Introduction to Data Science (in Python)

This page contains an outline of the topics, content, and assignments for the quarter. Note that this schedule will be updated as the quarter progresses, with all changes documented here.

Week Date Required Reading Lecture Slides Lab Activity Weekly Assignment Exams & Project
1 Summarizing Tabular Data Tuesday, January 6

Welcome to DATA 301!

Tabular Data & Variable Summaries

GenAI Activity (Link to Collab)

Activity 1.1 (Link to Collab)
Thursday, January 8 Visualizing and Comparing Categorical Variables Activity 1.2 (Link to Collab)

Lab 1A

Lab 1B

Monday, January 12 Lab 1A, 1B Due by 5pm
2 Summarizing & Visualizing Quantitative Data

Tuesday, January 14

(Dr. T’s b-day)

Visualizing and Summarizing Quantitative Variables

Lecture 2.1 Activity

Activity 2.1 (Link to Collab)
Thursday, January 16

Multivariate Summaries

Lecture 2.2 Activity

Activity 2.2

Lab 2A

Lab 2B

Monday, January 19 Lab 2A, 2B Due by 5pm
3
Measuring Similarity with Distances
Tuesday, January 20 No Class (Classes Follow Monday Schedule)
Thursday, January 22 Distances Between Observations

Lecture Activity 3.1
Activity 3.1 Lab 3
Monday, January 26 Lab 3 Due by 5pm
4
Dummy Variables & TF-IDF
Tuesday, January 27 Dummy Variables and Column Transformers Activity 4.1
Thursday, January 29 Bag-of-Words and TF-IDF Activity 4.2

Lab 4A

Lab 4B

Monday, February 2 Lab 4A, 4B Due by 5pm
5
K-Nearest Neighbors & Midterm Exam
Tuesday, February 3

K-Nearest-Neighbors

Lecture 5.1 Activity

Activity 5.1
Thursday, February 5 Spicing up Your Visualizations Activity 5.2 No lab this week! Exam 1 (in-class)
6
Classification & Model Selection
Tuesday, February 10

Introduction to Modeling

Lecture 6.1 Activity

Activity 6.1
Thursday, February 12

Cross-Validation and Grid Search

Lecture 6.2 Activity

Activity 6.2 Lab 6
Monday, February 16 Lab 6 Due by 5pm
7
Logistic Regression & Unsupervised Learning
Tuesday, February 17

Classification

Lecture 7.1 Activity

Activity 7.1
Thursday, February 19

Logistic Regression

Lecture 7.2 Activity

Activity 7.2 Lab 7
Monday, February 23 Lab 7 Due by 5pm Project Proposal Due
8
Clustering & Joining Data
Tuesday, February 24

Unsupervised Learning with K-Means

Lecture 8.1 Activity

Activity 8.1
Thursday, February 26

Combining Datasets

Lecture 8.2 Activity

Activity 8.2 Lab 8
Monday, March 2 Lab 8 Due by 5pm
9
Data Ethics
Tuesday, March 3 Reading Guide: Data Context Data Ethics Part 1 No Lab, Project Work Session
Thursday, March 5 Reading Guide: Model Ethics Data Ethics Part 2 No Lab, Project Work Session Project Guidelines
Monday, March 9 No lab this week! Practice Exam Review
10
Final Posters & Final Exam
Tuesday, March 10

First Half: Practice Exam Review

Second Half: Poster Work Session

Practice Exam Solutions
Thursday, March 12 Exam 2 (at beginning of class) Exam 2 (in-class)
Finals Week Saturday, March 14 1:10pm - 2:30pm Poster Presentations