Course Syllabus

Course Syllabus

About this course:

This course provides learning experiences for educators that introduce foundational concepts in artificial intelligence (AI). Special focus is placed on topics like machine learning (ML), responsible AI practices, and AI ethics. Here you can find interactive modules introducing AI literacy topics with real-world examples, and resources to implement AI literacy with students.

Technologies that use artificial intelligence (AI) have already been integrated into everyday life. From spam email recognition to Siri and Alexa, many of the daily tools we have come to rely are powered by AI. AI literacy has become a key qualification for participants across America’s workforce and plays a crucial role in primary and secondary education. Equipped with AI literacy tools, students can begin to prepare themselves for a future where AI is a fundamental part of everyone's personal and professional lives. 

Join us in empowering educators and students with the knowledge they need to navigate the evolving landscape of an AI-driven world!

Learning Objectives:

By the end of this course you will be able to:

1. Define Artificial Intelligence (AI), Machine Learning (ML), and data
2. Identify examples of AI, ML, and data in everyday life
3. Establish the relationship between AI and ML 
4. Understand how ML models learn from data during the ML process
5. Engage in hands-on activities with Teachable Machine to illustrate the machine learning process
6. Understand how ML models can perpetuate bias, and identify implications of biased ML & AI
7. Explore Responsible AI & AI Literacy frameworks to begin planning your first AI lesson!

Course Summary

Topics in this course are organized into modules. To successfully complete this course you will complete all assignments, quizzes and surveys in each module. You can see an outline of all modules in this course by choosing the "Modules" link in the left navigation bar, or by clicking the button below.