How to Get a Degree in Artificial Intelligence

05/26/2026

A Step-by-Step Guide to Earning an Artificial Intelligence Degree

Artificial intelligence is widely used in modern technology applications. From digital assistants and recommendation systems to advanced analytics and robotics, artificial intelligence (AI) is shaping how software operates in many industries. As interest in the field continues, many prospective students are researching how to get a degree in artificial intelligence and what education paths may help them study AI in depth.

An artificial intelligence degree combines computer science, mathematics, and data science with specialized topics like machine learning, deep learning, and computer vision. Programs may focus on developing technical skills, problem-solving abilities, and an understanding of how intelligent systems process data.

If you’re interested in AI education, explore typical degree options, what you may study in an AI program, and how to prepare for an artificial intelligence degree.

Artificial Intelligence Degree Overview and Key Concepts

Artificial intelligence programs typically focus on the technology behind intelligent computer systems. These systems are designed to analyze data, identify patterns, and perform complex tasks such as language translation, image recognition, or predictive analysis.

Many AI degree programs are structured around three core academic areas:

Computer science, which provides the foundation for programming and algorithms
Mathematics, including calculus and linear algebra, is used to design models
Data science, which focuses on data analysis and machine learning methods

AI learners often study how software systems interpret data, develop predictive models, and apply machine learning to real-world problems.

Artificial intelligence degrees are increasingly available at multiple academic levels:

Bachelor’s degree programs
Master’s degree programs
Doctoral or research programs

Some institutions may also offer certificates or specialized tracks in artificial intelligence.

Why Get a Bachelor’s Degree in Artificial Intelligence

A bachelor’s degree is a common starting point for students who want to build foundational AI knowledge. Undergraduate programs typically focus on both theoretical concepts and practical skills used in AI development.

Students pursuing a bachelor’s degree in artificial intelligence may study:

Programming and software development
Algorithms and data structures
Machine learning and data analysis
Artificial intelligence systems design
Mathematics and statistics

Compared with short certificate programs or bootcamps, a full AI degree program may offer a broader academic foundation compared to shorter programs, depending on the program structure and a student’s learning goals. Undergraduate education may also prepare students for continued learning through graduate-level programs, such as a master’s degree in artificial intelligence or data science.

AI Degrees Compared to Computer Science and Data Science Degrees

AI degrees often overlap with related fields such as computer science and data science. Understanding these pathways can help students choose the right direction.

Computer Science Pathways

Many students interested in AI begin with a computer science degree. Computer science programs often include courses in programming, algorithms, and software engineering that support artificial intelligence development.

Those pursuing this path may choose AI-focused electives such as:

Machine learning
Natural language processing
Computer vision
Robotics or intelligent systems

Data Science Pathways

Another related option is data science. Data science programs emphasize statistical modeling, data analysis, and predictive algorithms—skills often used when building AI models.

This path appeals to those interested in analytics, predictive systems, and machine learning.

Artificial Intelligence Degree Program Structure

A degree in artificial intelligence typically includes a combination of foundational coursework and specialized AI topics.

Core courses often include:

Programming fundamentals
Algorithms and data structures
Probability and statistics
Machine learning techniques
Data analysis and modeling

Students may also study advanced topics such as:

Deep learning and neural networks
Natural language processing
Computer vision
AI ethics and responsible AI development

Many AI degree programs also include capstone projects where students apply concepts to practical scenarios or project-based work or research topics.

Computer Engineering and Robotics Options

Students interested in hardware systems or robotics may pursue AI through engineering-related programs.

A computer engineering pathway may focus on how intelligent systems interact with hardware, sensors, and embedded systems. This can be relevant for technologies such as robotics or autonomous vehicles.

Those exploring robotics-related education may study topics such as:

Intelligent robotic systems
AI-driven automation
Sensors and computer vision
Embedded system programming

These programs often combine engineering principles with artificial intelligence research.

Graduate Degrees in Artificial Intelligence

Some students continue their education after earning a bachelor’s degree.

A master’s degree in artificial intelligence typically focuses on advanced technical topics such as:

Advanced machine learning models
AI research methods
Large-scale data science systems
Artificial intelligence engineering

Graduate programs may allow specialization in machine learning, natural language processing, robotics, or data science.

Doctoral programs focus heavily on independent study and are often pursued by those interested in academic research, research publications, and advanced theoretical work.

Artificial Intelligence Curriculum and Core Courses

Students studying AI often encounter a curriculum that blends computer science theory with applied technical skills.

Common courses may include:

Algorithms and computational theory
Programming for AI systems
Machine learning and predictive modeling
Data science and statistical analysis
Artificial intelligence ethics and governance

Elective courses may cover emerging AI topics such as natural language processing, computer vision, or robotics.

In addition to coursework, many programs emphasize hands-on projects that help students apply AI knowledge to practical systems.

Artificial Intelligence Internships and Hands-On Experience

Practical experience is an important part of studying AI. Students may build experience through activities such as:

Internships related to data science or AI technologies
Research projects with faculty members
Building machine learning models for personal projects
Participating in open-source AI initiatives

Hands-on projects allow students to practice applying theoretical knowledge and may help develop technical portfolios that demonstrate their skills.

Typical Career Paths With an Artificial Intelligence Degree

Students earning artificial intelligence degrees may explore roles connected to software development, data analysis, and intelligent systems.

Examples of positions sometimes associated with AI education include:

AI engineer
Machine learning engineer
Data scientist
Data analyst
Software engineer working with AI systems

These roles typically require additional skills, experience, or qualifications based on employer expectations.

Some graduates pursue research-focused roles after completing advanced degrees, with requirements varying by position and institution.

Next Steps for Earning an Artificial Intelligence Degree

Artificial intelligence is a rapidly evolving field that combines technical knowledge with creativity and problem-solving. For those interested in this area, pursuing an artificial intelligence degree can provide a structured way to study foundational concepts and technical skills.

Exploring degree programs, building foundational knowledge in programming and mathematics, and identifying areas of interest within AI can help you take the next step toward studying this field.