Due: Friday, 12/6 – NOTE: there will be no regrade window for this milestone. If your group would like written feedback, please fill out this form. General Directions The project video presentation is intended to provide a high-level overview of your project to an audience of your peers (that is, individuals who have a reasonable […]
Author: Dr Kristin Stephens-Martinez, Ph.D.
Project: Final Report
Due: Friday, 12/6 – NOTE: there will be no regrade window for this milestone. If your group would like written feedback, please fill out this form. General Directions The final report is intended to provide a comprehensive account of your collaborative course project in data science. The report should demonstrate your ability to apply the […]
Optional Module: Git and Jupyter Notebooks
This module is 100% optional. It is intended as supplementary material if you plan to use git with your Jupyter Notebooks. Content A. Git Mental Model B. Git with notebooks, how? Recommended Reading Coding habits for data scientists
Project: Prototype
Project Prototype Due: Saturday, November 9th General Directions The prototype deliverable is intended to demonstrate a proof of concept for your final project report. Large multi-week projects are challenging — this deliverable is intended to provide additional structure to ensure you are making substantial progress and are on a path toward success, as well as […]
Project: Proposal
Due: Friday, October 11th (late due Saturday, October 12th) To see an example proposal, you can find it in the class Box folder called Projects. General Directions The purpose of this document is to prepare your team for success in the course project. You should have feedback from your Initial Plan on the different research […]
Module 04: Data Wrangling
Prepare (due Mon 9/23) Content below Canvas quizzes Class engagement – See on the class forum Homework (due Sun 9/29) [LINK] Worked Example [LINK] Content (Slides in the Box folder) 04.A – What is Wrangling Data sources, formats, and importing (26 min.) Common data cleaning problems (16 min.) Read Section 3.4 Handling Missing Data from Python Data Science Handbook 04.B […]
Restart and Run All
Here is a guide on how to submit properly formatted .ipynb files for homework and exams. This is important because a common way to detect bugs that the autograder might find is to first restart the kernel and run everything. Moreover, it is the equivalent of ensuring that you are submitting a polished notebook. Steps […]
