Frequently Asked Questions About AI Degree Programs

A college education is a must-have qualification on the way to any career in artificial intelligence today.

AI and machine learning degrees are relatively new on the university scene, though. Some are being offered as their own majors; others are delivered as specializations tacked onto existing degrees like computer science, electrical engineering, or data science.

That lack of consistency leads to a lot of uncertainty for students who are trying to decipher the options in AI degree programs. Not only that, but the field is constantly changing. Answers that are correct for one semester may not still be true the next!

Below, we have all the up-to-date answers to the most frequently asked questions when it comes to applying for, studying, and paying for artificial intelligence degrees today.

Do I need to know any specific programming languages or tools before starting an AI degree program?

This is really two questions, with three different answers. Hang with us for a second, and we’ll explain.

The first is, do you need to know any specific programming languages or tools? That answer is no, although there are definitely some languages that are more common in AI development than others. An analysis by GitHub in 2019 of repositories involving machine learning turn up no surprises in the top 5:

  1. Python
  2. C++
  3. JavaScript
  4. Java
  5. C#

There are also some prestige languages that AI aficionados like to work with, like Haskell and Julia, which are newer and have features that lend themselves to ML/AI coding. There are also the classics, like LISP, developed by AI Founding Father John McCarthy specifically as the first language for working on AI. It’s still in use today, though not popular. R is also common in applied AI fields, like data science, financial modeling, and other statistically heavy uses.

There are AI projects in active development in almost every common programming language in use today.

You do need to know a programming language of some sort, however. If you had to pick one, Python is the stand-out choice in the field. Many of the most common libraries for deep learning and data science are coded in it:

  • NumPy
  • PyTorch
  • TensorFlow
  • Keras
  • OpenCV

The second question is do you need to know any of those tools or languages before you start an AI degree program? The answer to that depends on the degree program:

Are there online AI degree programs available?

Yes. Many, and perhaps even most, AI degrees today are available either entirely online or in a hybrid format.

An exception is at the doctoral level, where intimate and in-depth research and collaboration almost always require at least some in-person study. But the flexibility that comes with multi-year, highly individualized studies can often allow for extended remote work even at this level.

Are there scholarships or financial aid options available for AI students?

Yes. Financial aid is an option for any American college student. According to the National Center for Education Statistics, first-time, full-time undergraduate students at both public and private universities are overwhelmingly likely to be granted financial aid. Between 2010 and 2021, around 90 percent of students applied for and were awarded either grants, scholarships, or loans. The same is true for almost three-quarters of graduate students.

Most grants are offered through federal programs. It’s easy to check on eligibility at the official Federal Student Aid website. Most financial aid, whether public or private, is based on need. So if you can’t afford to pay out-of-pocket, you’re very likely to receive at least some amount of grant money. Student loans are also easy to qualify for and have fairly relaxed repayment terms.

Scholarships often have more specific qualifications. They may be offered based on:

There are a handful of scholarships specific to AI and ML studies. Most AI students are also eligible to tap into the more common STEM (Science, Technology, Engineering, and Math) scholarship offers.

Can I specialize in specific areas of AI, such as natural language processing, computer vision, or robotics?

Yes. It’s still very early days in the development of new branches and specializations in artificial intelligence and machine learning. Students with ambition and the right educational background are free to pick a path that interests them in the field. There is strong demand in all three of the specialization areas mentioned. Each has their own specific degree programs or concentrations in AI, as well as unique applications in multiple industries.

  • Translation
  • Summarization
  • Interactive assistance and customer service
  • Healthcare
  • Security
  • Transportation
  • Robotics

Each of these areas have their own unique educational requirements, career paths, and pay scales. But all are vital to the advancement of artificial intelligence today.

Do AI degree programs require students to have a strong background in mathematics or programming?

Yes, for the most part. There are real differences between admissions requirements and recommendations for undergraduate versus graduate AI degree programs, however.

For undergraduate AI degrees, typically the only actual requirement is to qualify for college admissions. Each school has their own set of qualifications for math, but most will require you to show at least three years of study advancing as far as Algebra II. Some also have a separate quantitative math study requirement. Colleges do not typically require any kind of programming experience for acceptance.

Of course, your life will be easier in college AI courses if you’ve gone further into calculus or picked up some programming skills as a high school student. Some AI bachelor’s programs may also require that you take specific college math classes before declaring your major, even if you have already met general admission requirements. Mainly, however, your undergraduate studies are built around developing the specific advanced math skills needed to succeed in AI.

For graduate AI degrees, advanced math and programming courses are usually listed as prerequisites for admission. Some programs may even require that applicants hold a bachelor’s degree in computer science, statistics, or other related STEM majors. At a minimum, most programs require:

Some practical experience is usually preferred, though not always required. Depending on the university, strong candidates who do not meet the prerequisites may be offered an opportunity to take them separately to qualify for admission.

How do I get a degree in AI? How hard is it to get a degree in artificial intelligence?

There is no question that degrees in artificial intelligence are not easy to earn, but with hard work and diligence any student can get one.

As far as qualifying for admissions, strong math and computer science skills are a definite plus. A focus on statistics, coding, and data structures will ease your studies of machine learning and AI.

It’s also worth noting that there are many different types of degrees in artificial intelligence, as well as different degree levels.

Associate’s degrees in artificial intelligence are better considered as the first half of a full four-year degree. They touch on basic concepts in the field, but don’t offer a complete education to qualify for most positions in AI today.

Bachelor’s degrees in artificial intelligence take four years to earn and cover most of the basic groundwork of advanced math, programming, and essential theory to get started in AI studies. They may qualify you for very entry-level roles as an AI programmer, trainer, or prompt engineer.

Master’s degrees in artificial intelligence take from one to two years and offer more advanced studies. They are considered essential qualifications for most AI engineering jobs today, and go into areas like deep learning and artificial neural network algorithm design.

Doctoral degrees in artificial intelligence can take anywhere from three to five years to complete. They are the top level of study in the field. Most research and development positions as well as leadership roles in the field require this degree level.

All these types of degrees are available with various concentrations in different AI specialties, such as computer vision, bioengineering, or robotics. They are already offered at a broad range of public and private universities, with more programs emerging all the time.

Is a degree in artificial intelligence worth it?

Do you really have to ask? We’re talking about a technology that is well on its way to completely transforming business, economics, and society as we know it. If you don’t think being a part of that transformation is worthwhile, what is?

But the real answer to the question depends on the context of the question.

Financially, AI is a field where salaries are already booming, and likely to continue to climb. The most elite players in computer science and information technology are flocking to AI, where paychecks are frequently well into six figures.

In terms of job security, the last roles that get replaced by robots will be the people who build the robots themselves. So that’s worth something. Of course, understanding the nuts and bolts behind the technology that will power all kinds of industries in the future is powerful job security. Not everything works out as planned with any new technology, and the truth is that jobs refining, debugging, and rebuilding AI will be around for as long as anyone entering the workforce today will be.

Morally, no matter what your stance on AI, participating in constructing a new kind of intelligence offers you the greatest leverage in how it is applied. Whether you are worried or excited about the reality of thinking machines, helping to build them is your best chance to create a better tomorrow.

Is an artificial intelligence degree hard?

For most people, a degree in artificial intelligence or machine learning is a heavy lift. At every level, AI degrees are steeped in heavy-duty mathematics, data, and programming concepts. You’ll even take a dip into some tough philosophical problems on the nature of consciousness, reasoning, and intelligence.

Yet graduates in the field point out that it’s important that AI degrees be tough. It’s a field where there are no easy answers. Facing challenges as a student helps prepare you to meet and overcome them on real-world projects.

It’s also an inclusive field where you will always find people willing to answer questions, review code, or offer pointers. Most universities that offer AI degrees come with extensive support systems. You’ll find tutoring, mentorships, and helpful resources easy to access when you hit the speed bumps on the intellectual expressway.

What are the core courses and subjects covered in an AI degree program?

Mathematics, probability and statistics, logic, and data structures and programming are all the core scientific areas that feed modern artificial intelligence development. Those are usually the central courses offered in undergraduate studies in AI.

For graduate students, those topics find a more specific focus as they are applied through coursework in:

AI degrees with different concentrations of course come with different coursework in their areas of specialization. But most of them still build on these essential classes.

What degree do you need to work in artificial intelligence?

Good question! The easy answer is a Bachelor of Science in Artificial Intelligence or a Master of Science in Artificial Intelligence, depending on what kind of job you want to work at.

But the real answer is that you can find positions in AI with a wide range of degrees. After all, formal degrees in artificial intelligence have only emerged in the past couple of decades. They have only been broadly popular for a few years. So most people working in AI today didn’t major in the field.

Some of the most advanced positions working in artificial intelligence are only available to graduates with a PhD.

Instead, common degrees among AI experts have included those in:

There are also many other fields that have come to artificial intelligence studies by different paths. These kinds of programs are often highly specialized, but as AI emerges as a powerful tool for addressing all kinds of challenges across industries, they are increasingly preparing graduates for AI jobs. Examples of those types of majors include:

Although they won’t prepare you for work in more general kinds of AI, they are turning out candidates who are working on AI in their respective fields.

What is an AI degree program, and what does it entail?

An artificial intelligence degree program is a college degree that prepares graduates to work in computer science and related disciplines to study, create, and manage machine intelligence.

Degrees are available at every level and have different requirements:

What is the difference between a degree in AI and a degree in machine learning, computer science, or data science?

A degree in artificial intelligence usually has a fairly broad spectrum of education that can prepare graduates for all kinds of different applications. They may be taken with specific concentrations that narrow those studies down to a particular industry or specialization.

A machine learning degree is focused primarily on the algorithms and data structures used to develop self-teaching systems. They include more focus on deep learning, neural networks, training systems, and the nuts and bolts of coding programs that learn from data. They may or may not involve broader artificial intelligence studies, since machine learning has applications outside of today’s AI focus areas.

Computer science degrees, on the other hand, are even more general than a degree in AI. Graduates may choose to specialize in AI, but they may also focus on other areas of computation and processing such as:

Data science degrees are entirely focused on data gathering, analysis, and presentation. They also include heavy helpings of machine learning studies.

Graduates from any of these types of programs can still find jobs working with artificial intelligence, however. The field both draws on the expertise of these subjects and is used to accelerate their effectiveness.

What types of AI degree programs are available, such as bachelor's, master's, or Ph.D.?


All the above are available. Each has different costs, educational objectives, and qualifies graduates for different types of work in the field.

Which degree is best for AI?

There is no single correct answer to this question. It all depends very much on what aspect of artificial intelligence you are interested in and at what level you plan to work in the industry. The best degree in AI is the one that you can afford that prepares you for the kind of career you will enjoy!

How much does an AI degree program cost, and are there scholarships or financial aid options available?

AI degrees are not usually priced any differently than other types of college educational programs. Looking at data from the National Center for Education Statistics (NCES), you can estimate the average total cost of tuition and fees for each level of AI degree:

In most cases, costs will be higher at private colleges or universities, and somewhat lower at public schools. The figures do not include cost-of-living or other expenses, such as textbooks or course materials.

Particularly at the master’s and doctoral levels, those amounts can vary depending on how long it takes you to progress through the advanced coursework. Whether or not you opt for a master’s before pursuing a PhD also matters. While it’s not required, if you do not earn a master’s first, you will typically earn one while getting your PhD… which adds years and expense.

The costs don’t necessarily exactly balance out—it can be more efficient to combine your studies, although also much tougher. The same is true of accelerated programs, which combine bachelor’s and master’s studies into a single five-year program.

Every university will have a financial aid office that can help students figure out all the various options for paying for those programs. There are many scholarship, grant, and loan programs available. Some are specific to AI, while others may be available to any college student. Frequently, other sources of financial assistance can be found in programs designed to support all types of STEM studies, or for minority or disadvantaged students.