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
0 Sunday, January 5 Welcome to DATA 301!
1 Summarizing Tabular Data Tuesday, January 7

Tabular Data & Variable Summaries

GenAI Activity (Link to Collab)

Activity 1.1 (Link to Collab)
Thursday, January 9 Visualizing and Comparing Categorical Variables Activity 1.2 (Link to Collab)

Lab 1A

Lab 1B

Sunday, January 12 Lab 1A, 1B Due by Midnight
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

Sunday, January 19 Lab 2A, 2B Due by Midnight
3
Measuring Similarity with Distances
Tuesday, January 21 No Class (Classes Follow Monday Schedule)
Thursday, January 23 Distances Between Observations

Lecture Activity 3.1
Activity 3.1 Lab 3
Sunday, January 26 Lab 3 Due by Midnight
4
Dummy Variables & TF-IDF
Tuesday, January 28 Dummy Variables and Column Transformers Activity 4.1
Thursday, January 30 Bag-of-Words and TF-IDF Activity 4.2

Lab 4A

Lab 4B

Sunday, February 2 Lab 4A, 4B Due by Midnight
5
K-Nearest Neighbors & Midterm Exam
Tuesday, February 4

K-Nearest-Neighbors

Lecture 5.1 Activity

Activity 5.1
Thursday, February 6 Spicing up Your Visualizations Activity 5.2 Exam 1 (in-class)
Friday, February 7 No lab this week!
6
Classification & Model Selection
Tuesday, February 11

Introduction to Modeling

Lecture 6.1 Activity

Activity 6.1
Thursday, February 13

Cross-Validation and Grid Search

Lecture 6.2 Activity

Activity 6.2 Lab 6
Sunday, February 16 Lab 6 Due by Midnight
7
Logistic Regression & Unsupervised Learning
Tuesday, February 18

Classification

Lecture 7.1 Activity

Activity 7.1
Thursday, February 20

Logistic Regression

Lecture 7.2 Activity

Activity 7.2 Lab 7
Sunday, February 23 Lab 7 Due by Midnight Project Proposal Due
8
Clustering & Joining Data
Tuesday, February 25

Unsupervised Learning with K-Means

Lecture 8.1 Activity

Activity 8.1
Thursday, February 27

Combining Datasets

Lecture 8.2 Activity

Activity 8.2 Lab 8
Sunday, March 2 Lab 8 Due by Midnight
9
Data Ethics
Tuesday, March 4 Reading Guide: Data Context Data Ethics Part 1 No Lab, Project Work Session
Thursday, March 6 Reading Guide: Model Ethics Data Ethics Part 2 No Lab, Project Work Session Project Guidelines
Sunday, March 9 No lab this week! Practice Exam Review
10
Final Posters & Final Exam
Tuesday, March 11

First Half: Practice Exam Review

Second Half: Poster Work Session

Thursday, March 13 Exam 2 (at beginning of class) Exam 2 (in-class)
Finals Week Saturday, March 15 1:10pm - 2:30pm Poster Presentations