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High School
Applications of Artificial Intelligence
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Building on the foundational knowledge acquired in Artificial Intelligence in the World, you’ll embark on a thrilling journey through the world of artificial intelligence. From machine learning to robotics, you’ll gain hands-on experience developing AI systems, delve into the complexities of natural language processing and computer vision, and consider the ethical and societal implications of this rapidly evolving technology. Get ready to be amazed and inspired by the limitless possibilities of AI as you immerse yourself in this cutting-edge field.
Major Topics and Concepts
Advancements in AI
How AI systems are used
Relationship between AI, humans, and the environment
Training data
Collecting and analyzing data
Databases
Relational databases
Challenges and solutions in AI
Software development life cycle
Decision-making and automation in AI
Data patterns and processing
Supervised and unsupervised learning
Speech transcription
Visual object recognition
Training machine learning (ML) models
Embedded systems
Career and technical student organizations
Course Materials
You will need the following programs to complete this course:
Microsoft Word (or other word-processing program)
Microsoft Excel or Google Sheets (or other data-visualization program)
Microsoft PowerPoint, Canva, or Adobe Photoshop
Micro:bit Python editor
Micro:bit MakeCode editor
Competencies
Artificial Intelligence Foundations
Students will demonstrate an understanding of artificial intelligence foundations by explaining artificial intelligence systems, explaining the importance of ethics and governance, and describing data usage and information handling.
Artificial Intelligence Standards
Students will demonstrate an understanding of artificial intelligence standards by explaining the role of technology, describing design standards, and explaining features of applications and functions.
Elements of Artificial Intelligence
Students will demonstrate an understanding of elements of artificial intelligence by describing the evaluation of artificial intelligence bias and diversity, explaining the role of machine learning in problem-solving, describing the impact of artificial intelligence services, and explaining the development of embedded systems.
