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Welcome to Data Science

Unit 1, Lesson 1


Materials We Provide

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

Learning Objectives

  • 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.

Student Requirements

Before this lesson(s), students should have:

  • Successfully completed the prework
  • Optional: enabled administrative privileges on personal machines, if possible (this makes installations easier)

Lesson Outline

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)

Additional Resources

For more information on this topic, check out the following resources: