Welcome to CS180! - Wingate and Toborg

Introduction

Welcome to the CS180 course repository! We are happy to have you taking this class, and we hope that you're as excited about the up-and-coming field of data science as we are. In this course there are two types of labs: python and data science labs. One average, we will have two labs per week, always due on Saturday night. In addition to the python and data science labs, we will have periodic data literacy quizzes. These quizzes are to test your ability to analyze and interpret infographics, and will challenge your ability to critically think about information presented to you.

Cloning This repository

We highly recommend you clone this repository to gain access to all of the lab specs and starter code. If you have not already, you will need to 1) install git, and 2) configure your SSH key to connect to GitHub.

Once your SSH key is setup, you can clone the repo with the following command: git@github.com:wingated/cs180.git

Data Science Labs

The 12 data science labs will be in the data science folder. There will be 11 different google colab (.ipynb) files. (.ipynb, jupyter notebook, and colab notebook all mean the same thing) On the days that the labs are due, download the .ipynb and create a new google colab notebook. You can watch a tutorial on how to use google colab here. When you finish the exercises on the data science lab, click the "run all" button in the runtime dropdown menu. Make sure that all of the cells work without any errors thrown before turning the assignments in through Learning Suite or Canvas (whatever your professor is using). Once you've verified that your code works, download the completed notebook file and submit just the notebook file.

Class Policies

• Late work will be accepted with a penalty of 20% per day.
• Once your work has been graded, please reach out to the TA during office hours with any questions regarding your grading. They will explain the reasoning for any deducted points. If you feel like their reasoning isn't just, reach out to the professor. This is the same for the python labs, the autograder might not work for your lab, so come in to the TAs office hours to see if it was the autograder, or just your code.
• Do not share your completed code on the internet after the class.
• Please be respectful to the TAs and professor, they're working really hard to make this class a good experience.