Instructor:
Laney Strange
Through four two-hour workshops and one final sharing session, we’ll learn the basics of data science programming with the Python programming language, and use what we learn to we extract meaning from community-based data to enhance knowledge, inform decision-making, and make more accurate predictions. After participating in the series, students will be able to:
Everything we learn will work towards a group project that leverages community-based data. We’ll work our way up to the project with mini-assignments that we’ll complete during each meeting. The first four meetings are split into two parts: a lecture/discussion where we learn about data science concepts and the programming skills required to bring them to life, followed by a short programming assignment to put everything into practice. We’ll conclude with the fifth meeting, a presentation session for students’ community-based group projects. We’ll also have short readings to do each week so that everyone can participate in informed discussion.
Assignments & Assessment
Students will complete a short assignment during the second half of each meeting.
They will complete and submit a short self-assessment to assess their level of confidence and mastery in materials covered so far. Students will also complete a group project and present their work to one another and to course staff. Students receive honors credit for:
Students are not expected to devote time to the project outside of class; the fourth meeting is specifically designed to set up the parameters of the project and guide students towards data that is meaningful to them. Each group will choose a dataset, identify a question to delve into, and develop Python code to analyze and visualize the data. At the fifth and final meeting, groups will present their work.
Honors Series: Data Science for Social Justice (and New Programmers)
Fall 2020
Meeting Details:
About the Series
This Data Science series is structured to connect technical learning with your interest and expertise in the community-based domains in need of data insights. Our collective experience through 2020 has called out for data analysis and understanding of social justice issues -- through an ongoing global pandemic, its unequal economic impact on women, and the scope of police brutality on black and brown individuals.
Policies
Links
Week
Date
Topics
Links
1
9/24
In-person rotationIntroduction to data science; introduction to programming.
Assignment #1
Python Reference Sheet #1
Self-Assessment #1
Sample solutions: Assignment #1
Slides: Data science + social justice
Slides: Service learning
Reading #1 (for 10/1)
2
10/1
In-person rotation
Ethics in data science. Python variables and lists.
Assignment #2
Sample code
Self-Assessment #2
Ethical Qs: Discussion
Reading #2 + Week 2 Writeup
Sample solution: Assignment #2
3
10/8
In-person rotation
Formulating meaningful questions. Files and graphs in Python.
Assignment #3
Sample code
Police Dataset
Self-Assessment #3
Data Resources
Sample solution: Assignment #3
Reading #3
4
10/15
Final topics and projects
Project Assignment
Project Slides
Self-Assessment #4
Reference: Python Syntax
5
10/29
Project presentations
Self-Assessment #5
Handout: Tech for Good Resources