Data Science and Artificial Intelligence: Introduction to Modern AI

Professor: Hartnett
Units: 0.5
Elective Course (Research Analysis and Design: Empirical Analysis)

This 10-week course will introduce and develop competence with modern AI/ML methods based in the neural network paradigm. The course is combination of theoretical instruction as well hands-on project work (“learning by instruction and doing”). The goals of this course are to:

  • Provide a rigorous statistical foundation for machine learning principles
  • Develop a facility with key machine learning models with a specific focus on differentiable models i.e. models implemented with artificial neural networks (NNs)
  • Gain some exposure to the history of the field and the current state-of-art (e.g. deep learning, GANs)
  • Develop an intuitive grasp of the strengths and limitations of the AI/ML paradigm