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Machine learning is an exciting field of data science that relies on computational algorithms as a means of discovering new insights, patterns, and connections in the world around us. Instead of explicitly programming a computer’s behavior, we teach computers to forge complex neural pathways that imitate a “thinking” brain. Through its wide-ranging applications, from speech recognition software to teaching driverless cars how to safely navigate our complex traffic systems, ideas that were once considered futuristic are swiftly becoming reality.

The BS in Computer Science in Machine Learning program focuses on predictive modeling and core machine learning algorithms, as well as on various paradigms such as artificial neural networks and deep learning. You’ll explore applications ranging from natural language processing to computer vision as you learn to draw meaningful conclusions from large distributed data sets.

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Who Should Pursue This Degree?

The BS in Computer Science in Machine Learning program is our newest degree and is intended to give students a more direct path into emerging career opportunities at the intersection of data science and software engineering. Long taught as a specialized topic at the master’s and doctorate level, DigiPen’s machine learning program is among the few offered as a four-year bachelor’s degree. For those who want to experience the same proven curricula of DigiPen’s other computer science programs — while also pursuing a specific career interest in data analysis and predictive modeling — this program could be a good fit.

As a student in this program, you will:

  • Become a Proficient Software Engineer

    Dive deep into core programming languages as you tackle coursework in data structures, algorithm analysis, operations research, and more.

  • Design Your Own Machine Learning Applications

    Become well-versed in designing, implementing, and managing machine learning systems for a wide variety of applications and industry needs.

  • Gain Experience in a Collaborative Studio Environment

    Learn how to collaborate with others on a shared codebase as you solve problems and tackle the challenges of software development.


Academic Roadmap

The BS in Computer Science in Machine Learning curriculum includes a heavy emphasis on computer science and mathematics. While the first year of the program follows the same structure as DigiPen’s other Bachelor of Science programs, you will quickly work your way toward learning about the three main categories of machine learning (supervised, reinforcement, and unsupervised) and advanced math coursework involving probability and statistics, data science, and numerical analysis. Throughout the program, you’ll also be working with your peers on team-based computer science projects that challenge you to design and build innovative tools and software applications that incorporate machine learning solutions.

View a sample course sequence

Admissions Requirements

In order to apply for the BS in Computer Science in Machine Learning program, you should have a strong foundation in math, science, and problem-solving. You’ll need to have completed precalculus (or its equivalent) prior to attending DigiPen.

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Topics Covered

Students in the BS in Computer Science in Machine Learning program will learn how to:

  • Tackle real-world problems by analyzing them and determining which combination of techniques can be used to provide general purpose solutions.
  • Implement basic and advanced machine learning algorithms from the ground up to understand their respective strengths and target applications.
  • Understand the math concepts behind many machine learning techniques and look for optimizations.
  • Extract meaningful information from raw data.
  • Consider the professional, ethical, legal, and security implications of data science and its impact on society and individuals.

Career Outlook

Graduates of this degree program will be prepared to enter technical industries as entry-level data scientists or software engineers.

Potential Careers

Data Scientist

The role of a data scientist is to collect, analyze, and make sense of large amounts of data — finding trends, discovering patterns, and identifying potential new strategies and solutions as a result. Data scientists often rely on a combination of computer science and machine learning knowledge to devise new methods of data analysis.

Application Analyst

An application analyst is responsible for supporting and maintaining the functionality of a company’s bespoke software infrastructure. In particular, they use their knowledge of these software systems and applications to diagnose problems and determine appropriate solutions.

Software Development Engineer

Software development engineer (SDE) positions can be found in any number of industries. The role of an SDE is typically to design and build computer systems and software — either from scratch or by modifying existing systems and codebase.