1. 1. Guten Tag!
  2. 2. Getting Started
    1. 2.1. Tools and Resources
    2. 2.2. Setting Up Our Environment
    3. 2.3. Running Python Locally
    4. 2.4. Jupyter Notebooks
  3. 3. Lectures
    1. 3.1. ✅ Installing Python
    2. 3.2. ✅ Thinking Programmatically
    3. 3.3. ✅ Basic Data Types
    4. 3.4. ✅ Conditionals
    5. 3.5. ✅ Lists
    6. 3.6. ✅ Dicts
    7. 3.7. ✅ Loops
    8. 3.8. ✅ Loops Practice
    9. 3.9. ✅ Modules & Functions
    10. 3.10. ✅ Classes
    11. 3.11. ✅ Classes Review
    12. 3.12. ✅ Classes (Cont'd)
    13. 3.13. ✅ Intro to Data Science
    14. 3.14. ✅ Pandas
    15. 3.15. ✅ Data Analysis I
    16. 3.16. Data Analysis II
    17. 3.17. Data Viz
    18. 3.18. Independent Study
    19. 3.19. Independent Study
    20. 3.20. 🎉 Fin.
  4. 4. Topics
    1. 4.1. Essential Terminology
    2. 4.2. Basic Data Types
    3. 4.3. Conditionals
    4. 4.4. Lists
    5. 4.5. Dicts
    6. 4.6. Loops
    7. 4.7. Modules & Packages
    8. 4.8. Functions
    9. 4.9. List Comprehensions
    10. 4.10. Classes
    11. 4.11. Data Science
    12. 4.12. Intro to Pandas Objects
    13. 4.13. Exploratory Data Analysis w. 🐼
    14. 4.14. Pandas Analysis II
    15. 4.15. Data Visualization
    16. 4.16. Course Review
    17. 4.17. Python Project Ideas
  5. 5. Homework
    1. 5.1. Homework 1
    2. 5.2. Homework 2
    3. 5.3. Homework 3
    4. 5.4. Homework 4
    5. 5.5. Homework 5
    6. 5.6. Final Project Reqs
  6. 6. Resources
    1. 6.1. Python Glossary
    2. 6.2. Basic Statistics
    3. 6.3. Pandas Glossary
    4. 6.4. General Reference Guides
    5. 6.5. Libraries, Packages, & Other Tools
    6. 6.6. Cheat Sheets
    7. 6.7. Helpful Articles/Tutorials
    8. 6.8. Open Source Datasets
  7. 7. About

Python Programming

✅ Lecture 1: Installing Python

Objectives

  1. Get to know each other!
  2. Install python locally

Agenda

  1. Intros
  2. Tools
  3. Environment
  4. Install Python