This course introduces students to the basic concepts of AI and shows them how to build AI applications. This course is intended for students with no prior AI knowledge, and introduces the concepts in a way that does not require deep knowledge of math.
No pre-requisites for students in 9th grade and above. Students in Middle School can take this advanced camp if they have already taken one or our Basics course or the Middle School AI Camp, or if they are in 8th grade and have taken an introductory algebra course.
Curriculum
Students will learn to build different types of AI for numbers, text, categorical data and images. They will learn some of the powerful algorithms used to build these AIs (such as Decision Trees, Neural Networks and Natural Language Processing) and how to select the right algorithms and tune them for the AI projects.
They will build several AIs such as to detect emotions in text and images, to detect and predict values (such as house prices or product prices), and to use image processing for scientific applications, and how AIs can be taught to play and win games. . They will build AI projects to do each of these and learn how the methods behind them work and how to tune them. This knowledge will equip them to use AI in other projects, such as STEM competitions. They will also get a good understanding of the issues of fairness and bias in AI and how to think about these issues in their daily lives and studies.
Students will also do a custom project of their choice to build an AI system to solve a problem. They will showcase their project to their parents and peers on the last day of the summer camp. We will provide project ideas on the first day of camp.
The core AI concepts they will learn are:
• Learn to identify different types of algorithms (classification, regression) appropriate for different types of problems and data (text, numbers, categories and images).
• Learn how AI algorithms work (Linear Regression, Decision Trees, and Neural Networks) and how to tune and improve the AI performance.
• Train an AI system from raw data and use it to build cool applications.
• How to improve an AI with better data. Core concepts of Data Skew, Balance, Overfitting etc.
• How AI compares to rule engines (can I beat an AI by writing rules?), and when to use and not to use AI
• What is Deep Learning? How does it work? How can it be used for AI to understand images?
• How to train an AI to compete and win in games.
Prerequisites
• A laptop with chrome browser
• Wifi connectivity
• Coding knowledge optional. All projects can be done with no code.
• No previous math or algebra knowledge needed
What Students Take Away
• A good understanding of AI - a fascinating and fundamental technology that is changing our world.
• Several AI projects that they can build, covering numbers, text, images and games.
• A lifetime access to an online cloud account where they can continue to build new projects and learn more AI
• Certificate of Completion
• Opportunities to compete and win in AI competitions