Artificial Intelligence Degrees: What Do You Need to Apply?

Artificial Intelligence Engineer

An AI engineer leverages artificial intelligence to design, develop, and deploy solutions to problems that impact everyday people and everyday life. Artificial intelligence engineers might focus on one area of artificial intelligence — like computer vision to improve self-driving cars, natural language processing to improve auto-translators, or deep learning to improve investment strategy — or work as a generalist. Though you will find job postings out there for artificial intelligence engineers, often individuals with these responsibilities have titles like software developer, software engineer, AI specialist, or AI engineer.

According to Glassdoor, the median AI engineer salary in the US is $126,639. You can also read more about the role in our artificial intelligence engineer career guide.

Machine Learning Engineer

A machine learning engineer is responsible for designing, developing, and shipping machine learning models — and then maintaining them once they are shipped and deployed to a live product. Just like an AI engineer, an ML-specific engineer might work on a team focused on building a particular product or feature, or they might work as a generalist and move between a variety of different types of projects. In addition, machine learning engineers can be responsible for managing data systems and undertaking various kinds of data analysis, such as analyzing data sets from A/B tests on a machine learning system or algorithm.

According to Glassdoor, the median machine learning engineer salary in the US is $129,869. If this path interests you, see our guide on how to become a machine learning engineer.

Data Scientist

A data scientist ideates and executes novel approaches that turn raw data into business insights and solutions. After understanding business needs, they determine what types of data are relevant in addressing those needs and what kinds of questions need to be asked of this data, and then help develop machine learning models and other predictive analytics to efficiently carry out this analysis. After the analysis, a data scientist is usually responsible for communicating results to relevant stakeholders.

According to Glassdoor, the median data scientist salary in the US is $124,286.

Undergraduate Degree Application Requirements

While in Europe or the United Kingdom those seeking an undergraduate degree will often apply to a particular major within a university, in the US, high schoolers usually apply to — and are accepted by — a university or college as a whole, not a specific major. Only later, in their second or third year of college, do these students then declare a major. This is not to say that a student’s academic profile and personal statements don’t play a factor in admissions decisions, just that more often than not undergraduate computer science or artificial intelligence programs won’t have specific application requirements from the get-go.

The upshot? If you are looking to earn a bachelor’s in artificial intelligence, then find a school with a program that appeals to you — we have some great suggestions — and head to their undergraduate admissions page to see their application requirements.

Generally, prospective bachelor’s students are required to submit: high school transcripts; standardized test scores, such as SAT or ACT scores when required; up to three letters of recommendation, including from a high school guidance counselor; a personal statement; school-specific supplementary essays; a school-specific online application or the Common App; proof of English proficiency through TOEFL, IELTS, or Duolingo English Test for certain international applicants; and an application fee.

Graduate Degree Application Requirements

Different from the bachelor’s application process, individuals seeking admission into graduate degree programs in artificial intelligence, whether terminal master’s or Ph.D. programs, will apply to the specific programs, and so will have to keep in mind the particular requirements of each.

Generally, prospective master’s and Ph.D. students are required to submit: transcripts from each university attended; undergraduate GPA, often with a program minimum such as 3.0 or higher; GRE scores when required; three letters of recommendation; a current resume or curriculum vitae; a statement of purpose describing reasons for entering graduate study, including career goals; sometimes a personal statement describing how personal background motivates the decision to enter graduate study; an online application; proof of English proficiency through TOEFL, IELTS, or Duolingo English Test for certain international applicants; and an application fee.

As graduate study is far more advanced than undergraduate study, graduate degree programs will additionally require applicants to be able to demonstrate proficiency in advanced mathematics, including probability, statistics, and linear algebra; basic computer science, including fluency in at least one programming language like Python or R; and familiarity with key artificial intelligence concepts like machine learning, deep learning and neural networks, big data, human-computer interaction, and others.

Applicants can demonstrate this proficiency through their academic history, work experience as a data analyst, computer programmer, or even information technology (IT) professional, or some combination of the two.

In the US, doctoral students are generally accepted to hold only a bachelor’s degree, with the understanding that they will earn a master’s degree en route to the doctorate. Accordingly, Ph.D. applicants are required to demonstrate proficiency in the above areas, but not necessarily to a greater extent than terminal master’s applicants. Ph.D. applicants, however, will need to demonstrate aptitude for both the rigor of doctoral study and independent research. This can be shown through GPA, recommendations, transcripts, independent projects, participation in computer science and artificial intelligence conferences, and publication history. If you are thinking of applying to a Ph.D. program, it’s a good idea to get in contact with a faculty member (or several) to gauge your fit and begin building relationships.