DigiPen Institute of Technology is excited to introduce a brand new degree program starting fall of 2019 — the Bachelor of Science in Computer Science in Machine Learning.
Machine learning, a term coined by computer science pioneer Arthur Samuel in 1959, refers to the “field of study that gives computers the ability to learn without being explicitly programmed.” Nearly 60 years since Samuel defined it, the field has grown exponentially. The ability to predict and discover insights, patterns, and efficiencies in the world around us through data and computational algorithms has found applications in healthcare, self-driving vehicles, digital entertainment, software development, robotics, finance, marketing, science, and beyond.
“Now is the right time,” program director Samir Abou Samra says of the program’s introduction. “Today, with cloud computing, increasing computational power and efficiency, everyone wants to predict and guess what the next move should be. Machine learning is about optimizing solutions, and there is a lot of work that needs to be done there. So what we’re doing that is new, to meet that demand, is teaching machine learning at the undergraduate level.”
Long taught as a specialized topic at the master’s and doctorate level, DigiPen’s machine learning program will be among the few offered as a four-year bachelor’s degree. Building on DigiPen’s established computer science and math curriculum, graduates will enter the industry as skilled computer and data scientists with an in-depth understanding of predictive modeling and the three bedrock methods (supervised, unsupervised, and reinforcement learning) foundational to the field of machine learning.
Although DigiPen’s BS in Computer Science in Machine Learning program is a new addition, the institution’s history in the field actually stretches back to 1984, four years before DigiPen was even established. That year, DigiPen founder Claude Comair began work on the “VU” computer language during his research as part of Osaka University’s engineering faculty. The computer language, which incorporated machine learning concepts, allowed architects and graphic designers to create virtual 3D primitives for buildings and cities based on simple data input. The language was also used to simulate events, such as natural disasters, and their effects on those structures and populations.
Two decades later, in 2005, DigiPen’s internal Research & Development team adapted the same basic framework of VU toward the development of another language called the Human Behavioral Description Language (HBDL). Initially designed as a project for The Boeing Company, HBDL was used in machine learning applications as means of simulating and predicting human behavior for a multitude of real-world scenarios. The success of the project led Boeing to award DigiPen with its 2008 “Supplier of the Year” award in technology.
Concurrently, beginning in 2006, DigiPen Research & Development also began working with the Renault Sport Formula One Team to develop a new software platform supported by machine learning. The result was a “race dashboard system” that captures and analyzes a wealth of real-time vehicle data during Formula One races in order to predict the outcomes of various strategies — all based on current, and potential future, race conditions. By enabling drivers and strategists to make smarter decisions, the software led to 40 podium finishes from the 2008 season onward, also prompting a 2015 partnership with Andretti Autosport to bring similar technology to the North American IndyCar Series.
Although machine learning has traditionally been taught as a high-level subject, and its real-world applications have grown increasingly complex, director Abou-Samra emphasizes that DigiPen’s new program is designed for students starting from ground zero. By the end of the program, he says, students will acquire both the knowledge and hands-on experience of how to design, implement, and manage machine learning systems for a wide variety of applications and industry needs.
“Any student with good math skills and an interest in computer science and forecasting is a good fit for this program,” Abou Samra says.
Learn more about the Bachelor of Science in Computer Science in Machine Learning program. Applications are currently open for the Fall 2019 semester.