
Day(s): Fridays
Course Format: On-campus course
Duration: 6 weeks
Date(s): Oct 6—Nov 10
Time: 7:00—8:50 pm
Drop Deadline: Oct 19
Unit: 1
Tuition: $405
Instructor(s): Mohammad Shokoohi-Yekta
Limit: 20
Status: Closed
Please Note: This course has a different schedule than what appears in the print catalogue. The course will meet from October 6 to November 10.
Fall
On-campus course
Fridays
7:00—8:50 pm
Date(s)
Oct 6—Nov 10
6 weeks
Drop By
Oct 19
1 Unit
Fees
$405
Instructor(s):
Mohammad Shokoohi-Yekta
Limit
20
Closed
Please Note: This course has a different schedule than what appears in the print catalogue. The course will meet from October 6 to November 10.
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.

Prerequisite: No programming experience is necessary. Students must be familiar with computer basics. Students are required to bring a fully charged Mac or Windows-based laptop computer to class.

This course will cover similar introductory content to CS 57 and CS 46 W. 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 works on the Antenna Design team at Apple. Prior to joining Apple, he worked for Samsung, Bosch, General Electric, and UCLA, and taught at UC Riverside and Cal Poly Pomona. He received a PhD in computer science from UC Riverside. He is the author of the book Applications of Mining Massive Time Series Data.

Textbooks for this course:

There are no required textbooks; however, some fee-based online readings may be assigned.
DOWNLOAD THE PRELIMINARY SYLLABUS » (subject to change)