A two-week day camp to introduce programming and machine learning to high school students.
The objective of the program is to introduce students to machine learning and programming through a project in which they program various machine learning algorithms including a neural network to recognize images and make a self- driving toy car.
The course consists of conceptual level component and programming components. Students will be introduced to various machine learning concepts and algorithms. In parallel they will be introduced to the Python programming language, which will allow them to implement the concepts they have studied.
Students will participate in exercises using different methods for classifying images of hand-written numerical digits, and will be shown tools to continue learning and programming on their own. Finally, they will take pictures of physical objects and train their own neural network to recognize these objects. Once they achieve high-quality performance, they will install their program into a toy car equipped with a camera which will self drive using their programmed neural network.
Program Dates: July 20-31, 2020 | 9:00 am – 4:00 pm
*Note: the program is a day camp only and does not provide housing for participants.*
- high school student (rising freshman – senior)
- We also have limited slots available for college students who are interested in data science but have prior experience in programming and machine learning. Fees will be waived for college students who are interested in serving as course assistants.
- Students from underrepresented minorities & low-income backgrounds are encouraged to apply. Full and partial scholarships will be available for those who require financial support.
- Interest in applying to college with a focus in STEM
- Basic algebra
- Completed application and release forms
The program is hosted by the Biostatistics Department at the Harvard T.H Chan School of Public Health. It is overseen by a Faculty Director, but developed and taught by Biostatistics PhD students.
For more information, please contact Amanda King