Artificial Intelligence

All-Genders Course;
Prerequisite - Successful completion of at least one year of high school math;
Fall Semester or Full-Year Course

From virtual personal assistants like Siri and Alexa to autonomous vehicles that navigate and drive themselves, Artificial Intelligence (AI) is embedded in all kinds of technology and makes everyday objects act in human-like ways. Beginning with AI’s foundation in data science, this course explores the world of AI, its key technologies, and the concerns guiding its use. Students model machine learning algorithms using block-based and Python programming languages, and design intelligent agents to solve real-world problems. Topics include natural language processing, image processing, deep neural networks, data science life cycle, computation thinking, and predictive analytics. Students leave this course having gained an understanding of how AI can help us make better decisions and build “smarter” technology.

Please note: this course cannot be completed without a computer running a Windows or Macintosh operating system. Chromebooks, iPads, smartphones, and tablets are not adequate.

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FAQ

Meet The One Schoolhouse Faculty

"This course has been fantastic! It has been very fun while still remarkably educational."

Course Approval

One Schoolhouse is fully accredited with the Middle States Association of Colleges and Schools and the Western Association of Schools and Colleges through December 1, 2025; we are an approved online publisher for the University of California.

Teachers at One Schoolhouse

Teachers at One Schoolhouse are passionate about helping students flourish and thrive.

With small sections (averaging 15 students), teachers inspire, encourage, and instill confidence in their students.

One Schoolhouse teachers are experts in their subject field. 94% of our teachers hold an advanced degree.

Teachers are drawn from top independent schools across the country and participate in our extensive training on current research and best practices in online instruction methods.

What Happens In The Second Semester?

Students wishing to pursue an artificial intelligence project may enroll in the course for the full year. For students continuing into Semester II, the course shifts into personalized, project-based work, where students engage in deep, sustained inquiry, authentic and iterative research, critical analysis, and rigorous reflection, revision, and assessment as they journey through a self-designed, long-term activism, design, or research project on the topic of their choosing. Guided by a One Schoolhouse teacher, students pursue individual study/self-assessment or collaborative seminar/peer-review. Pathway options from which students choose include:

Spring Activism Seminar: In this seminar, students identify a need and create a plan to effect economic, environmental, political, or social change in a target community. Utilizing a social science approach to research and evaluation, students are guided through the process of planning the deployment of a novel idea and identifying markers of success. Students may create a strategic plan for a club or non-profit or design an artistic product in this seminar.
Spring Design Seminar: In this seminar, students design a technological solution to a real-world problem. Through the engineering design process/scientific method, students gather and analyze data to determine the effectiveness of their model or the accuracy of their hypothesis. Students may prototype and produce a public product in this seminar.
Spring Research Seminar: In this seminar, students answer a theoretical or ethical question. Utilizing the social science/humanities tools for source evaluation, students collect, critique, and evaluate artifacts or primary source documents to explore their thesis. Students may create a written or multimedia product in this seminar.

Upon completion of their inquiry-driven project, students will have gained academic maturity and expanded their ability to engage in a diverse and changing world. They will be able to draw and defend conclusions from theoretical underpinnings, contextual background, and mathematical analysis or source evaluation. Finally, they will have created and tested something useful of their own design or will be able to defend a position based on their own research.