Practical Data Science 🛠️
EECS 398, Spring 2025 🌸 at the University of Michigan
Suraj Rampurehe/him
Lecture: TuTh 2-5PM, 1690 BBB
See the study session and office hours schedule here
Jump to Week 2: More Pandas, EDA, and Web Scraping Announcements 📣
Week 1: Python, NumPy, and Pandas
- Tue May 6
LEC 1 Introduction, Jupyter Notebooks
LEC 2 Python Basics
- Thu May 8
LEC 3 NumPy and Random Simulations
LEC 4 DataFrame Fundamentals
- Fri May 9
SUR Welcome Survey
HW 1 Python Fundamentals
Week 2: More Pandas, EDA, and Web Scraping
- Tue May 13
LEC 5 Aggregation: Grouping and Pivoting
LEC 6 Pivoting, Merging, and Transforming
- Wed May 14
HW 2 Arrays and DataFrames
- Thu May 15
LEC 7 EDA, Visualization, and Missing Value Imputation
📝 filled html✍️ annotations
GitHub🎥 recording🧑🤝🧑 Guide: Visualization Tips and Examples📕 Read: LDS 10-11LEC 8 Web Scraping and APIs
- Fri May 16
INT Technical Interview Signups Open
Technical Interview slots are on May 22nd, 23rd, and 27th, all in-person. Practice interview slots are on May 19th (Zoom), May 20th (in-person), and May 21st (Zoom). See the Syllabus for more details.
Week 3: Text Data, Introduction to Machine Learning
- Mon May 19
HW 3 Grouping, Pivoting, and Merging
- Tue May 20
LEC 9 Regular Expressions
LEC 10 Text as Data
- Wed May 21
HW 4 EDA and Web Scraping
- Thu May 22
LEC 11 Introduction to Machine Learning
⏯️ videos📕 Read: LDS 4📕 Read: UCSD 1.1-1.2Watch all of the videos in the playlist above, but especially the first one, as it covers a derivation that is relevant to upcoming homeworks and exams.
LEC 12 Loss Functions and Simple Linear Regression
Week 4: Midterm Exam, Regression with Linear Algebra
- Mon May 26
HW 5 APIs and Regular Expressions
- Tue May 27
LEC 13 Exam Review
- Wed May 28
EXAM Midterm Exam (2-4PM, 1690 BBB, in-person)
Well before the exam, you should start practicing the theoretical problems at the Study Site.
- Thu May 29
LEC 14 Regression using Linear Algebra
LEC 15 Multiple Linear Regression
- Fri May 30
PROJ Final Project Checkpoint
Week 5: Feature Engineering, Generalization
- Mon Jun 2
HW 6 GPTEECS and Loss Functions
- Tue Jun 3
LEC 16 Feature Engineering
LEC 17 Pipelines
- Wed Jun 4
HW 7 Multiple Linear Regression
- Thu Jun 5
LEC 18 Generalization and Cross-Validation
LEC 19 Regularization
Week 6: Classification
- Mon Jun 9
HW 8 Feature Engineering and Pipelines
- Tue Jun 10
LEC 20 Gradient Descent
LEC 21 Introduction to Classification
- Wed Jun 11
HW 9 Cross-Validation and Regularization
- Thu Jun 12
LEC 22 Logistic Regression
LEC 23 Logistic Regression, Continued