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Here are some suggested activity sequences for middle and high school, covering various levels of detail on how AI works, and even how to program it.

(This page is currently being improved)
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College

Complete introduction to AI" course

Objectives: Understand the basic functioning of AI and machine learning
Time required: approximately 6 hours
Activities:
1. Introduction to AI
2. Robot race - introduction to supervised learning
3. Line tracking (manual editing + supervised learning)
4. Follow-me robot
5. Reinforcement learning - Obstacle avoidance
6. AI ethics
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Rapid introduction to AI" course

Objectives: Understand the basic functioning of AI and machine learning
Time required: approximately 3 hours
Activities:
1. Robot race - introduction to supervised learning
2. Line tracking (manual editing + supervised learning)
3. Follow-me robot
4. Reinforcement learning - Obstacle avoidance
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High School

Introduction to AI" curriculum

Objectives: Understand the basic functioning of AI and learning
Time required: approximately 5 hours
Activities:
1. Introduction to AI
2. Robot race - introduction to supervised learning
3. Line tracking (manual editing + supervised learning)
4. Reinforcement learning - Obstacle avoidance
5. AI ethics
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AI & Mathematics" curriculum

Objectives: Understand how AI and machine learning work, and that everything is governed by mathematics!
Time required: approximately 8 hours
Activities:
1. Robot race - introduction to supervised learning
2. Line tracking (manual editing + supervised learning)
3. KNN algorithm
4. Intruder detection (neural network mathematics)
5. Reinforcement learning - Obstacle avoidance
6. Reinforcement learning - Blocked VS Movement

Simple "AI & Python Programming" course

Objectives: Understand how AI and machine learning work, and program algorithms in Python
Time required: approximately 9 hours
Activities:
1. Robot race - introduction to supervised learning
2. Line tracking (manual editing + supervised learning)
3. Remote-controlled AlphAI (Python programming)
4. KNN algorithm
5. Advanced KNN algorithm (programming)
6. Reinforcement learning - Obstacle avoidance
7. Reinforcement learning - Stuck VS Movement
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Advanced "AI & Python Programming" course

Objectives: Understand how AI and machine learning work, and program algorithms in Python
Time required: approximately 14 hours
Activities:
1. Robot race - introduction to supervised learning
2. Line tracking (manual editing + supervised learning)
3. Remote-controlled AlphAI (Python programming)
4. Camera programming
5. KNN algorithm
6. Advanced KNN algorithm (programming)
7. Intruder detection (neural network mathematics)
8. Reinforcement learning - Obstacle avoidance
9. Reinforcement learning - Blocked VS Movement
10. Reinforcement learning - Q-learning (programming)
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Python programming" course

Objectives: Learn how to program simple algorithms in Python
Time required: approximately 4 hours
Activities:
1. Remote-controlled AlphAI (Python programming)
2. Camera programming
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