A master’s degree in artificial intelligence provides the necessary training, and background for students to launch a successful career in the exciting and growing field of artificial intelligence.
This guide contains a comprehensive background on the latest artificial intelligence master’s programs, online artificial intelligence master’s programs, and what to expect from the curriculum.
Why Pursue a Master’s Degree in AI?
Artificial intelligence (AI) is the science of teaching machines to think for themselves. One of the largest domains within AI is machine learning (ML). ML teaches a program to build a model for decision-making based on training data. Using feedback and trial and error, these programs can develop the ability to make decisions for themselves without external input.
AI and ML can make a big difference in many different fields. Computers are much better at processing large amounts of data and seeing patterns than people. This is an invaluable skill in many industries where making accurate predictions and data-driven decisions are vital to profitability.
The growing demand for AI specialists and data scientists makes a master’s degree in AI a good investment. Many top firms are snapping up qualified professionals with AI skillsets as quickly as they can find them, and having an advanced degree in the field helps to stand out from the crowd.
Additionally, specialists in ML and AI have the potential to work on a bunch of cool projects. Initiatives for developing flying and self-driving cars, advanced surgical and medical diagnostic tools, and other technologies all require ML and AI. By building skills in these fields, it’s possible to be on the cutting edge of science and work in various fields.
What Does a Master’s in AI Program Look Like?
A master’s degree program in AI provides a student with durable skills in AI. While many courses and resources exist for ML and AI, they are often focused on solving a specific task with high-level algorithms and skills. AI Master’s degree programs provide a student with an understanding of the theory and applications of AI, enabling them to apply their knowledge to a wide range of potential problems.
Like most Master’s programs, a graduate degree in AI will take 1-2 years for a full-time student to complete. Some of the courses that a student should expect to take include:
- Applied AI
- Deep learning
- Theoretical AI
- Data science
- Probability and statistics
An AI degree program aims to prepare students to use their knowledge and skills to solve real-world problems. For this reason, AI Master’s programs commonly include a hands-on component and coursework.
This may be in the form of an internship, co-op, capstone project, or independent research project.
Online master’s degrees in AI and ML are essentially the same as their on-campus counterparts. Students need to meet the same admissions requirements and take the same courses to achieve their degrees.
The main difference between online and on-campus master’s degrees in AI and ML is the delivery of the course content. Instead of sitting in the classroom, online students will take their courses over the Internet. This can provide a few advantages over an in-person degree program, such as:
Artificial Intelligence Degree Requirements
A master’s degree in AI can be very technical and theoretical. The program’s goal is to help students learn to apply existing knowledge and skills to AI problems. Some skills that students are likely to expected to have going into the program include:
- Programming: AI and ML implement self-learning systems as computer programs. A master’s student in AI is expected to know how to program before pursuing the degree.
- Probability and statistics: AI is applied probability and statistics. Students need to know the basics of these fields so they can learn to use this knowledge as part of their degree program.
In addition to certain knowledge, making it through the application process for a master’s in AI will likely require the following:
- Bachelor’s degree: Most MS in AI programs require an undergraduate degree in Computer Science, Mathematics, or a related field. This demonstrates that students have the fundamental theoretical knowledge necessary to succeed in the program.
- GRE or GMAT: Many schools require applicants to take the Graduate Record Examinations (GRE) or Graduate Management Admission Test (GMAT) with a certain minimum score for admission into a graduate degree program.
- Transcripts: These are commonly required as part of the admissions process to prove that an applicant holds an undergraduate degree and has completed any necessary prerequisites.
- References: Master’s programs commonly require references from teachers or other parties who would be familiar with the applicant’s knowledge and work.
Paying for a Master’s Degree in AI
Tuition for a master’s degree in AI can vary greatly depending on the school. Tuition is impacted by a number of different factors, including the quality of the school and degree program, whether the student is pursuing the degree online or in-person, and geographic locations.
When pursuing a Master’s in AI, a student doesn’t necessarily have to pay for the full tuition themselves. Some options for paying for at least part of your degree include:
- Financial Aid: Many schools offer financial aid to qualified students. This can offset some or all of the cost of a Master’s degree program.
- Scholarships and Fellowships: In addition to need-based financial aid, students may also be eligible for scholarships and fellowships based on academic performance and other factors.
- Assistantships: Many schools offer graduate students the option to offset their tuition with an assistantship. A graduate assistant may help a professor teach their classes or participate in their research, both helping to pay for their schooling and gaining valuable experience.
- Corporate Programs: Artificial intelligence and machine learning are skill sets that are in high demand in many industries. This means that a student’s employer may be willing to cover some or all of the costs of their schooling to help them to develop the knowledge and experience that the business needs.
Career Paths with a Master’s in Artificial Intelligence
With a Master’s in AI, a student can pursue a number of different job roles in information science. Some common job titles include:
- AI specialist or developer
- ML engineer, researcher, or specialist
- Data scientist
- Robotics engineer
- Software engineer
According to Payscale, a degree holder of a master’s in AI should expect to earn an average of $102,906. The Bureau of Labor Statistics claims that the median pay for computer and information research scientists is $126,830. These salaries are significantly higher than the average salary of a BS in Computer Science (a common entry point into the degree), which is $86,675. The salary difference and the cost of a degree mean that an MS in AI can pay itself off in as little as 1-2 years.
In addition to a salary hike, holders of an MS in AI look forward to entering a rapidly-growing job market. The BLS anticipates a 15 percent growth in Computer and Information Research Science, which is significantly faster than the average field. Additionally, students with a solid grounding in AI can likely expect to be snapped up by top tech companies always looking for AI talent.
Master’s in Artificial Intelligence FAQs
A master’s degree in AI makes a number of career paths open up that would otherwise be unavailable. Another important consideration is earning potential. The difference in salary between someone holding a master’s degree in AI versus someone with a bachelor’s in computer science (commonly an entry point to the program) can pay off the degree in a couple of years.
A master’s in AI program is designed to provide students with the theoretical knowledge and hands-on experience necessary to use artificial intelligence and machine learning effectively. With the degree, a student can pursue careers in AI or data science in a number of different fields.
Typically, a full-time student can complete a master’s program in one to two years. Students pursuing the degree part-time might take three to four years, depending on the number of courses taken per term.