COMS BC1016: Introduction to Computational Thinking and Data Science

Spring 2026
Barnard College

Course Details

Instructor: Prof. Eysa Lee

TAs:

Computing Fellows:

Lectures: 10:10am-11:25am, 140 Horace Mann Hall

Labs:

Office Hours:

Course Links

Jupyter Hub: Link (login required)

Class Discussion Forum: EdStem (login required)

Courseworks: Link

Syllabus: Link

Resources

Python Resources:
Data8 Python Reference: https://www.data8.org/fa24/reference/
DataScience Python Library Developer Documentation: https://www.data8.org/datascience/

Data8 Textbook: https://inferentialthinking.com/chapters/intro.html

Lecture Schedule

The schedule below will be updated as the course progresses.

Week Date Topic Lab Assignment
1 1/21 1 - Introduction
[Slides]
No Lab
2 1/26 2 - Introduction to Python [Slides]

(Remote - Snow Day)

1/28 3 - Arrays and Tables [Slides]
Demo: lec03-tables.ipynb
Lab 1 - Expressions (Due 1/30)
3 2/02 4 - Tables and Functions [Slides]
Demo: lec04-tables-and-functions-starter.ipynb
HW 1 - Arrays and Tables (Due 2/11)
2/04 5 - Functions and Charts [Slides]
Demo: lec05-charts-starter.ipynb
Lab 2 - Table Operations
4 2/09 6 - Histograms and Bar Charts [Slides]
Demo: lec06-starter.ipynb
HW 2 - Table Manipulation and Visualzation (Due 2/18)
2/11 7 - Histograms and Functions (continued) [Slides]
Demo: lec07-starter.ipynb
Lab 3 - Data Types and Arrays HW 1 Due
5 2/16 8 - Functions, Groups, Pivots, and Joins [Slides]
Demo: lec08-starter.ipynb
HW 3 - Functions, Tables, and Groups (Due 2/25)
2/18 9 - Review and Conditionals [Slides]
Demo: lec09-starter.ipynb
Lab 4 - Functions and Visualizations HW 2 Due
6 2/23 10 - Conditionals and Iteration [Slides]
Demo: lec10-starter.ipynb

(Remote - Snow Day)

HW 4 - Probability, Simultion, and Estimation (Due 3/9)
2/25 11 - Simulations [Slides]
Demo: lec11-starter.ipynb
Lab 5 - Simulations HW 3 Due
7 3/02 12 - Probability and Sampling [Slides]
Demo: lec12-starter.ipynb

(Optional) Midterm Practice Problems
3/04 13 - Models [Slides]
Demo: lec13-starter.ipynb
No Lab
8 3/09 TA Midterm Review HW 4 Due
3/11 Midterm Exam

(5"x8" index card allowed)

No Lab
- Spring Recess
9 3/23 14 - Hypothesis Testing [Slides]
Demo: lec14-starter.ipynb
3/25 15 - Statistical Significance [Slides]
Demo: lec15-starter.ipynb
Lab 6 - Examining the Therapeutic Touch
10 3/30 16 - AB Testing [Slides]
Demo: lec16-starter.ipynb
HW 5 - Testing Hypotheses
4/01 17 - Confidence Intervals [Slides]
Demo: lec17-starter.ipynb
Lab 7 - A/B Test Final Project Group Declaration
11 4/06 18 - Standard Deviation and Normal Distributions [Slides]
Demo: lec18-starter.ipynb

(Slides contain information on Final Project Proposals)

HW 6 - Confidence Intervals
4/08 19 - Central Limit Theorem [Slides] Lab 8 - Normal Distribution and Variability of Sample Means HW 5 Due 11:59PM
12 4/13 20 - Correlation and Linear Regression [Slides]
Demo: lec20-starter.ipynb
HW 7 - Sample Sizes and Confidence Intervals
4/15 21 - Least Squares, Residuals, and Regression Inference [Slides]
Demo: lec21-starter.ipynb

(Slides contain information on Final Project Proposals and Progress Reports)

Lab 9 - Regression HW 6 Due 11:59PM

Final Project Proposals Due Friday, 4/17
13 4/20 Special Topics: Data Ethics
(Computing Fellows Workshop)
HW 8 - Linear Regression
4/22 Special Topics: Bias in AI
(Guest lecture by Murad Megjhani)
Lab: Final Project Work Time HW 7 Due 11:59PM
14 4/27 22 - Classification Final Project Progress Reports

HW 9 - Regression Inference (Optional, Due 5/4)
4/29 Lab: Final Project Consultations HW 8 Due 11:59PM
15 5/04 HW 9 Due 11:59PM (Optional)

Final Project Report Due Friday 5/8

(No extensions or late days on the final report)