Advances in machine learning algorithms, growth in computer processing power, and access to large volumes of data make artificial intelligence possible. Recent advances flow from the development of deep learning methods, which are neural networks with many hidden layers. Artificial intelligence builds on machine learning, with computer programs performing many tasks formerly associated with human intelligence. Students in this specialization learn how to move from the traditional models of applied statistics to contemporary data-adaptive models employing machine learning. Students learn how to implement solutions in computer vision, natural language processing, and software robotics.

Curriculum

Core Courses (8 units)

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Students need to choose one of these eight course options to fulfill the business, leadership, communication requirement.  A student cannot fulfill a core and specialization requirement with the same course.

 

 

Specialization Courses (4 units)

About the Final Project

As their final course in the program, students take either a master's thesis project in an independent study format or a classroom final project class in which students integrate the knowledge they have gained in the core curriculum in a team project approved by the instructor. In both cases, students are guided by faculty in exploring the body of knowledge of data science. The master’s thesis or capstone class project count as one unit of credit.