CSCI1090

Data Science Principles

This course will provide students with an overview of the field of data science and its responsible uses, along with an introduction to programming in Python from a data science perspective. An emphasis will be placed on solving problems and applying data science principles to real-world datasets. Topics will include variables, data structures, control structures, functions, exploratory data analysis, data manipulation, and data visualization, as well as an introduction to descriptive statistics and machine learning. Students will engage through readings and in class discussions on topics such as applications of data science for the common good, privacy in a digitally connected world, issues of representation and omission in data collection, biases inherent in constructing information infrastructures and classification schemes, and the impact of algorithmic decision-making.

Course overview

Department
Computer Science
School
MCAS
Credits
3

Requirements fulfilled

No source-backed degree requirement is attached to this course yet.

Official evaluation summary

3.85 / 5

Based on 225 aggregate responses from BC Avalanche/Blue evaluations.

Data freshness

Course and evaluation data last updated 2026-07-23. Source details and limitations are documented in Data Sources and Methodology.

Instructors

Sections

  • Section 01
    Fall 2026 · Mira Yun · 245 Beacon Street Room 230 TuTh 01:30PM-02:45PM · Offered
  • Section 02
    Fall 2026 · Mira Yun · 245 Beacon Street Room 230 TuTh 03:00PM-04:15PM · Offered
  • Section 03
    Fall 2026 · Alexander Creiner · Campion Hall 236 MWF 01:00PM-01:50PM · Offered