Product Description:

The "Advanced Machine Learning & Artificial Intelligence" course is designed for learners in grades 9-12. This comprehensive 15-hour course introduces students to the advanced concepts of machine learning and artificial intelligence, focusing on real-life applications and challenges. Students will collect and build datasets to train machine learning algorithms and explore image analysis and augmented reality (AR) applications.

Course Features:

• 15 Lesson Hours: The course includes 15 detailed lessons that cover a wide range of topics in machine learning and artificial intelligence.

• Curriculum and Supporting Materials: Comprehensive lesson plans, activity guides, and additional resources to support effective teaching and learning.

• Ongoing Product and Curriculum Support: Continuous support to ensure the curriculum remains relevant and effective.

• Professional Development: Training sessions for educators to deliver the course content effectively and facilitate student learning.

• Facilitation by a Trained STEM Instructor (Optional): Option to have a professional STEM instructor lead the course.

Learning Target Examples:

1. Introduction to Machine Learning and AI: Understand the foundational concepts of machine learning and artificial intelligence.

2. Data Collection and Preparation: Learn how to collect, clean, and prepare datasets for machine learning models.

3. Supervised Learning: Explore supervised learning techniques and algorithms.

4. Unsupervised Learning: Understand unsupervised learning methods and their applications.

5. Neural Networks and Deep Learning: Dive into the basics of neural networks and deep learning.

6. Image Recognition: Implement image recognition models and understand their applications.

7. Natural Language Processing (NLP): Explore NLP techniques and build models for text analysis.

8. Reinforcement Learning: Understand the principles of reinforcement learning and its real-world applications.

9. Model Evaluation and Optimization: Learn how to evaluate and optimize machine learning models.

10. Ethics in AI: Discuss the ethical implications of artificial intelligence and machine learning.

11. Augmented Reality (AR) Applications: Explore the integration of machine learning with AR technologies.

12. AI in Healthcare: Understand the applications of AI in the healthcare industry.

13. AI in Finance: Explore how AI is transforming the finance sector.

14. AI in Autonomous Vehicles: Learn about the role of AI in developing autonomous vehicles.

15. Final Project: Develop a comprehensive machine learning project that addresses a real-world problem.

Equipment Included:

• Classroom Set of Tablets: Devices for students to use for coding and machine learning projects.

• Supporting Materials: Various materials required for hands-on activities, including software licenses and instructional guides.

• Machine Learning Software Access: Access to machine learning and AI software tools necessary for the course.

Professional Development:

• Teacher Training: Comprehensive training sessions to equip educators with the skills and knowledge to effectively teach the course.

• Ongoing Support: Continuous professional development opportunities and support to ensure successful course delivery.

Additional Information:

• Designed for Learners in Grades 9-12: The course is tailored to meet the developmental and educational needs of students in this age group.

• Hands-On Activities: Emphasis on interactive and engaging activities to foster a love for learning and exploration in STEM fields.

• Problem-Solving and Creativity: Encourages students to use their imagination and creativity while learning advanced concepts in machine learning and artificial intelligence.