CS50 Computer Science & AI Ethics Academy

Overview

A full academic-year academy for academically motivated teens who want a deeper introduction to computer science, computational thinking, and the social impact of technology. Inspired by the spirit of rigorous introductory CS pathways, this program combines programming, algorithmic thinking, problem solving, and discussion of AI and ethics.

This Academy is designed for students who want a more serious, intellectually challenging coding experience with clear academic value.

Best for

Ages 13–17
Best for students who are motivated, curious, and ready for a more rigorous computer science experience
Prior coding experience is recommended

Learning goals

Students will:

• develop a stronger understanding of core computer science concepts
• improve algorithmic thinking and problem decomposition
• strengthen coding fluency across structured programming tasks
• explore how computing systems affect people and society
• discuss responsible technology use, AI ethics, and digital citizenship
• build confidence in academic-style problem solving and technical communication

Year at a glance

Fall Term: Foundations of Computer Science
Students begin with core problem solving, logic, variables, control flow, functions, and introductory computational concepts. Emphasis is placed on understanding how and why programs work.

Winter Term: Algorithms, Data, and Systems Thinking
Students go deeper into how data is organized, how algorithms solve problems, and how computational systems scale. They work through more demanding programming challenges and analytical exercises.

Spring Term: AI, Ethics, and Applied Computing
Students examine modern computing topics including AI tools, ethics, bias, privacy, and decision-making. They complete a final project or presentation that combines technical thinking with broader reflection.

Skills students develop

• computational thinking
• algorithm design
• structured programming
• debugging and reasoning
• technical communication
• ethical analysis of computing
• academic confidence in CS

Sample projects

• algorithmic coding challenges
• data-focused programming tasks
• simulation or systems-based projects
• AI ethics case study
• final technical or interdisciplinary capstone

Format and expectations

Weekly live cohort sessions over the academic year
Students should be ready for a more academic pace and consistent engagement
Optional reading, reflection, or light between-class work may be included

End-of-year outcome

Students gain a stronger foundation in computer science, more confidence with technical reasoning, and a clearer understanding of how coding and AI connect to the wider world.