Practical Data Science 🛠️

EECS 398-003, Fall 2024 at the University of Michigan

Interested in taking the course next semester? Read this page.

Suraj Rampure
he/him

rampure@umich.edu

Lecture: TuTh 1:30-3:00PM, 1500 EECS

Jump to the current week

Week 1: Introduction, Python

Tue Aug 27

LEC 1 Introduction

SUR Welcome Survey

Thu Aug 29

LEC 2 Python and Jupyter Notebooks

EX HW Example Homework (not due!)

Fri Aug 30

DISC 1 Introductions, Python Review

Week 2: NumPy and Pandas

Tue Sep 3

LEC 3 NumPy

Thu Sep 5

LEC 4 Simulation, DataFrame Fundamentals

HW 1 Python Fundamentals

Fri Sep 6

DISC 2 Arrays and DataFrames

Week 3: More Pandas

Tue Sep 10

LEC 5 Querying and Grouping

Thu Sep 12

LEC 6 Grouping, Pivoting, and Merging

Fri Sep 13

DIS 3 Grouping, Pivoting, and Merging

HW 2 Arrays and DataFrames

Week 4: Exploratory Data Analysis

Tue Sep 17

LEC 7 EDA, Data Cleaning, and Visualization

Thu Sep 19

LEC 8 More Visualization, Missing Values

HW 3 Grouping, Pivoting, and Merging

Fri Sep 20

DIS 4 Visualization, Missing Values, More Practice

Week 5: Web Scraping and APIs

Tue Sep 24

LEC 9 Web Scraping

Thu Sep 26

LEC 10 APIs, Spreadsheets, and SQL

HW 4 Exploratory Data Analysis and Missing Values

Fri Sep 27

DIS 5 Web Scraping

Week 6: Text Processing

Tue Oct 1

LEC 11 Regular Expressions

Thu Oct 3

LEC 12 Text as Data

HW 5 Web Scraping and APIs

SUR Pre-Midterm Survey

Fri Oct 4

DIS 6 Regular Expressions and Text Features

Week 7: Midterm Exam

Mon Oct 7

REV Midterm Review (6-8PM, FXB 1109, led by TAs)

Tue Oct 8

LEC 13 Midterm Review (during lecture, led by Suraj)

OH Office Hours After Lecture

Wed Oct 9

EXAM Midterm Exam (7-9PM)

Thu Oct 10

No Lecture: (Early) Fall Break 🍁

Fri Oct 11

No Discussion: (Early) Fall Break 🍁

Week 8: Fall Break; Introduction to Modeling

Tue Oct 15

No Lecture: Fall Break 🍁

Thu Oct 17

LEC 14 Introduction to Modeling

HW 6 SQL, Regular Expressions, and GPTEECS

Fri Oct 18

DIS 7 Summary Statistics and the Constant Model

Week 9: Regression

Tue Oct 22

LEC 15 Simple Linear Regression

Thu Oct 24

LEC 16 Regression using Linear Algebra

HW 7 Loss Functions and Linear Algebra

Fri Oct 25

DIS 8 Linear Regression

Week 10: More Regression, Feature Engineering

Tue Oct 29

LEC 17 Multiple Linear Regression and Feature Engineering

Thu Oct 31

LEC 18 Feature Engineering, Continued

Fri Nov 1

DIS 9 Multiple Linear Regression and Feature Engineering

HW 8 Linear Regression

Week 11: Generalization

Tue Nov 5

LEC 19 Pipelines, Generalization

Thu Nov 7

LEC 20 Cross-Validation and Regularization

Fri Nov 8

DIS 10 Generalization, Cross-Validation, Regularization

Week 12: Regularization, Gradient Descent

Mon Nov 11

HW 9 Multiple Linear Regression, Feature Engineering

Tue Nov 12

LEC 21 Regularization, Gradient Descent

Thu Nov 14

LEC 22 Gradient Descent

Fri Nov 15

DIS 11 Gradient Descent and Convexity

Week 13: Classification and Logistic Regression

Tue Nov 19

LEC 23 Introduction to Classification

Thu Nov 21

LEC 24 Logistic Regression

Fri Nov 22

DIS 12 Discussion 12

Week 14: Decision Trees; Thanksgiving

Mon Nov 25

PR HW Portfolio Homework Checkpoint (no slip days!)

Tue Nov 26

LEC 25 Decision Trees and Random Forests

Thu Nov 28

No Lecture: Thanksgiving Break 🦃

Fri Nov 29

No Discussion: Thanksgiving Break 🦃

Week 15: Conclusion

Mon Dec 2

HW 10 Cross-Validation, Regularization, Gradient Descent, and Logistic Regression

Tue Dec 3

LEC 26 Clustering

Thu Dec 5

LEC 27 Conclusion

HW 11 Homework 11

Fri Dec 6

DIS 13 Discussion 13

Sat Dec 7

PR HW Portfolio Homework (no slip days!)

Week 16: Final Exam

Thu Dec 12

EXAM Final Exam (4-6PM)