DATA 101, Spring 2018
Kris Shaffer, Ph.D., University of Mary Washington.
Beginning in Week 2, every week (except for midterm presentations in Week 7) will follow the same general schedule:
Note: the weekly lab assignments are begun (and mostly completed) in pairs in class, where you can receive help from your colleagues and from me. However, any work completed outside of class time must be done individually and must be your own work, in accordance with the UMW honor code.
Also note: if you have a laptop that you can bring to class, please do so every day.
The DataCamp courses will take us through the Data Analyst with Python career track at DataCamp. In addition to UMW credit, you will also receive a certificate from DataCamp upon completion of those materials, which you can highlight on your resume, your website, you LinkedIn profile, etc., should you find it beneficial.
You will find information about all DataCamp courses we'll be working on together on our DataCamp course page.
DataCamp course: Introduction to Python for Data Science (complete Chapters 1 & 2 before Thursday's class)
Inspire: Hamilton68 dashboard - tracking Russian influence operations on Twitter
Lab assignment: Getting up and running with Anaconda
DataCamp course: Intermediate Python for Data Science (complete entire course before Tuesday's class)
Inspire: She Giggles, He Gallops - Analyzing gender tropes in film with screen direction from 2,000 scripts, Julia Silge
Lab assignment: Exploratory Data Analysis with the National Immunization Survey (due in Canvas by Tuesday, Jan 30, 11am)
DataCamp course: Python Data Science Toolbox (Part 1)
Inspire: The Follower Factory - Interactive article on purchased followers, likes, and favorites on Twitter
Checkout this Jupyter notebook for example code to reproduce a similar study.
Lab assignment: The Ramen Rater (due in Canvas by Tuesday, Feb 6, 11am)
Self-assessment 1
DataCamp course: Importing Data in Python (Part 1)
Inspire: Face2Face - Synthesizing facial expressions in real time.
Lab assignment: The Million-Song Dataset (due in Canvas by Tuesday, Feb 13, 11am)
DataCamp course: Importing Data in Python (Part 2)
Inspire: Data.gov - free, public datasets.
Lab assignment: Scraping data from the web (due in Canvas by Tuesday, Feb 20, 11am)
DataCamp course: Cleaning Data in Python
Lab assignment: Midterm project (to present next week)
See project details
Self-assessment 2
DataCamp course: pandas Foundations
Lab assignment: Tweet Mining
DataCamp course: pandas Foundations (continued, though you may want to start working ahead on Week 10's DataCamp course)
Lab assignment: Tweet Mining (continued)
DataCamp course: Manipulating DataFrames with pandas (due March 27)
Lab assignment: UFO Sightings (due April 3)
DataCamp course: Merging DataFrames with pandas (due April 3)
Lab assignment: 2016 US Election Analysis (due April 17)
Self-assessment 3 (due April 10)
DataCamp course: Introduction to Data Visualization with Python (CHAPTER 1 ONLY — "Customizing Plots") and Lab assignment: 2016 US Election Analysis, cont. (due April 17) DataCamp course: Statistical Thinking in Python (Part 1, Chapters 2–4) (due April 17) Lab assignment: begin work on your final project. DataCamp course: Statistical Thinking in Python (Part 2) (due April 24) Lab assignment: work on your final project. Due Thursday, May 3, noon. Details here. Self-assessment 4, due Thursday, May 3, noon. There is no in-person final exam.
Statistical Thinking in Python, Part 1 (CHAPTER 1 ONLY — "Graphical Exploratory Data Analysis")Week 13: Statistical Thinking in Python (Part 1)
Week 14: Statistical Thinking in Python (Part 2)
FINAL PROJECT