You’ll review neural networks and create convolutional neural networks in Keras to process medical images. Pneumonia Detection (Healthcare, Computer Vision): In this project, you’ll create a computer vision system to help diagnose pneumonia from chest X-rays. Finally, you’ll extend your model through challenge exercises: analyzing when it succeeds and fails, creating saliency maps to make your model interpretable, or editing your dataset to preserve privacy. You’ll use a variety of machine learning techniques, including convolutional neural networks and transfer learning, to create and improve effective models.
Inspirit ai scholars program drivers#
Below are some examples of our projects:ĭistracted Drivers (Computer Vision): In this project, you’ll use computer vision to improve road safety by detecting distracted drivers. In our course, students will work on a mentor-led group project in a domain of their choice and present their work to peers and instructors on the final day.
Day 10 Final Project Presentations, College & Career Prep Panel. Day 9 AI Research Spotlights, Scientific Communication, Hands-on Project Work. Day 8 AI & Careers Workshop, Model Building, Hands-on Project Work. Day 7 AI & Ethics Workshop, Data Exploration, Hands-on Project Work. Day 6 College Prep Workshop, AI Literature Review, AI for Social Good Project Introduction. Day 5 Convolutional Neural Networks, Image and Pattern Detection, CNN Lab. Day 4 Computer Vision, Neural Networks, Neural Networks Coding Lab. Day 3 Natural Language Processing, Test Classification, NLP Coding Lab. Day 2 Machine Learning Foundations, Regression and Classification, Regression Coding Lab. Day 1 Introduction to Artificial Intelligence, Statistics and Probability, Python and AI Libraries Coding Lab. Summer Session Times Options (Weekday or Weekend): Weekend cohorts meet Sat and Sun for five weeks. Weekday cohorts meet Mon-Fri for two weeks. In the second half of the course, students will complete an instructor-led group project applying AI to the discipline of their choice (e.g., music, healthcare, astrophysics, finance, etc.), utilizing the programming skills they developed in the first half.Īll times are in Pacific Time please adjust for your time zone.Ĭohorts meet once/week for ten weeks. Students will not only learn about different types of machine learning models, but also apply those models to real data sets. In the first half of the course, students learn AI’s core technologies including applications, foundational concepts, and programming tools through live online lectures and coding labs. We will explore the foundations of machine learning and explore different applications of machine learning models. AI is already all around us today, and by the end of the program, students will understand the underlying concepts and motivations behind technology such as computer vision, natural language processing, and neural networks. Whether you’re interested in law, healthcare, art, or economics, AI is poised to transform every discipline and industry in the future. What do self-driving cars, Alexa, and iPhone's face recognition technology have in common? They are driven by modern advances in artificial intelligence. See Cohort Schedule in "More Details" orange button below 
Bring your college and career questions, review past class material, and attend special coding workshops!ĭates & Times: 10 sessions, 2.5 hours each. Open Labs and Special Sessions: Come and explore the exciting topics in AI that we couldn't pack into regularly scheduled class time.music, healthcare, astrophysics, finance, etc.) Students can use these projects in their résumés and college applications. Project-Based Learning: In our AI for Social Good project, students will be able to apply their newly acquired talents in a collaborative, challenging environment, applying AI to a domain they're passionate about (e.g.Hands-On Python Coding Develop valuable skills in Python, machine learning, and artificial intelligence in our hands-on coding labs, using cutting-edge research to solve real-world problems like breast cancer diagnosis, building self-driving cars, and more.Machine Learning Talks: Learn about machine learning algorithms and techniques in a uniquely interactive, engaging format, before you apply that knowledge in live coding labs.
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