The discussion provided ideas for teaching software automation in the HSC Software Engineering course.

The following was discussed:

• • Algorithms in machine learning

  • Distinguishing between artificial intelligence (AI) and machine learning (ML)

  • Exploring models of training ML

  • Supervised learning

  • Unsupervised learning

  • Semi-supervised learning

  • Reinforcement learning

• The document provides a variety of resources for teaching these topics, including videos, articles, and online learning platforms.

• The document also suggests ways to differentiate instruction to meet the needs of all students.

Here are some of the key takeaways

• Machine learning is a powerful tool that can be used to automate tasks.

• There are different types of machine learning, each with its own strengths and weaknesses.

• It is important to understand the different types of machine learning in order to choose the right one for a particular task.

• There are a variety of resources available to help teachers teach machine learning.

Other thoughts

• The HSC Software Engineering unit should include a section on software automation, with a focus on machine learning (ML).

• This section should start by defining AI and ML, and then discuss how ML can be used to automate tasks through DevOps, robotic process automation (RPA), and business process automation (BPA).

• The section should also cover the different models of training ML, including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning.

• There are a number of resources that can be used to teach this section, including videos, online learning systems, and interactive quizzes.