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DATA 301 - Home
  • Unsyllabus

About this course

  • Course Schedule
  • How to do well in this course
  • Course Syllabus (Official)

Labs

  • GitHub Classroom Links

Getting Started

  • Frequently Asked Questions
  • Before the term starts
  • Before the first class
  • After the first class
  • In the first week
  • Data Science Tech Stack
    • macOS Setup Instructions
    • Windows Setup Instructions

Weekly Content

  • Week 1
    • Videos
    • Class 1A - Introduction to DATA 301
    • Class 1B: Data Science Tech Stack
    • Class 1C: GitHub and Accepting Labs
    • Lab 1
      • Task 1 - Set up your computer
      • Task 2 - Learning Markdown (Part 1)
      • Task 3 - Learning Markdown (Part 2)
    • Learning Log 1
  • Week 2
    • Class 2A. Introduction to the File System, and the Terminal (Command line)
    • Class 2B. Introduction to the Terminal (Command line) and Git
    • Class 2C: Customizing your Computer, and introduction to the Course Project
    • Lab 2
      • Task 1 - Practice Terminal Commands
      • Task 2 - BashCrawl
    • Learning Log 2
  • Week 3
    • Videos
    • Learning Log 3
    • A. Introduction to Python
    • B. Data 301 Project
    • C. More Python
    • Lab 3
      • Task 1 - Introduction to Python
      • Task 2: Python Fundamentals II
      • Task 3 - Dictionaries, Lists and data manipulation
      • Task 4 - Pandas
      • Task 5 - Dictionaries, Lists and data manipulation
  • Week 4
    • Videos
    • Class 4A: Introduction to Programming in Python
    • Class 4C: Introduction to Programming in Python II
    • Lab 4
      • Task 1 - Introduction to Python
      • Task 2: Python Fundamentals II
      • Task 3 - Dictionaries, Lists and data manipulation
      • Task 4 - Pandas
      • Task 5 - Dictionaries, Lists and data manipulation
    • Test 1
    • Learning Log 4
  • Week 5
    • Videos
    • A. Introduction to Pandas
    • B. More Pandas
    • Notes on Missing Data
    • Lab 5
      • Task 1
      • Task 2
      • Task 3
      • Task 4
    • Bonus Test 1
    • Learning Log 5
  • Week 6
    • Videos
    • A. Introduction to Data Visualization
    • B. Seaborn Tutorial
    • C. More Pandas
    • Lab 6
      • Task 1
      • Task 2
      • Task 3
    • Test 2
    • Learning Log 6
    • Mid-course Feedback (Anonymous)
  • Week 7 (Break!)
  • Week 8
    • Videos
    • Lab 7
      • Task 1
      • Task 2
      • Task 3
      • Task 4
    • Practicing Exploratory Data Analysis
    • A. Practicing EDA
    • B. Principles of Effective Data Visualization
    • C. Git and Version Control
    • Bonus Test 2
    • Learning Log 7
  • Week 9
    • Lab 8
      • Task 1
      • Task 2
      • Task 3
      • Task 4
      • Task 5
    • A. Programming in Python I
    • C. Programming in Python II
    • Test 3
    • Learning Log 9
  • Week 10
  • Week 11
    • Videos
    • Lab 9
      • Task 1
      • Task 2
      • Task 3
      • Task 4
      • Task 5
    • A. Tableau Dashboards
    • Bonus Test 3
    • Learning Log 11
  • Week 12
    • Week 12 - Microsoft Excel
    • Lab 10
      • Task 1
      • Task 2
      • Task 3
      • Task 4
    • Test 4
    • Learning Log 12

Course Feedback

  • Anonymous Feedback Form

Project

  • DATA 301 Project
    • Milestone 1 - Form Team and Find Dataset
    • Milestone 2 - Load your dataset, explain it, and define your research questions
    • Milestone 3 - Exploratory Data Analysis (EDA)
    • Milestone 4 - Visualizations, Analysis, and Pipeline.
    • Milestone 5 - Present your Dashboard!
    • Milestone 6 - Address Feedback and Refine project

Extra Practice with Python

  • Practice Exercises
    • 1. Strings
    • 2. Numbers
    • 3. Conditionals
    • 4. Lists
    • 5. Dictionaries
    • 6. Loops
    • 7. Functions
    • 8. File input/output
    • 9. Classes
    • 10. Exceptions
    • 11. Debugging

Tools

  • Ed Discussion
  • Repository
  • Suggest edit
  • Open issue
  • .md

GitHub Classroom Links

Contents

  • Labs
  • Project
  • OPTIONAL Labs

GitHub Classroom Links#

We are using GitHub Classroom to provision the labs and project. You will first need to accept the lab so the “starter code” is copied to your repository. Click links below to accept the labs, I expect they will be released by Monday morning of each week.

Labs#

Lab

Due Date

Link to Accept

Lab 1 - Course Setup Markdown, Terminal, GitHub

Wednesday January 18 at 18:00

Accept Lab

Lab 2 - BashCrawl

Wednesday January 25 at 18:00

Accept Lab

Lab 3 - Git Tutorial

Wednesday February 1 at 18:00

Accept Lab

Lab 4 - Introduction to Python and Pandas

Wednesday February 8 at 18:00

Accept Lab

Lab 5 - Pandas and EDA

Wednesday February 15 at 18:00

Accept Lab

Lab 6 - Data Visualization

Wednesday February 22 at 18:00

Accept Lab

Lab 7 - Data Analysis

Wednesday March 8 at 18:00

Accept Lab

Lab 8 - Python Functions

Wednesday March 15 at 18:00

Accept Lab

Lab 9 - Tableau

Wednesday March 22 at 18:00

Accept Lab

Lab 10 - Excel

Wednesday March 29 at 18:00

Accept Lab

Project#

Project Milestone

Due Date

Link to Accept

Template Project

N/A

Accept Project

Milestone 1

Thursday Feb 2, 2023 at 18:00

None (continue using repo)

Milestone 2

Thursday Feb 16, 2023 at 18:00

None (continue using repo)

Milestone 3

Thursday Mar 2, 2023 at 18:00

None (continue using repo)

Milestone 4

Thursday Mar 23, 2023 at 18:00

None (continue using repo)

Milestone 5

Thursday Apr 6, 2023 at 18:00

None (continue using repo)

Milestone 6

Thursday Apr 11, 2023 at 18:00

None (continue using repo)

Once you click the link, a repository will automatically be created for you with some starter code. You can now work on the repo, make commits, and push them to GitHub as you please.

OPTIONAL Labs#

These are somewhat more advanced topics that are no longer part of DATA 301, the labs are here if you’d like to explore them further.

Lab

Due Date

Link to Accept

Solutions

Lab 11 - SQL I

N/A

Accept Lab[]](https://classroom.github.com/a/)

In the repo

Lab 12 - SQL II

N/A

Accept Lab[]](https://classroom.github.com/a/)

In the repo

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Contents
  • Labs
  • Project
  • OPTIONAL Labs

By Firas Moosvi

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