Artificial Intelligence Teaching Machines to Think like Humans

STEM (Science, Technology, Engineering, Mathematics)

Grades: 7-9

• 6:00 p.m. Eastern Time (New York Time)

Artificial intelligence (AI) has arrived. With it, nearly every aspect of modern society has been disrupted, spanning across business, finance, marketing, politics, media, transportation, science, agriculture, medicine, and the arts. From the simplicity of a spam filter to the complexity of driving, from the originality of composing music to the technicality of medical diagnosis, and from the scale of running a search engine to the personalization of movie recommendations, AI is transforming our everyday lives. This course focuses on building an understanding of the foundational concepts of modern artificial intelligence. The course will start by focusing on simple questions like “what is AI?” “what does it mean for machines to ‘learn’?” and “where is AI being applied in everyday life?” Then, we will delve into the mathematics of artificial intelligence, present several classes of machine learning algorithms designed to solve problems, and see how these algorithms can be applied to have a transformative impact. The course will cover state-of-the-art AI, including supervised learning and reinforcement learning using deep neural networks. Finally, we will consider the implications of deploying an autonomous system into the real world and discuss the fairness and ethics of AI.

Ross Benjamin Alexander

Ross Benjamin Alexander

PhD(c) Aeronautics & Astronautics at Stanford University

Ross is a second-year graduate student at Stanford University pursuing a Ph.D. in Aeronautics & Astronautics (M.S. 2021; Ph.D. 2024) and is also the recipient of a Stanford Graduate Fellowship (SGF) in Science & Engineering. As a researcher in the Stanford Intelligent Systems Lab (SISL), Ross works on developing principled methods for algorithmic decision making under uncertainty utilizing approaches involving machine learning and artificial intelligence. Ross’s research has led to collaborations across the globe on topics spanning multidisciplinary design optimization, autonomous driving, and COVID-19. Ross continues to build his teaching career as a course assistant for graduate-level computer science courses and as an Artificial Intelligence course instructor for the Stanford Pre-Collegiate Studies Institute.

Ross earned his Bachelor of Science in Aerospace Engineering from Texas A&M University in 2019. In his four years at Texas A&M, Ross developed a strong technical background through his work in trajectory modeling & simulation and propulsion system design on the Texas A&M University Sounding Rocketry Team and also through three internships at aerospace research & development (R&D) companies.

Program Calendar:
January 11-22, 2021
(Monday – Friday)
Real-Time Classes Duration:
1 hour & 45 minutes long
(with a 15-minute break).
Max Class Group:
Small class size
(20 students max)

Program Courses

Grades 7-9

For grade 9 students all course options are available.





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