Academic Programs

Applied Computing Series

Data Analytics

The Applied Computing Series in collaboration with Google, teaches the foundations of computer and data science through hands-on, project-based coursework, topically designed to attract students who might not consider themselves destined for a technology career. The courses leverage the 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.

Students participating in the program will:

  • Gain exposure to computer and data science and develop skills that can be applied to their own majors.
  • Work with Google employees 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. The first course, Foundations of Python Programming, is being offered as a traditional course on campus this fall; the second course, How to Think Like a Data Scientist, will be offered in the spring.

The following courses are taught by Lasell College faculty with guidance from the Google Engineering Education team.

Applied Computing 101: Foundations of Python Programming

This introduction to computer science, developed by Google and their university partners, 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. And within the context of programming, they will learn to formulate problems, think creatively about solutions, and express those solutions clearly and accurately. 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 and attend class for collaborative team projects to solve real-life problems, similar to those a team at Google might face. As part of the course, students also hear from Google engineers about their careers in the tech industry and learn how they can prepare for similar careers. Prior programming experience is not a requirement for this course.

Applied Computing 201: How to Think Like a Data Scientist

How to Think Like a Data Scientist 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. Presenting and discussing an analysis of datasets chosen by the students will be an important part of the course. Like AC101, this course will be "flipped," with content learned outside of class and classroom time focused on hands-on, collaborative projects.

Request more information about the Applied Computing Series :

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