Introduction to Machine Learning and Artificial Intelligence

Credits: 3

Prerequisites: CS 101, MA 225, MA 226

Introduction to machine learning and artificial intelligence applications and methods. Machine learning tasks will include regression, classification and clustering. Machine learning algorithms studied will include linear regression, logistic regression, decision trees, neural networks, principal component analysis, K-means clustering. Concepts covered will include training, testing and cross-validation. Other areas of AI introduced will include strategy games, natural language processing, computer vision, and robotics. The course will end with an introduction to the ethics of AI and ML.

Course Overview & Topics

• key concepts, software, etc

Professors

• John Doe
  • specific advice
  • workload, assessments, teaching style
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Resources

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