This course introduces students to the principles and tools of data science. This course will provide a foundation for properly collecting and analyzing data to draw insights and to answer data-driven questions. The course has three main components: applied probability and statistics, data analysis and visualization, and machine learning. In the first component students will be introduced to the fundamentals of applied probability and statistics, learn how to interpret randomness, and how to assess predictive uncertainty. Students will then learn how to handle, clean, process, and visualize data of varying types using Python. Finally, the students will be introduced to the basics of machine learning to build predictive models. Students will further learn how to assess model validity and how to interpret the quality of model predictions.
Instructor: Jason Pacheco, GS 724, Email: email@example.com TA: Enfa Rose George: firstname.lastname@example.org TA: Saiful Islam Salim email@example.com Office Hours: Enfa, Mondays, 10:30 - 11:30, Gould-Simpson Rm 934, Desk #6 (Hybrid) Saiful, Tuesdays, 10:00 - 11:00, Gould-Simpson Rm 942 (Hybrid) Jason, Wednesdays, 10:00 - 11:00, (Zoom) D2L: https://d2l.arizona.edu/d2l/home/1072117 Piazza: https://piazza.com/arizona/fall2021/csc380 Instructor Homepage: http://www.pachecoj.com
|8/24||Introduction + Course Overview (slides)||
What is Data Science?
Robinson, E. and Nolis, J.
|8/26||Random Events and Probability (slides)||WL : CH1|
|8/31||Discrete Probability Distributions + numpy.random (slides)||WL : CH2||HW1 (Due: 9/9)|
|9/2||Continuous Probability, PDFs (slides)|
|9/7||Moments and Dependence (slides)||WL : CH3|
|9/9||Statistics and Estimation (slides)||WL : Sec. 9.1 - 9.7||HW2 (Due: 9/16)|
|9/14||Bayesian Statistics (slides)||
WL : Sec. 6.3, Sec. 10.2, Sec. 11.1-11.4
Scribbr: A Step-by-step Guide to Statistical Analysis
||HW3 (Due: 9/23)|
|9/21||Exploratory Data Analysis|
|9/28||Introduction to Data Visualization|
|10/5||Review + Midterm|
|11/11||Veteran's Day / NO CLASS|
|11/25||Thanksgiving Recess / NO CLASS|