Artificial Intelligence Colleges: Which are Best in 2023

The first step on most people’s AI career path is to enroll in a college degree program that will provide the necessary training to set them up for success. But now more than ever, there are lots of options out there, all purporting to offer the “best” AI education.

In this article, we’ll take a look at the state of AI colleges before diving into what it means to be “best” and how you can choose the best program for you. Along the way, we’ll preview some great AI programs from across the country.

What’s the AI higher education landscape look like today?

The AI market’s growing rapidly,  with Grand View Research projecting it to expand by over 40% to over $900 trillion worldwide by 2028. With the growth of the market, so grows the AI workforce. According to Indeed, demand for those with AI skills and expertise more than doubled from 2015 to 2018, and there’s no sign this demand will slacken in the coming years. 

The growing AI market is offering lucrative salaries to those who can help it grow: Glassdoor pegs the median artificial intelligence engineer salary at $119,640 annually, and for a machine learning engineer, that median salary climbs to $124,040, both eclipsing the 2020 median US household income of $67,521.

Given the booming job market and high earning potential of a career in artificial intelligence, it makes sense that today more than ever, aspiring technologists are flocking to colleges and universities to get an artificial intelligence degree. It’s also no surprise that universities and other educational providers are increasingly seeking to provide high-quality AI & ML instruction, both in existing computer science departments and through new, standalone artificial intelligence and machine learning programs.

Student growth in the field is noticeable from the undergraduate level on up. Stanford University’s AI Index found the number of courses offering undergrads instruction in developing practical AI and ML models to have more than doubled over the four academic years from 2016 to 2020. 

Enrollment at these schools has also grown considerably in introductory courses in artificial intelligence and machine learning, increasing by 60% over the same time frame. And Stanford notes that almost 30,000 students graduated with an undergraduate computer science degree — the most common form of artificial intelligence degree — in 2019 in North America alone, three-fold growth over 2010. 

While not all of these students graduated with AI- or ML specializations, together with course-offering data this paints a picture of robust participation in artificial intelligence and machine learning at the undergraduate level.

While the growth in course offerings at the graduate level has been more modest — around 40% over the same four years — graduate programs have seen substantial growth in the number of tenure-track faculty who specialize in AI, with over 60 new professors joining the ranks of the 18 schools surveyed. 

The market is justifying that demand for qualified professors: as we mentioned above, computer science Ph.D. students are increasingly specializing in artificial intelligence and machine learning. Indeed, as the number of CS Ph.D. students tripled over the ten years leading up to 2020, students within this group working in artificial intelligence, machine learning, or robotics grew by over 10% and now make up over 20% of all new CS PhDs. Of course, these data miss the many graduate students working in the new AI and ML-specific Master’s and Ph.D. programs that are launching every academic year.

What’s our approach?

This is where we come in. We know there are lots of different artificial intelligence colleges out there and millions of bright young people seeking an artificial intelligence degree (or, as it happens more often, a computer science degree with an artificial intelligence concentration). With this in mind, in rounding up our best colleges for artificial intelligence, we’ve sought to feature a broad swath of programs, all of which are stellar but differ in the following ways:

• Reputation

• Size

• Focus (e.g. machine learning, computer vision, data analytics, computer engineering, etc.)

• Geographic location

• Modality options

• Price

Below, you’ll find the big names you would expect to find on such a list, but you’ll also find some great options that provide quality AI instruction at a fraction of the price. In all, we’ve chosen eight schools — four private universities, four public universities — spanning every region of the US and, with remote options, anywhere with an internet connection. They are:

• Carnegie Mellon University

• Massachusetts Institute of Technology

• Stanford University

• Cornell University

• University of Illinois, Urbana–Champaign

• Georgia Institute of Technology 

• University of Texas – Austin

• University of Washington

In assembling them, we’re not looking to push you in one direction or another, but rather give you some basic information about each to make your decision — because it is your decision — easier.

We’ve just laid out some great schools offering exquisite instruction in AI — but how do you know which one is right for you? Here are some things to keep in mind:

Admissions Requirements & Prerequisites

Before you fall in love with a program and start assembling your application, it’s crucial to ascertain whether your application will be welcome. When schools list requirements and prerequisites for study, they mean it. Their top priority is turning out stellar artificial intelligence professionals (or data scientists, information technology professionals, etc.) who will make an impact, whether in research or industry. Accordingly, they will only accept students who show an aptitude to thrive in their program.

Often, “aptitude to thrive” can be reduced to particular numbers — GPA, SAT, or GRE scores — combined with demonstrated interest or experience through coursework, work history, or a personal statement.

Of course, there might be exceptions if you are a fringe case — especially if you have a compelling reason or an interesting story. When in doubt about whether you fulfill the requirements, there’s no harm in sending the admissions director, the department chair, or even an assistant professor an email inquiry before you invest time in an application.

Curriculum Specifics

Not all AI programs are created equal: artificial intelligence courses offered will differ based on the strengths of the faculty, the department’s vision for the program, and even a school’s location and the nearby industry connections it can cultivate.

When researching programs, you don’t need to already have an idea of where exactly in artificial intelligence you want to end up. It’s useful, however, to be self-aware if you have an idea of where you want to end up. If you’re just looking to build a baseline in AI and go from there, make sure that the programs you apply to are heavy on broader core survey courses. If you already have an inkling of what you want to focus on in your career — if, for example, you want to be a data scientist, work in software engineering, or engross yourself in deep learning — make sure you apply to programs that can get you there through electives, internship connections, and research opportunities.

A university department is also looking for a good fit, listing its curriculum on its website to make interested students’ jobs easier. In addition to checking out these curricula, look at the make-up of the faculty to determine the strengths of the department and even identify potential formal or informal advisors. You might also seek to connect with program alumni on LinkedIn to hear their side of things and learn where they ended up. 

Industry Relationships

While we’ve already touched on this, it bears repeating: one of a program’s biggest advantages comes in the industry relationships they cultivate. These relationships yield not only internship opportunities, but potentially also job pipelines.  When looking at programs, check to see if they’ve listed industry relationships on their website, or email the department directly to inquire. Failing this, you might again take to LinkedIn to see whether alumni list internships they had during their studies. Often, this can be a good indicator that there is an existing relationship between a school and the company.

Location and Learning Modality

Do you want to stay close to home? Explore a new region of the country? Lose yourself in a big city? Settle down in a cozy college town? The location should play a key role in your decision-making process — especially if you live in a state with a great state college and can take advantage of the drastically reduced tuition.

Or maybe you don’t want to leave your couch. If COVID has had any upside, it’s that it has offered proof of concept that online learning can be just as effective as learning in person — and at a fraction of the cost. If you’re not interested in relocating or having a robust campus experience, or if you’re looking to continue working as you study, prioritize colleges that offer online programs, like Georgia Tech.

Student Outcomes

Before even applying to a program, you want to be sure it will get you where you want to go — there’s no use spending time and money on education if you won’t recoup this investment with a great career in AI. Oftentimes, departments will proudly list alumni placement on their websites. You might also (again!) hit up LinkedIn to see where alumni have ended up.

Cost

Last, but certainly not least, you want to factor a program’s cost into your calculations. When doing so, take into account not just the cost of tuition, but of relocation, living expenses, and, if you will stop working to study, lost income potential, and balance these against what you’ve learned about student outcomes and average salaries for the specific roles a school’s program might prepare you for. As we’ve said before, you might also consider a state school or online program, for tuition will generally be markedly lower.

It’s also crucial to look into any scholarships or grants a department or university might offer you. While places in such programs are competitive, you might also try to gain admission to one of a handful of partially- or fully-funded master’s programs in computer science that allow you to pursue artificial intelligence while receiving a tuition remission and/or earning a modest stipend for serving as a research or teaching assistant.

How Else Can We Help?

With so many factors at play, it’s easy to get overwhelmed when deciding on a program. Ultimately, the decision will be yours: you’re the expert on your current situation and your goals for the future. But to make your research and decision easier, we’ve assembled some top-notch information on AI careers, education, and the field as a whole. As you continue researching, take some time to read through the articles — regardless of your particular background, you’re bound to find something to help you move forward in your thinking.

To get started, take a deep dive into the future of machine learning. And as a bonus, we’ve just dropped our collection of the best AI scholarships.