AI Institute Summer Camp

1. What’s the top idea and mindset you like for your children have when the camp done?

The top mindset we want students to have is curiosity, critical thinking, and the confidence to solve real-world problems.

AI is not just about programming; it is also about problem-solving. Students will learn how to define a problem, figure out the best way to provide a solution, and identify the best AI tools to address those problems efficiently.

2. How will this program prepare students for the future?

Our summer camp gives students a unique opportunity to cope with the new AI revolution. The world is very different now, and AI is changing very fast. The summer camp trains students not only to use AI tools, but also to think about how to address real-world problems. If students only know how to do coding, that is not enough. The camp provides training on how to solve problems, how to build real-world applications, and how to present their ideas.

Students can complete portfolio-ready end-to-end projects, and they can use the summer camp outcome for other research competitions, college applications, or future research pathways.

3. How do students with no coding experience succeed in the camp?

We understand that students come with different levels of technical skills. Some students may already know Python, and some may have zero coding background. That is okay.

Each day, professors provide lectures in the morning, PhD students lead live sessions in the afternoon, and assistants provide guided practice and personal help. We will also share some materials before the summer camp starts, so students can review the basic principles of coding.

The more important part for our summer camp is whether the student is curious, willing to learn, and willing to solve problems.

4. What can a 9th grader learn in one or two weeks? What kind of projects would you offer?

Each week is independent, so students can join one week or stack any week in any order they like. Even in one or two weeks, students can learn key AI foundations and build hands-on projects.

For example, students can build their first machine learning model, work on computer vision and object detection, build an AI chatbot, create generative AI projects with text, images, audio, and video, or present a poster or report.

The goal is that students do not just learn concepts. They work directly with AI tools, design inputs, compare outputs, build projects, and present what they created with their teams.

5. Do you have any standout projects or success stories?

We also want to share one example from last summer. During one lab session, we saw three boys playing games together. At first, we were upset. But our TAs were very patient. They talked with the boys to see what their interests were and encouraged them to focus on expanding them.

On the last day, those three boys built a computer game to explain why it is important to protect the environment and protect the Earth. They connected their personal interest in games with AI, education, and a real-world problem. This shows why personal guidance and multi-level mentorship are so important.

6. Why is this year’s camp stronger?

We decided to make the summer camp a university-level AI training experience. Every day, the professor will provide a 3-hour lecture on fundamental theories, methods, and real-world cases. The PhD student will lead a 3-hour live session in the afternoon, and the assistants will provide two hours of guided practice at different levels of mentorship.

We target to help students build real-world applications and complete portfolio-ready end-to-end projects. Students can use the summer camp outcome for research competitions, college applications, academic programs, or publication pathways. For competent students, PhD advisors are eager to help them learn how to do research, how to do critical thinking, and how to pursue future opportunities.