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CSC 380: Principle of Data Science

Overview

This course introduces students to principles of data science that are necessary for computer scientists to make effective decisions in their professional careers. A number of computer science sub-disciplines now rely on data collection and analysis. For example, computer systems are now complicated enough that comparing the execution performance of two different programs becomes a statistical estimation problem rather than a deterministic computation. This course teaches students the basic principles of how to properly collect and process data sources in order to derive appropriate conclusions from them. The course has three main components: data analysis, machine learning, and a project where students apply the concepts discussed in class to a substantial open-ended problem.

Logistics info

Time and venue: Tuesday and Thursday 5:00-6:15pm at ILC 130

We will be using Piazza to make important announcements and do Q&As. Some general rules:

  • If you have technical questions, try posing your questions as general as possible, to promote discussions among the class.
  • If you have private questions, generally please make a private Piazza post instead of sending an email - This will help facilitate our processings of your requests significantly.

Course staff

  • Instructor: Xinchen Yu
  • Teaching assistants:

Office hours:

  • Xinchen Yu: Tuesday 2:00pm-3:00pm, Gould-Simpson 854

Textbook

There is no single designated textbook for this course. Much of the course materials and assigned readings will be based on the following books:

Other useful resources