Heidelberg is one of only five colleges and universities selected nationally to collaborate with Google to pilot all three offerings in the new Applied Computing Series.
The Applied Computing Series is a new, three-course program that will increase students’ access to quality data science and machine learning education by leveraging new technologies and teaching styles. In partnership with Google, Heidelberg will offer two Applied Computing courses during the academic year and a third advanced course during the summer designed to offer non-computer science majors a crash course in data engineering and machine learning that they can apply to their own majors and areas of expertise.
Courses are taught using a “flipped classroom” model, where students review, study and practice material on their own, then work on collaborative projects in groups with coaching by their instructors. Google is building these robust 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 Heidelberg faculty in STEM-related fields.
- Skills that will position them for entry-level positions in the burgeoning machine learning workforce
- Opportunities to work with Google engineers to learn about the tech industry’s working environments, challenges and nuances
- Immersion in a project-based curriculum to help reinforce the computer and data science principles they’re learning
Applied Computing 101: Foundations of Python Programming
This introduction to computer science emphasizes problem solving and data analysis skills along with computer programming skills. Using Python, students learn design, implementation, testing, and analysis of algorithms and programs. Problems will be chosen from real-world examples such as graphics, image processing, cryptography, data analysis, astronomy, video games, and environmental simulation. Students get instruction from a world-class computer science professor, delivered remotely through video and interactive media. Prior programming experience is not a requirement for this course.
Applied Computing 201: How to Think Like a Data Scientist
This course introduces students to the importance of gathering, cleaning, normalizing, visualizing and analyzing data to drive informed decision-making, no matter the field of study. Students will learn to use a combination of tools and techniques, including spreadsheets, SQL and Python to work on real-world datasets using a combination of procedural and basic machine learning algorithms. They will also learn to ask good, exploratory questions and develop metrics to come up with a well thought-out analysis.
Applied Machine Learning Intensive
In this ten-week, full-time immersive experience, students will learn the fundamentals of machine learning to prepare for a role at the intersection of data science, computer science, and the individual student’s field of study or interest. Students will learn different machine learning tools and models; how to prepare and identify issues with data; and hone their coding skills in Python and SQL. Students will be immersed in project-based teams dedicated to exploring and solving data problems based on their own professional aspirations.
Why is Heidelberg partnering with Google on these new courses?
Heidelberg and Google are developing these courses to rethink the way traditional computer science is taught, as well as to prepare students for a relatively new career path in machine learning. The focus of the courses goes beyond teaching students how to code; they also teach data analytics and statistical techniques, as well as machine learning modeling in the more advanced course. All the courses combine these skills in hands-on, collaborative projects meant to solve real-life problems in the tech industry and beyond.
How will these courses work?
The courses implement a flipped-classroom style of teaching to support varied learning styles and maximize hands-on learning. Students will have the opportunity to apply the skills and concepts they’ve learned via in-class collaborative projects to solve real-world problems similar to those a team at Google might face. Students with interest in pursuing tech roles will have the added opportunity to connect and network with Google employees to learn about working environments, challenges and nuances in working in the industry. At the conclusion of the Applied Machine Learning Intensive, students will also have the opportunity to network with potential employers at poster sessions dedicated to the work students have completed over the course of the 10 weeks.
Why was our school chosen for this project?
Heidelberg is involved in this pilot program because of our successful track record implementing new programs with innovative teaching and learning methods. Google and the schools involved are also interested in investigating new, economically efficient approaches to reaching more students.