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DS 208

Programming for Data Science

Programming foundations for data science with Python, NumPy, pandas, visualization, and reproducible workflows

Course Overview
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Course Syllabus
Schedule, grading, policies & resources
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Python Foundations 5 modules
intro
Welcome to DS 208
Module intro
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1
Introduction: Python & the Data Science Toolkit
Module 1
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2
Python Fundamentals I: Types, Control Flow & Functions
Module 2
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3
Python Fundamentals II: Data Structures & Files
Module 3
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4
Modular Programming: OOP, Errors & Code Organization
Module 4
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NumPy & pandas 3 modules
5
Scientific Computing with NumPy
Module 5
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6
Data Manipulation with pandas I
Module 6
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7
Data Manipulation with pandas II: Grouping, Merging & Reshaping
Module 7
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Visualization & Data Sources 3 modules
8
Data Visualization with matplotlib & seaborn
Module 8
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9
Working with Data Sources: Files, SQL & APIs
Module 9
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10
Text Processing & Regular Expressions
Module 10
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Workflows & Project 2 modules
11
Reproducible Workflows: Git, Environments & Debugging
Module 11
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12
Integrative Project & Presentations
Module 12
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Weekly Lab Exercises

Practice exercises for each week's lecture (30-60 min each).

1
Week 1 Lab
Welcome Lab: Where You're Starting From
2
Week 2 Lab
Types, Control Flow & Functions
3
Week 3 Lab
Data Structures & Files
4
Week 4 Lab
Classes, Errors & Project Layout
5
Week 5 Lab
Arrays with NumPy
6
Week 6 Lab
pandas I: Loading, Filtering, Selecting
7
Week 7 Lab
pandas II: Grouping, Merging & Reshaping
8
Week 8 Lab
Plotting with matplotlib & seaborn
9
Week 9 Lab
Reading Files, SQL & APIs
10
Week 10 Lab
Regular Expressions in Practice
11
Week 11 Lab
Git, Environments & Debugging
12
Week 12 Lab
Integrative Project Workbench

💡 Tip: Labs run and are submitted right here in the browser — no installs, no Colab. Your submitted code is what's recorded, and re-submitting a lab replaces your previous attempt.