elevate-osna-starter

This repository contains starter code for the summer Elevate course SCI 498 - 410: Online Social Network Analysis taught at the Illinois Institute of Technology.

The code in this repository will be copied into your team's repository at the start of class to provide a starting point for your project.

Using this repository

• At the start of the course, students will be divided into project teams. Each team will receive a copy of this starter code in a new repository. E.g.: https://github.com/tapilab/elevate-osna-team1
• Each team member will then clone their team repository to their personal computer to work on their project. E.g.: git clone https://github.com/tapilab/elevate-osna-team1.git
• Tasks will be assigned to each team, who will then check in their code to their team repository.
• Before beginning work each day, run the update.sh command to pull the latest code from the elevate-osna-starter repository to your team's repository.

Contents

• docs: template to create slides for project presentations
• lessons: lesson plan for each day of the course
• osna: Python project code
• tests: unit tests for project code

Prerequisites

Prior to the start of the course, please complete the following steps:

1. Learn Python by completing this online tutorial: https://www.learnpython.org/ (3 hours)
2. Create a GitHub account at https://github.com/
3. Setup git by following https://help.github.com/en/articles/set-up-git (30 minutes)
4. Learn git by completing the Introduction to GitHub tutorial, reading the git handbook, then completing the Managing merge conflicts tutorial (1 hour).
5. Install the Python data science stack from https://www.anaconda.com/distribution/ . We will use Python 3 (30 minutes)
6. Complete the scikit-learn tutorial from https://www.datacamp.com/community/tutorials/machine-learning-python (2 hours)
7. Understand how python packages work by going through the Python Packaging User Guide (you can skip the "Creating Documentation" section). (1 hour)
8. Complete Part 1 of the Flask tutorial, which is the library we will use for making a web demo for your project.