High School

Applications of Artificial Intelligence

0.5 Credits
18 weeks
artificial intelligence graphic

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
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


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.