CAMP schedule and curriculum

Camp Structure:
In the first week we will focus on building up AI knowledge and skills that students will implement on a group project in the second week. The second week will also feature workshops on college and career preparation.

Beginner and Advanced Batches: Separate batches will exist for those with no programming experience and those with significant experience. A survey will be sent in early-May to place participants in the appropriate batch based on CS background and project interests.

Pre-camp Preparation: Students will receive preparation materials to help them get the most out of the camp once they arrive. These materials will differ based on student experience, and we would strongly encourage students to explore them. Example: Python basics video series

Curriculum Week 1

In week 1 students will explore applications, foundational AI concepts, and develop AI programming skills.

Applications: We will start each day with a session on applications. E.g. “How AI can help doctors?” or “How does Alexa work?”

Conceptual Intuition: We will pick the most important machine learning algorithms, and provide conceptual intuition. E.g. Neural Networks, Decision Trees

AI Programming Skills: We will guide students to implement mini-projects using Python. E.g. Classifying breast cancer tumors using computer vision

Advanced Batch: Students with programming/AI experience will cover advanced topics such as Object Detection (used in applications like Amazon Go), Generative Models (used for novel image creation tasks e.g. creating anime characters), and Neural Style Transfer (used to combine the style of two images to generate novel paintings).

Tentative Schedule: Evening batch will follow same structure.


Curriculum Week 2

In week 2, students will apply the AI programming skills they learned in week 1 on a mentor-led AI for Social Good project, and will also go through college and career preparation workshops.

AI for Social Good Project: Students will work in teams of 3 – 4 to build an AI application under the guidance of a mentor. Project options and datasets will be previously chosen by instructors to maximize learning and fun*. A digital poster creation workshop will teach students how to document and communicate their project experience.

College and Career Workshops: Workshops will include gaining inspiration from successful Stanford college essays, preparing for top-ranked CS/AI programs in the US, and pursuing ventures or careers in AI.

*Application asks students to specify an AI project they would like to work on. Student input will be considered in picking fun and meaningful projects.

Advanced Batch: Students with programming/AI experience will be matched with a project and team that suits their interests and experience. This could include building a more involved AI model that combines multiple models to achieve the desired outcome, or working with AI models that are tougher to train (e.g. models for language translation)

Tentative Schedule: Evening batch will follow same structure.