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Python Advanced Topics 

Department: Computer Science and Engineering                      
Instructors: Jordan Campbell
Instructors' Emails:
Prerequisites: Experience with Object oriented programming or Python.
Schedule: Weds - Fri, 9:00AM - 11:00AM PST

Course Description

This course is for students who have some experience in programming already. In this course, projects will be provided that test creativity and adaptability using python. Some topics this course might cover are statistics, machine learning, bioinformatics, materials science, and engineering. In this course, students will not be required to know the particulars of each of the topics covered, but should be able to learn enough about them to handle the python problems effectively. These are all problems that have been covered by graduate students at various levels so the problems should be challenging and force students outside of their boundaries in python. The point of this class is to force students to look up and familiarize themselves with different python libraries and then be able to solve problems using that knowledge. For any review topics, students can additionally complete projects from the Introduction to Python Class. This class will be taught using Python 3.

Note: This course is being designed to be challenging. This course will be light on lectures and heavy on office hours.


Learning Objectives

  • Students should be able to articulate the process of how to use python to solve several real-world problems
  • Students should be able to identify errors in their code and identify efficient fixes
  • Students will be able to take a problem from concept to design to completion with minimal assistance

Course Topics

  • Materials Science using Data Science
  • BioInformatics
  • Machine Learning
  • Data Science
  • Other programming projects (Ex: Drone Programming)

*Courses vary by experience and exposure to content. Instructors have the ability to change content and pace to serve the needs of students. Courses have been modified for online teaching.