As of right now, I’m double majoring in two things at Virginia Tech: Statistics, and Computational Modeling and Data Analytics (Big Data). I could provide major and course descriptions for these majors if need be, but CMDA contains courses like Calc 1-3, Linear Algebra, Diff Eq, Stat Methods, Probability, Software Design, Data Structures, Math Modeling, Python, Intro to Data Visualization and Data Analytics, and Intro to Machine Learning as it’s core classes. But people have been telling me that CS would have been a better major to pursue in order to pursue a career in machine learning. Is this true, or should I be okay?
Sorry for the lengthy post!!
It probably depends on exactly what you want to do. The more important thing would be whether you have the prerequisites for an AI or ML program.
Artificial intelligence is a subfield of computer science, and most AI programs are either going to be concentrations of an MS in computer science or a standalone degree within a computer science department. So computer science would likely be the traditional major for this pursuit. You could probably do quite well with major in statistics and CMDA, especially if you are interested in mathematical applications to AI or the use of machine learning in data analytics and statistics - but you would most likely need to take more computer science courses as prerequisites. Here is what CMU’s MS in CS has to say:
The M.S. in Computer Science offers students with a bachelor’s degree the opportunity to improve their training with advanced study in computer science. We cater to students with basic analytic skills and a strong aptitude for mathematics, programming, and logical reasoning. You don’t need a bachelor’s degree in computer science specifically for the program, but a technical undergraduate background will set you up for success.
AI programs also sometimes like to see coursework in psychology, philosophy, and linguistics, such as UGA’s MS in artificial intelligence:
No specific undergraduate major is required for admission, but admission is competitive. We are looking for students with a strong preparation in one or more relevant background areas (psychology, philosophy, linguistics, computer science, logic, engineering, or the like), a demonstrated ability to handle all types of academic work (from humanities to mathematics), and an excellent command of written and spoken English.
Machine learning is also usually a concentration in computer science or a program offered from a CS department, but it is often a hybrid program of statistics and computer science and so a statistics + CDMA degree would be excellent preparation as long as you have the computer science basics you need. Here are CMU’s program’s requirements:
Incoming students must have a strong background in Computer Science, including a solid understanding of complexity theory and good programming skills, as well as a good background in mathematics. Specifically, the first-year courses assume at least one year of college-level probability and statistics, as well as matrix algebra and multivariate calculus.
At some universities, machine learning can be pursued from a lot of departments. For example, at Duke, you can pursue ML from computer science, ECE, math, statistics, and computational biology. So your background would also be fine.