ECE 20875: Python for Data Science (Spring 2021)

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Course Information

This course introduces Python programming to students through data science problems. Students learn Python concepts as well as introductory data science topics, and use their knowledge of Python to implement data analyses. More detailed information can be found in the course syllabus.

Assignments

• Assignment 1 (Due: 01/29/2021)
• Assignment 2 (Due: 02/05/2021)
• Assignment 3 (Due: 02/12/2021)
• Assignment 4 (Due: 02/19/2021)
• Assignment 5 (Due: 03/05/2021)
• Assignment 6 (Due: 03/12/2021)
• Assignment 7 (Due: 03/26/2021)
• Assignment 8 (Due: 04/02/2021)
• Assignment 9 (Due: 04/16/2021)
• Assignment 10 (Due: 04/23/2021)
• Mini Project (Due: 04/30/2021)
  

Practice Exam

• Practice Exam 1

Lecture Content by Week

1. Week 1 (1/18/2021)
   • Introduction and syllabus
   • Basics of GIT and Python programming, (basics notebook, pdf of notebook)
2. Week 2 (1/25/2021)
   • Python programming (continued) and data structures, (data structures notebook, pdf of notebook, in-class notebook)
   • Python data structures (continued), Histograms
3. Week 3 (2/1/2021)
   • Histograms (continued), Probability
   • Probability (continued)
4. Week 4 (2/8/2021)
   • Higher-order functions, (higher-order functions notebook, pdf of notebook)
   • Higher-order functions (continued), List comprehensions (list comprehension examples, pdf of notebook)
5. Week 5 (2/15/2021)
   • Estimation, sampling, and central limit theorem, (sampling/CLT notebook, pdf of notebook
   • Hypothesis testing and confidence intervals, (hypothesis testing and CI notebook, pdf of notebook)
6. Week 6 (2/22/2021)
   • Hypothesis testing and confidence intervals (continued), Regular expressions
   • Review for midterm (based on student questions), Regular expressions (continued)
   • Midterm (Friday)
7. Week 7 (3/1/2021)
   • (Tuesday lecture for sections 001 and OL1 cancelled to account for midterm on Friday)
   • Regular expressions (continued) (regex and fileIO notebook, pdf of notebook)
8. Week 8 (3/8/2021)
   • File IO, Bash (files for bash demo)
   • Regression
9. Week 9 (3/15/2021)
   • Regression (continued)
   • Reading Day (no lecture)
10. Week 10 (3/22/2021)
    • Regression (continued), (regression notebook, pdf of notebook) (numpy notebook, pdf of notebook)
    • N-grams and natural language processing basic, (nltk tutorial, pdf of notebook)
11. Week 11 (3/29/2021)
    • Objects and classes, (object notebook, pdf of notebook)
    • Clustering and GMMs, (kmeans notebook, pdf of notebook), (GMM notebook, pdf of notebook)
12. Week 12 (4/5/2021)
    • Clustering and GMMs (continued)
    • Cancelled lecture because of exam
13. Week 13 (4/12/2021)
    • Reading day
    • Inheritance (inheritance notebook, pdf of notebook), Iterators and generators (iterators notebook, pdf of notebook)
14. Week 14 (4/19/2021)
    • Iterators and generators (continued), Naive Bayes (naive bayes demo, pdf of notebook)
    • K-nearest neighbors (kNN), Logistic Regression (gradient descent illustration, pdf of notebook)
15. Week 15 (4/26/2021)
    • Introduction to neural networks
    • Introduction to neural networks (continued)