Practical Data Science 🛠️

EECS 398, Winter 2025 at the University of Michigan

Suraj Rampure
he/him

rampure@umich.edu

Lecture: MW 3-4:30PM, 1670 BBB

The Final Exam is on Monday, April 28th from 10:30AM-12:30PM. Find your assigned room and other logistics here.

We have one more review session this week, on Saturday 4/26 from 1-3PM in 1670 BBB. Attempt the worksheet (linked below) before coming.

Jump to Week 16: Conclusion, Review Announcements 📣

Week 1: Introduction

Wed Jan 8

LEC 1 Introduction, Jupyter Notebooks

SUR Welcome Survey

Thu Jan 9

DISC 1 Environment Setup, Python Basics

Fri Jan 10

EX HW Example Homework (not due!)

Week 2: Python and NumPy

Mon Jan 13

LEC 2 Python Basics

Wed Jan 15

LEC 3 NumPy and Random Simulations

Thu Jan 16

DISC 2 Arrays and Probability

Fri Jan 17

HW 1 Python Fundamentals

Week 3: DataFrames

Mon Jan 20

No Lecture: MLK Day

Wed Jan 22

LEC 4 DataFrame Fundamentals

Thu Jan 23

DISC 3 DataFrames and Querying

Week 4: More Pandas

Mon Jan 27

LEC 5 Aggregation: Grouping and Pivoting

Tue Jan 28

HW 2 Arrays, Probability, and DataFrames

Wed Jan 29

LEC 6 Pivoting, Merging, and Transforming

Thu Jan 30

DIS 4 Grouping, Pivoting, and Merging

Week 5: Real, Messy Data

Mon Feb 3

LEC 7 EDA, Visualization, and Missing Value Imputation

Tue Feb 4

HW 3 Grouping, Pivoting, and Merging

Wed Feb 5

LEC 8 Web Scraping and APIs

Thu Feb 6

DIS 5 Visualization, Imputation, and Web Scraping

Week 6: Text Processing

Mon Feb 10

LEC 9 Regular Expressions

Tue Feb 11

HW 4 EDA and Web Scraping

Wed Feb 12

LEC 10 Text as Data

Thu Feb 13

DIS 6 Regular Expressions and Text Features

Week 7: Introduction to Machine Learning

Mon Feb 17

LEC 11 Introduction to Machine Learning

Tue Feb 18

HW 5 APIs and Regular Expressions

SUR Pre-Midterm Survey

Wed Feb 19

LEC 12 Loss Functions and Simple Linear Regression

Thu Feb 20

DIS 7 Loss Functions and Simple Linear Regression

Week 8: Midterm Exam

Sun Feb 23

REV Exam Review, Day 1 (5-7PM, 1670 BBB and Zoom)

Mon Feb 24

LEC 13 Exam Review, Day 2

Tue Feb 25

EXAM Midterm Exam (7-9PM)

Wed Feb 26

No Lecture: Suraj is at a conference; (Early) Spring Break 🌸

Thu Feb 27

No Discussion: (Early) Spring Break 🌸

Week 9: Spring Break 🌸

Enjoy the time off!

Week 10: Regression using Linear Algebra

Mon Mar 10

LEC 14 Regression using Linear Algebra

Tue Mar 11

HW 6 GPTEECS and Loss Functions

Wed Mar 12

LEC 15 Multiple Linear Regression

Thu Mar 13

DIS 8 Multiple Linear Regression

Week 11: Feature Engineering

Mon Mar 17

LEC 16 Feature Engineering

Tue Mar 18

HW 7 Multiple Linear Regression

Wed Mar 19

LEC 17 Pipelines

Thu Mar 20

DIS 9 Feature Engineering and Pipelines

Week 12: Model Selection

Mon Mar 24

LEC 18 Generalization and Cross-Validation

Wed Mar 26

LEC 19 Regularization

PROJ (Optional) Deadline to Propose Custom Dataset

HW 8 Feature Engineering and Pipelines

Thu Mar 27

DIS 10 Cross-Validation and Regularization

Fri Mar 28

PROJ Final Project Checkpoint

Week 13: Gradient Descent and Classification

Mon Mar 31

LEC 20 Gradient Descent

Wed Apr 2

LEC 21 Introduction to Classification

HW 9 Cross-Validation and Regularization

Thu Apr 3

DIS 11 Gradient Descent and Classification

Week 14: Logistic Regression

Mon Apr 7

LEC 22 Logistic Regression

Wed Apr 9

LEC 23 Logistic Regression, Continued

Thu Apr 10

DIS 12 Logistic Regression

Fri Apr 11

HW 10 Gradient Descent and Classification

Week 15: Unsupervised Learning

Mon Apr 14

No Lecture (see Ed for details)

Wed Apr 16

LEC 24 Clustering (on Zoom!)

Thu Apr 17

DIS 13 Clustering

Fri Apr 18

HW 11 Logistic Regression

Week 16: Conclusion, Review

Mon Apr 21

LEC 25 Computer Vision, Conclusion

Tue Apr 22

PROJ Final Project (no slip days!)

Wed Apr 23

REV Review Session 1 (3-5PM, 1670 BBB)

SUR End-of-Semester Survey and Official Evals

Sat Apr 26

REV Review Session 2 (1-3PM, 1670 BBB)

Week 17: Final Exam

Mon Apr 28

EXAM Final Exam (10:30AM-12:30PM)