Unit 1, Lesson 1
| Topic | Description | Link |
|---|---|---|
| Part 1. Development Environment | A quick check to ensure that git and Anaconda are working | here |
| Part 2. Data Science Definitions | Jupyter notebook reviewing common terms, topics, & course info | here |
| Part 3. Python Practice | Jupyter notebook review of Python programming fundamentals | here |
- Set up and confirm your development environment.
- Define the Data Science Workflow and common Machine Learning concepts.
- Discuss the topics and goals of our course.
- Use types in Python correctly.
- Create basic functions in Python.
Before this lesson(s), students should have:
- Successfully completed the prework
- Optional: enabled administrative privileges on personal machines, if possible (this makes installations easier)
Total Time: 180 min.
-
Part 1. Development Environment
- Installation Check (15 mins)
-
Part 2. Data Science Definitions
- Activity: Data Science in the Real World (5 mins)
- How to Ask a Question (10 mins)
- Data Science Workflow through Ames Data (20 mins)
- Summary (5 mins)
- Common ML Definitions (15 mins)
- Activity - Quiz or group (15 mins)
- Summary (5 mins)
-
Break + Course Info
- Course & Project Structure (5-10 mins)
-
Part 3. Python Fundamentals
- Survey (5-10 min)
- Common Python Types (10 min)
- Common Types Codealong (20 min)
- Common Python Functions and Control Flow (10 min)
- Common Python Functions Codealong (20 min)
- Recap and Requests (5 min)
For more information on this topic, check out the following resources: