Intro to AI
Explore the overview, objectives, and structure for the Introduction to AI course.
This one-semester course introduces students aged 12-18 to the fundamental concepts, applications, and implications of Artificial Intelligence (AI). Through a combination of theoretical understanding and hands-on experiential learning, students will explore how AI works, where it's used in everyday life, and how to think critically about its impact on society. The course emphasizes practical, project-based learning with accessible tools that require minimal programming experience.
By the end of this course, students will be able to:
Upon successful completion of this course, students will:
Total Duration: One semester (approximately 80 days) Total Instructional Hours: 40 hours Lesson Length: Approximately 1 hour per lesson Number of Units: 8 units Lessons per Unit: 4-5 lessons per unit
| Unit | Topic | Duration | Lessons |
|---|---|---|---|
| 1 | Introduction to AI | 5 hours | 5 lessons |
| 2 | Machine Learning Basics | 5 hours | 5 lessons |
| 3 | Neural Networks | 5 hours | 5 lessons |
| 4 | AI Applications | 5 hours | 5 lessons |
| 5 | Ethics and Bias | 5 hours | 5 lessons |
| 6 | Hands-On Projects | 5 hours | 5 lessons |
| 7 | Current Trends and Future | 5 hours | 5 lessons |
| 8 | Final Projects and Presentations | 5 hours | 5 lessons |
Assessment in this course emphasizes understanding, application, and reflection over memorization:
Formative Assessments (Ongoing)
Project-Based Assessments (Unit 6 & 8)
Summative Assessments (End of Units)
Final Assessment (End of Course)
Learning Objectives: Students will understand what AI is, its history, different types of AI, and recognize AI in everyday life.
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Learning Objectives: Students will understand the three main types of machine learning and how machines learn from data.
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Learning Objectives: Students will understand how neural networks work conceptually and their role in deep learning.
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Learning Objectives: Students will explore major AI application areas and experiment with real AI tools.
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Learning Objectives: Students will critically examine ethical issues, bias, and societal impacts of AI.
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Learning Objectives: Students will create their own AI applications using accessible tools.
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Learning Objectives: Students will explore cutting-edge AI developments and consider future possibilities.
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Learning Objectives: Students will develop comprehensive capstone projects and present their work.
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This course is designed for a mixed-age group (12-18). Differentiation strategies include:
Students are encouraged to ask questions during class and seek help when needed. The course emphasizes learning through exploration and collaboration.
Course Philosophy: This course believes that AI literacy is essential for all students, regardless of age or background. Through hands-on experience and critical thinking, students will become informed citizens who can engage thoughtfully with AI technology in their lives and careers.
Unit 1: Introduction to AI 5 hours · 5 lessons Unit Objectives Define artificial intelligence in their own words. Explain the difference between narrow AI and general AI. Identify AI applications in their daily lives. Describe key milestones in AI…
Unit 2: Machine Learning Basics 5 hours · 5 lessons Unit Objectives Define machine learning and explain how it differs from traditional programming. Identify and explain the three main types of machine learning. Understand training data, testing data, and model…
Unit 3: Neural Networks 5 hours · 5 lessons Unit Objectives Explain what a neural network is and how it draws inspiration from the brain. Understand neural network structure, including neurons, layers, and connections. Describe how neural networks learn and…
Unit 4: AI Applications 5 hours · 5 lessons Unit Objectives Understand how AI powers computer vision solutions. Explain the fundamentals of natural language processing. Recognize AI applications in speech recognition and synthesis. Understand AI’s role in robotics and autonomous…
Unit 5: Ethics and Bias 5 hours · 5 lessons Unit Objectives Understand what bias is and how it appears in AI systems. Recognize why fairness is essential in AI. Identify privacy concerns connected to AI technologies. Analyze the societal…
Unit 6: Hands-On Projects 5 hours · 5 lessons Unit Objectives Plan and design an AI project from concept to delivery. Use no-code and low-code AI tools to build applications. Implement machine learning models to solve real problems. Test and…
Unit 7: Current Trends and Future 5 hours · 5 lessons Unit Objectives Understand cutting-edge developments shaping AI today. Explain large language models and generative AI. Recognize AI applications across multiple industries. Explore future possibilities and predictions for AI. Identify…
Unit 8: Final Projects and Presentations 5 hours · 5 lessons Unit Objectives Develop a comprehensive capstone AI project. Integrate multiple concepts learned throughout the course. Create detailed project documentation. Deliver effective presentations. Provide constructive peer feedback. Reflect on the…