Lesson List
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.
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Course Topics
Media / website resources
Vocabulary used
FaceBoxes: Simple face detection demonstration & activity
00:00:00
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.
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Defining AI vs NI (Natural Intelligence)
00:00:00
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.
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How do real world AI technologies align with AI’s 5 Big Ideas?
00:00:00
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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Making and testing an AI object detection model in Teachable Machine
Draft Lesson
00:00:00
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Lesson: Media / website resources
Overview
Exercise Files
About Lesson

Media / Resources:

Cozmo – Robot Friend Video

https://www.youtube.com/watch?v=BWymDFX8PlY

Alexa Video

https://www.youtube.com/watch?v=W3DEJgnGZYc

Miro:

https://miro.com/

Teachable Machine:

https://teachablemachine.withgoogle.com/train

AI4K12 5 Big Ideas / AI Teaching Concepts

https://ai4k12.org/wp-content/uploads/2021/01/AI4K12_Five_Big_Ideas_Poster-1.pdf

AI4K12 Website (see AI K12 Guidelines)

https://ai4k12.org/

Codepen OpenCV Browser Based Face Detection Program

https://codepen.io/bmonteith/full/BaJWzXx

Supplemental Media:

AI Drone Video

https://www.youtube.com/watch?v=CdzFvT2EHKY&feature=emb_imp_woyt

Exercise Files
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Lesson List
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.
0/4
Course Topics
Media / website resources
Vocabulary used
FaceBoxes: Simple face detection demonstration & activity
00:00:00
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.
0/1
Defining AI vs NI (Natural Intelligence)
00:00:00
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.
0/1
How do real world AI technologies align with AI’s 5 Big Ideas?
00:00:00
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.
0/2
Making and testing an AI object detection model in Teachable Machine
Draft Lesson
00:00:00
This feature has been disabled by the administrator
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