All assignments for the class will be listed here.
FiveFour homework assignments, each with 2-3 programming problems.
- A midterm “tutorial” assignment where you will write up a short tutorial on a data science subject.
- A final project, done in groups, on a data science problem of your choosing.
All assignments will be released by 11:59 PM ET on the release date, and are due at 11:59pm ET (midnight) on the due date.
You are expected to know and adhere to the course policies, which govern late days, submissions, and collaboration.
We may occasionally modify assignment dates and scopes. If we do that, there will be an announcement in-class and an update here.
|Assignment||Release date||Due date||Notebooks||Colab|
|Homework 1||Feb 9||Feb 23||hw1_get_started
|Homework 2||Feb 28||Mar 16||hw2_relational_data
|Tutorial||Mar 15||Mar 26 (proposal)
April 8 (submission)
April 15 (evaluations)
|Homework 3||Mar 16||April 1||hw3_linear
|Project||Apr 12||Apr 22 (proposal)
May 14 (video)
May 17 (report)
|Homework 4||April 15||April 29||hw4_bayes
|hw4_bayes hw4_unsupervised hw4_cf|
TAs may not be available to answer questions about an assignment after its due date; keep this in mind before deciding to use your grace days.
Homeworks are distributed Jupyter notebooks (we will also link Colab notebooks shortly), and are submitted for grading using code in the notebook as well (we will post a description of this proceess along with the first homework). To submit the assignments, sign up for an account (with your andrew email) on the autograding site https://mugrade.datasciencecourse.org
In lieu of a midterm exam, students will write a tutorial on a data science topic of their choosing. More information will be posted here when the assignment is released. Again, no late days are permitted on the tutorial, and failure to submit by the deadline will result in zero points.
The final project of the course will consist of a large data science project done in teams of 2-3 people (single person or four person teams will be considered on an individual basis). The final report for this project will be a Jupyter notebook detailing the data collection, analysis, and results. In addition to the report, teams will also prepare a short video for showing during a final project video session.
No late days are permitted on the final project, and failure to submit by the deadline will result in zero points.