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Google Collaboration

Bay Path University is now collaborating with Google to offer computer science, data science, and machine learning courses to its undergraduate students.

We are one of only four colleges and universities selected nationally to collaborate with Google to pilot all three offerings in their new Applied Computing Series. The courses aim to increase undergraduate access to quality data science and machine learning education by leveraging new technologies and teaching styles.

The Applied Computing Series teaches the foundations of computer and data science through hands-on, project-based course content, topically designed to attract students who might not consider themselves destined for a technology career. The most advanced of these offerings, the Applied Machine Learning Intensive will be a 10-week summer program designed to offer non-computer science majors a crash course in data engineering and machine learning they can apply to their own majors and areas of expertise. All of the courses leverage tools and techniques used at Google and in the wider tech industry, while also teaching the non-tech skills needed to be successful at work more generally: critical thinking and problem-solving, collaboration, and the ability to communicate and network.

The learning content for the Applied Computing Series is distributed via a “flipped classroom” model of instruction, where students review, study and practice material on their own, then work on collaborative projects in groups with coaching by their instructors. To develop the most robust curriculum, Google is building these courses in partnership with highly-regarded computer science academics. The Google instructional team builds the centralized content and in-class projects so that students have relevant, real-world problems to solve; the courses are then facilitated by Bay Path University faculty in STEM-adjacent fields.

Students participating in the program will:

  • Develop skills that will position them for entry-level positions in the burgeoning machine learning workforce;
  • Work with Google engineers to learn about the tech industry’s working environments, challenges and nuances;
  • Immerse themselves in a project-based curriculum to help reinforce the computer and data science principles they’re learning.