Join our Free MathCAI Events – You’re Invited!
Space is limited, so don’t wait!
Join our MathCAI Information Webinar – You’re Invited!
Space is limited, so don’t wait!
Where Math meets Computer Science and AI
Welcome to MathCAI, which offers a chance to experience next-generation Math education. In this course, students learn math topics integrated with Computer Science and AI! With hands-on projects, games, and activities, we make learning easy and enjoyable in a friendly environment. This engaging and inspiring environment fosters creativity, enhances critical thinking, and equips students with essential skills for the STEM fields of tomorrow.
Why MathCAI?
MathCAI offers a unique, integrated approach to learning Math, Computer Science, and Artificial Intelligence. By connecting these disciplines, we provide students with a well-rounded foundation that prepares them for the future.
Our program focuses on:
- Developing mathematical thinking
- Enhancing problem-solving skills
- Building teamwork and collaboration
Through fun, engaging, and hands-on activities, MathCAI inspires curiosity and passion for exploring the connections between Math, CS, and AI.
Who Should Attend?
MathCAI is designed for rising 5th and 6th graders with a good understanding of 5th-grade math concepts.
Location
Santa Clara, CA
Curriculum
MathCAI emphasizes conceptual understanding, creative problem-solving, and exploration of advanced and interdisciplinary math topics that often go beyond grade-level math. However, it does not focus on grade-level math in the traditional sense, like teaching specific curricula aligned with school standards (e.g., Common Core or grade-specific arithmetic or algebra).
MathCAI Summer Courses are designed as one-week, half-day sessions, each offering a unique and independent learning experience across six different courses.
MathCAI Summer Courses
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Ants on a Math Trail
Bears and Number Secrets
Dolphins and Playful Brain Games
Eagles and the Art of Prediction
Squirrels and Shape Puzzles
Turtles and Hidden Messages
2025 Summer Camp Schedule
| Morning (9 am - 12 pm) | Afternoon (1 pm - 4 pm) |
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| Jun 9-13 | Ants | Eagles |
| Jun 16-20 | Bears | Squirrels |
| Jun 23-27 | Dolpinhs | Turtles |
| Jul 14-18 | Eagles | Ants |
| Jul 21-25 | Squirrels | Bears |
| Jul 28-Aug 1 | Turtles | Dolpinhs |
Sample Activity
The Ultimate Rock-Paper-Scissors Battle
This hands-on, collaborative exercise introduces key concepts in math, computer science, and artificial intelligence through one of the simplest yet most strategic games ever created. It’s a fun and engaging way to spark curiosity and excitement about STEM!
What Happens in the Activity?
- Play and Log Results
- Students start by playing Rock-Paper-Scissors individually, keeping logs of their results.
- Discussions follow about patterns, winning strategies, and player behavior.
- Team Play and Strategy Development
- Students form teams and compete against other teams.
- Each team develops fixed strategies (e.g., always playing a specific sequence) and discusses their strengths and weaknesses.
- Simulating Strategies with Computers
- Teams watch a computer simulate matches using various fixed strategies.
- Students explore how computers can play with consistency and how to predict outcomes based on data.
- Teaching Computers to Learn
- Introducing AI: Students learn how a computer can “learn” from human behavior to improve its game.
- They see how AI adapts and creates counter-strategies over time.
- Challenge the AI
- Equipped with their new knowledge, students try their best strategies against the AI model, using math-based insights to increase their chances of winning.
Concepts Explored
- Probability: Understanding randomness and predicting outcomes.
- Data and Statistics: Collecting, analyzing, and interpreting game results.
- Modeling Strategies with Math: Using patterns and mathematical thinking to optimize strategies.
- Simulations: Visualizing how computers follow fixed strategies through simple simulations.
- Modeling Human Behavior: Learning how AI can analyze patterns, adapt strategies, and respond dynamically based on past data.
