COMS BC1016: Introduction to Computational Thinking and Data Science

Fall 2026
Barnard College

Course Details

Instructor: Prof. Eysa Lee

TAs:

• Aarya Dharm [email protected]
• Aditya Pendyala [email protected]
• Minh Le [email protected]
• Yeonji Baek [email protected]

Computing Fellows:

• Winnie Wang
• Aarani Narenthiran
• Aayusha Pokharel
• Sonali Sinha

Lectures: Monday/Wednesday 1:10pm-2:25pm, 328 Milbank Hall

Labs:

• Wednesday 2:40-3:55, LL001 Milstein Center (Aarya Dharm and Aarani Narenthiran)
• Wednesday 4:10-5:25, 409 Barnard Hall (Aditya Pendyala and Aayusha Pokharel)
• Thursday 9:40-11, 516 Milstein Center (Minh Le and Winnie Wang)
• Wednesday 4:10-5:25, LL107 R&D Science Center (Yeonji Baek and Sonali Sinha)

Office Hours:

• Monday/Wednesday 4:00pm-5:00pm, Milstein Center 512 (Prof. Eysa Lee)
• Monday 3pm-4pm, Milstein Center 502 (Yeonji Baek)
• Tuesday 9am-10am, Milstein Center 502 (Minh Le)
• Wednesday 4:00pm-5:00pm, Milstein Center 502 (Aarya Dharm)
• Wednesday 2:30pm-3:30pm, Milstein Center 502 (Aditya Pendyala)
• Monday/Wednesday 1pm-2pm, Milbank Hall 226E (Prof. Murad Megjhani)

Course Links

Jupyter Hub: https://bccoms-1016-lee-20263.hub.cuit.columbia.edu/ (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/

Lecture Schedule

The schedule below will be updated as the course progresses.

Week	Date	Topic	Lab	Homeworks	Due Dates
1	9/9	1 - Introduction [Slides - Updated 9/10]	No Lab
2	9/14	2 - Intro to Python [Slides]
	9/16	3 - Tables [Slides] [Demo Files - Updated to include completed]	Lab 1 - Expressions
3	9/21	4 - Data Visualizations [Slides] [Demo Files - Updated with Completed File]		HW 1 - Arrays and Tables
	9/23	5 - Histograms [Slides] [Demo Files - Updated with Class Version]	Lab 2 - Table Operations
4	9/28	6 - Histograms and Functions [Slides] [Demo Files - Updated with Class Version]		HW 2 - Table Manipulation and Visualization
	9/30	7 - Groups and Pivots [Slides] [Demo Files - Updated with Class Version]	Lab 3 - Data Types and Arrays		HW 1 Due
5	10/5	8 - Joining Tables and Booleans [Slides] [Demo Files - Updated with Class Version]		HW 3 - Functions, Tables, and Groups
	10/7	9 - Conditionals and Iteration [Slides] [Demo Files - Updated with Class Demo]	Lab 4 - Functions and Visualizations		HW 2 Due
6	10/12	10 - Sampling [Slides] [Demo Files - Updated with Class Demo]
	10/14	11 - Models [Slides] [Demo Files - Updated with Class Version]	Lab 5 - Simulations	HW 4 - Probability, Simulation, and Estimation	HW 3 Due
7	10/19	12 - Models and Empirical Simulations
	10/21	Midterm Review	No Lab
8	10/26	Midterm
	10/28	Special Topics	No Lab		HW 4 Due
9	11/2	Academic Holiday
	11/4	13 - Hypothesis Testing	Lab 6 - Examining the Therapeutic Touch
	11/6	-			Final Project Group Declaration Due
10	11/9	14 - Statistical Significance and AB Testing		HW 5 - Testing Hypotheses
	11/11	15 - Confidence Intervals	Lab 7 - A/B Test	HW 6 - Confidence Intervals
11	11/16	16 - The Normal Distribution
	11/18	17 - Sample Means	Lab 8 - Normal Distribution and Variability of Sample Means	HW 7 - Sample Sizes and Confidence Intervals	HW 5 Due
	11/20	-			Final Project Proposals Due
12	11/23	Special Topics			HW 6 Due
	11/25	Holiday	No Lab
13	11/30	18 - Correlation and Linear Regression		HW 8 - Linear Regression
	12/2	19 - Least Squares, Residuals, and Regression Inference	Lab 9 - Regression		HW 7 Due
14	12/7	20 - Classification		HW 9 - Classification	Final Project Progress Reports Due
	12/9	21 - Classification	Lab: Final Project Consultations		HW 8 Due
15	12/14	22 - Wrap-Up			HW 9 Due
-	12/18	-			Final Project Report Due (No extensions or late days on the final report)