TDM 10100

Assignment Schedule

Only the best 10 of 14 projects will count towards your grade.

Topics are subject to change. While this is a rough sketch of the project topics, we may adjust the topics as the semester progresses.

Project 1 - Introduction to Data Analysis using Python and R in Jupyter Lab; Project Templates for Documenting Analysis, Workflow, and Submissions; Teamwork Stucture and Learning Community Overview

Aug 24, 2026

Sep 2, 2026

Syllabus Quiz

Aug 24, 2026

Sep 4, 2026

Academic Integrity Quiz

Aug 24, 2026

Sep 4, 2026

Project 2 - Responsible Usage of Generative AI in Projects; Documenting, Disclosing, and Academic Integrity in Reporting and Publishing; Best Practices for Teamwork and Collaboration on Data-Driven Projects

Aug 31, 2026

Sep 9, 2026

Project 3 - Exploratory Data Analysis and Data Types (categorical data, numerical, strings, geo-spatial/temporal data, indexing)

Sep 7, 2026

Sep 16, 2026

Project 4 - Data Frames in Python and R (comparing and contrasting Pandas, Polars, Tibbles, and Databases)

Sep 14, 2026

Sep 23, 2026

Outside Event 1

Aug 24, 2026

Sep 25, 2026

Project 5 - Introduction to Data Cleaning and Data Wrangling in Python and R

Sep 21, 2026

Sep 30, 2026

Project 6 - Dates, Date-Times, Timestamps, and Libraries in Python and R for Date-Time Conversions

Sep 28, 2026

Oct 7, 2026

Project 7 - Basic Data Modeling and Overview of Statistical Models such as Regression

Oct 5, 2026

Oct 16, 2026

Fall Break

Oct 12, 2026

Oct 13, 2026

Project 8 - Data Grouping, Subsets, Looping through Data using Apply (sapply/tapply/lapply) Functions, and Splitting Data

Oct 9, 2026

Oct 21, 2026

Outside Event 2

Aug 24, 2026

Oct 23, 2026

Project 9 - Introduction to Data Visualization, using Data for Communication, and Data in the Media

Oct 19, 2026

Oct 28, 2026

Project 10 - Visualizing Temporal Data and Early Introduction to Time Series

Oct 26, 2026

Nov 4, 2026

Project 11 - Assessing Data Visualizations (for accuracy, clarity, transparency, ethics, bias, with consistent adherence to best practices for data viz)

Nov 2, 2026

Nov 11, 2026

Project 12 - Maps, Map-making, and Spatial Data in Python and R (e.g., Geopandas, ggplot, Leaflet, Plotly)

Nov 9, 2026

Nov 18, 2026

Outside Event 3

Aug 24, 2026

Nov 20, 2026

Project 13 - Families of Functions Used to Cluster/Combine/Split Data, with an introduction to Lambda functions

Nov 16, 2026

Dec 2, 2026

Project 14 - Overview, Review, Student Feedback to Team, and Summative Group Project Submissions

Nov 23, 2026

Dec 9, 2026

Projects are released on Mondays, and are due 1 week and 2 days later on the following Wednesday, by 11:59pm. There are a few exceptions to these dates; please refer to the schedule. Late work is not accepted. We give partial credit for work you have completed — always submit the work you have completed before the due date. If you do not submit the work you were able to get done, we will not be able to give you credit for the work you were able to complete.

Always double check that the work that you submitted was uploaded properly. See here for more information.

Each week, we will announce in Piazza that a project is officially released. Some projects, or parts of projects may be released in advance of the official release date. Work on projects ahead of time at your own risk. These projects are subject to change until the official release announcement in Piazza.