Camp Overview
This summer camp introduces students to the power of data science through hands-on, real-world problem solving—starting with questions they actually care about.
Instead of just learning concepts, students explore questions like:
Does more screen time affect happiness?
Is healthy food always lower in calories?
Can a computer guess your favorite snack?
How does Netflix know what you want to watch?
Can AI recognize what’s in your lunch?
Students begin by learning how to analyze and visualize data to uncover patterns and insights. They then explore how machines make predictions, building an intuitive understanding of modeling. As the camp progresses, students are introduced to advanced topics such as computer vision and large language models (LLMs), connecting their learning to modern AI technologies they see in everyday life.
 
Project-Based Learning Experience
The camp is centered around a project-based experience where students take on the role of a data analytics team.
Working with engaging, real-world datasets, students answer questions such as:
What snack should we sell to make the most money?
What price should we set to maximize profit?
Which product should we keep or remove?
How do real companies use data to make decisions?
By the end of the program, each team completes an end-to-end project—defining a problem, analyzing data, building a model, and presenting a data-driven recommendation. This process helps students develop not only technical skills, but also critical thinking, collaboration, and decision-making abilities.
 
 
Example Daily Schedule (9:30 AM – 4:30 PM)
Schedule may be adjusted based on class needs
9:30 – 10:00 | Warm-Up & Community Time
Kick off the day with interactive activities, fun challenges, and discussion questions to spark curiosity and engagement.
10:00 – 12:00 | Data Science Learning (with short breaks)
Hands-on lessons covering data analysis, visualization, and modeling. Students participate in mini challenges and interactive activities to apply what they learn.
12:00 – 1:00 | Lunch & Recess (Lunch included)
Time to relax and recharge. Students can socialize or join optional activities.
Example lunch: homemade dumplings, burgers/sandwiches, sushi rolls, chicken wings, fruits
1:00 – 4:00 | Project Work (with short break)
Students work in teams on their projects—exploring questions, analyzing data, and building solutions with guidance and regular check-ins.
4:00 – 4:30 | Wrap-Up & Dismissal Prep
Students reflect on their progress, share insights, and prepare for the next day.
 
 
Instructors
Dr. Zhou
Dr. Zhou is a Technology Teacher at Eastside Preparatory School and a former Principal Data Science Manager at Microsoft, with over a decade of industry experience. She holds a Ph.D. in Computer Science and specializes in connecting data science and AI concepts to real-world applications.
In her classroom, Dr. Zhou emphasizes project-based learning and guides students through the full problem-solving process—from asking meaningful questions to delivering data-driven solutions—while building confidence, independence, and critical thinking skills.
 
Prof. Huang
Prof. Huang is an experienced data science and analytics leader with over a decade of industry experience. He has taught Predictive Analytics and Quantitative Analysis for Business at the University of Washington and holds a Ph.D. in Economics.
His work focuses on applying data science and quantitative methods to real-world business problems. In teaching, he emphasizes practical application—helping students move beyond formulas to understand how to define problems, analyze data, and make clear, evidence-based decisions.
 
 
Pricing & Payment Notes
Tuition: $750 per student (lunch included)
A 3% processing fee is added to online payments (total: $770).
Offline payment options (Zelle/Venmo) are available to avoid processing fees. Select offline payment at checkout to pay $750.
 
Early Bird Discount: $10 before 5/16/2026
Referral Discount: $10
Existing Family Discount: $10