Section outline

  • Lesson Goal: Ensure students can access and run machine learning code without installing software on their own computer, by using Jupyter notebooks and Google Colab. This lesson covers why Python is the go-to language for ML, what notebooks are, how to use Colab in a browser, and how this cloud setup provides more power and zero setup headaches.

    • Micro-Topic 2.1: Why Python for Machine Learning?

      Goal: Explain why Python is the most popular language for machine learning and how its features (libraries, simplicity) help beginners and experts alike.

    • L02 MT1 FREE content only SCORM12 SCORM package

    • Micro-Topic 2.2: Jupyter Notebooks – Interactive Coding

      Goal: Introduce Jupyter notebooks, explaining what they are and why they are useful for learning and experimenting with code, especially in data science and ML.

    • L02 MT2 FREE content only SCORM12 SCORM package

    • Micro-Topic 2.3: Using Google Colab – Your Cloud Coding Lab

      Goal: Explain what Google Colab is and how it allows you to run notebooks in the cloud, with zero setup and access to powerful computing resources (for free), directly from a browser.

    • L02 MT3 FREE content only SCORM12 SCORM package

    • Micro-Topic 2.4: Running Your First Code in Colab

      Goal: Walk through a simple example of opening a Colab notebook and running a basic Python ML snippet, to demonstrate the end-to-end process of using Colab for the first time.

    • L02 MT4 FREE content only SCORM12 SCORM package