Data 198: Introduction to Real World Data Science

UC Berkeley, Fall 2026

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Week 7 Announcements

Oct 26 · 0 min read

Lab 06: Unsupervised Learning is released and due Monday, November 2, at 5:00 PM.

Week 1

Sep 14: 1 Welcome, Icebreakers, Data Science Lifecycle, Course Expectations 🧊; Lecture Slides

Week 2

Sep 21: 2 Introduction to Pandas, Data Cleaning and Manipulation, Introductory EDA; Lecture Slides; Textbook Pandas, Data Cleaning, and Introductory EDA; Lab Lab 01: Pandas, Data Cleaning, and EDA (Due 9/28 at 5:00 PM); Lightning Talk Recruiting - Wayland La

Week 3

Sep 28: 3 Data Visualization, Feature Engineering and Selection; Lecture Slides; Textbook Data Visualization, Feature Engineering, and Selection; Lab Lab 02: Data Visualization, Feature Engineering, and Selection (Due 10/5 at 5:00 PM); Lightning Talk Navigating Berkeley - Collin

Week 4

Oct 5: 4 Introduction to Machine Learning, Loss Functions, Gradient Descent, Bias/Variance; Lecture Slides; Textbook Introduction to Machine Learning; Lab Lab 03: Introduction to Machine Learning (Due 10/12 at 5:00 PM); Checkpoint Project Checkpoint 1 (Due 10/5 at 11:59 PM) · Submit PC1

Week 5

Oct 12: 5 Supervised Learning Models; Lecture Slides; Textbook Supervised Learning: Linear Regression, Logistic Regression, and Decision Trees; Lab Lab 04: Supervised Learning (Due 10/19 at 5:00 PM); Checkpoint Project Checkpoint 2 (Due 10/19 at 11:59 PM) · Submit PC2

Week 6

Oct 19: 6 Model Evaluation; Lecture Slides; Textbook Model Evaluation; Lab Lab 05: Model Evaluation (Due 10/26 at 5:00 PM)

Week 7

Oct 26: 7 Unsupervised Learning; Lecture Slides; Textbook Unsupervised Learning: K-Means, Dimensionality Reduction, and PCA; Lab Lab 06: Unsupervised Learning (Due 11/2 at 5:00 PM); Checkpoint Project Checkpoint 3 (Due 11/02 at 11:59 PM) · Submit PC3

Week 8

Nov 2: 9 ML and Modeling IV

Week 9

Nov 9: 10 ML & Modeling V

Week 10

Nov 16: 11 Symposium I

Week 11

Nov 23: 12 No Lecture (Thanksgiving Break)

Week 12

Nov 30: 13 Symposium II