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

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The specifications for the Portfolio Homework have been released; take a look here!

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, Continued

Fri Nov 15

DIS 11 Discussion 11

Week 13: Logistic Regression

Tue Nov 19

LEC 23 Logistic Regression

Thu Nov 21

LEC 24 Logistic Regression, Continued

HW 10 Homework 10

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

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)