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Intro to A.I.

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Course Info

About Course

Welcome to our general intro course about artificial intelligence.  Here we will learn about the basic algorithms behind much of today's modern AI, and discuss examples of modern technologies that incorporate AI.  Most important, we will apply our knowledge of AI, to engage in some fun activities that demonstrate real world applications of our newfound AI skills.

What Will You Learn?

  • In this class, you will learn about machine learning, some basic AI algorithms, and we will walk through examples of some of today's coolest AI technologies, as well as basic AI activities you can try yourself.

About the instructor

instructor avatar
AI Ninja
Barnas Monteith runs Tumblehome Learning, which focuses on creating curriculum and learning materials for K-12 science and engineering education. Barnas has served for many years as Chairman of the Massachusetts State Science and Engineering Fair, Inc. — the oldest dedicated inquiry based science education non-profit in the state. As a young student, Barnas was the most successful science fair participants in Massachusetts history, with four 1st place MSSEF wins, four 1st place Regional wins, two International (ISEF) 1st place Grand Awards, and a number of other scholarships and special first prize awards. His projects focused on the study of dinosaur and bird evolution using fossilized eggshell microstructures and biochemistry. Today, he continues to mentor students developing their own science fair projects. Barnas spent nearly a decade conducting research on evolution of biochemicals, using custom built pattern recognition software, and was the youngest researchers ever to present a plenary lecture at the Society for Vertebrate Paleontology, based on his work using advanced software to demonstrate species evolution based on genetics over hundreds of millions of years. Later, he conducted research at MIT Media Lab and based on this technology, started several successful technology companies focusing on software, wearable tech, and the manufacture of synthetic diamonds for the semiconductor, lighting and energy industries. His company won a number of top business awards from Harvard, MIT, Columbia, UC Berkely and more. His company's semiconductor products held the leading market share across the globe, and are still used today by the world's leading chip companies. Barnas has served on the Massachusetts Department of Education Math & Science Advisory Council and the inaugural Governor’s STEM Advisory Council, as Chair of its Public Awareness subcommittee. He has authored a number of patents, published scientific articles in a variety of areas including AI, energy/semiconductors and materials science and speaks regularly at STEM education events and conferences throughout the world. He has written several books on the topics of computers, cross disciplinary science fairs, and AI.

Course Curriculum

Section 1. Course Intro – Activity 1: FaceBoxes – Basic Face Detection
In this brief section, including Activity 1 we will discuss the various topics we will cover in this course, as well as some background on the concept of artificial intelligence vs natural intelligence.

Section 2. History of Computing & AI – Activity 2: What is AI?
In this section, we will discuss the early and recent history in AI technology development. We will also cover some background on semiconductors, CPU's, GPU's and other technology that make AI possible. We will also discuss the basics of AI model training, and go through some of today's most popular AI technologies.

Section 3. How is AI used in different applications? – Activity 3: Aligning real world AI with AI4K12
In this section, we will discuss several real world examples of AI robotics, and go through the exercise of aligning AI concepts with the AI4K12 5 Big Ideas in AI.

Section 4. AI in action: Teachable Machine – Activity 4: Training and testing an AI model
In this section, we will conduct a browser based activity, and will go through all the steps of developing training data, uploading it to a Google server, and training a real AI model, for object detection. We will then test our resulting model with different objects and record our results, to determine if the model is well-built and if there are any potential drawbacks or ways to improve the system.

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Material Includes

  • Videos
  • Class activity worksheets
  • Activity / lesson guides
  • Browser based activity resources


  • • Chrome Browser, updated to latest version
  • • Internet Connection
  • • Webcam capable of use with Chrome browser applications