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Class Info
Class Info
Syllabus (PDF or Website)
Ariel's Office Hours are M 3-4, W 1-2 or you can make an appointment outside those times by clicking this link
Text Book - None of the below options are required but they may be good resources for the class.
-- Intro to Python for Computer Science and Data Science (ISBN: 9780135404676)
-- Python for Data Analysis (PDF here)
-- Data Science from Scratch: First Principles with Python
(ISBN-13: 9781491901427)
-- Data Analysis with Open Source Tools
(ISBN-13: 9780596802356)
Assignments
Assignments
Unless otherwise stated in the assignment, due dates will be on Fridays at 5PM. Late assignments will be given a 5% penalty for every 24 hours late they are and then will not be accepted after 1 week has passed.
Engaged Learning 0 - Python Bootcamp - 8/31/23
Project 1 Milestone 1 - 9/1/23
Engaged Learning 1 - Web Scrapping - 9/5/23
Engaged Learning 2 - Data Ownership - 9/7/23
Project 1 Milestone 2 - 9/15/23
Engaged Learning 3 - Word Cloud - 9/12/23
Engaged Learning 4 - Sentiment Analysis - 9/14/23
Engaged Learning 5 - Mean and Variance - 9/21/23
Project 1 Milestone 3 - 9/22/23
Project 1 Presentation - 9/26/23 - 9/28/23
Midterm - 10/3/23
Engaged Learning 6 - Bayes Intro - 10/12/23
Engaged Learning 7 - Multinational Naive Bayes - 10/17/23
Engaged Learning 8 - Gaussian Naive Bayes - 10/24/23
Project 2 - 10/27/23
Midterm - 11/7/23
Engaged Learning 9 - Dimensional Reduction and PCA - 11/9/23
Extra Credit - 11/10/23
Engaged Learning 10 - Proxies in Practice 1 - 11/14/23
Engaged Learning 11 - Proxies in Practice 2- 11/16/23 - Questions
Project 2 Part 2 - 11/17/23
Final Exam - 12/7/23
Project 3 - Due 12/14/23 (11AM)
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