Artificial Intelligence Foundations
Artificial Intelligence Foundations builds an applied understanding of topics in Artificial Intelligence. Some basic knowledge of math and statistics is necessary to take this course. Interactive applets within the course material build dynamic data visualizations and explore new concepts. At the end of the course, students will have knowledge of key AI concepts like supervised learning, unsupervised learning, decision trees, artificial neural networks, and commonly used ensemble techniques.
Artificial Intelligence Foundations builds an applied understanding of topics in Artificial Intelligence. Some basic knowledge of math and statistics is necessary to take this course. Interactive applets within the course material build dynamic data visualizations and explore new concepts. At the end of the course, students will have knowledge of key AI concepts like supervised learning, unsupervised learning, decision trees, artificial neural networks, and commonly used ensemble techniques.
Overview
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What You Will Learn
- Apply fundamental concepts in artificial intelligence, including supervised and unsupervised learning methods, decision trees, and artificial neural networks.
- Analyze complex datasets exploring relationships between variables and identifying potential insights that can inform AI model development.
Course Highlights
- Interactive Course Book and Aplets to support learning