Artificial Intelligence has grown into a broad field with application in many sectors. As a result, there are many paths to a career in AI. Both undergraduate and graduate degrees can provide the necessary skills and knowledge for working in AI. Specialized AI degrees offer a more narrow focus when preparing for a career in AI.
Artificial intelligence is transforming industries from healthcare to transportation. As AI adoption grows, so does demand for professionals who can develop, optimize, and manage AI systems. But what degree is best to gain the skills needed for an artificial intelligence career?
In this guide, we’ll compare options like computer science, data science, software engineering, and specialized AI programs to help you determine the ideal path to get started in AI.
Computer Science
A computer science (CS) degree provides foundational training in programming algorithms data structures, and machine learning. Core CS courses include
- Programming fundamentals – Languages like Python, Java, C++
- Algorithms and data structures
- Database systems
- Operating systems
- Computer architecture
- Calculus and statistics
- Discrete math
Electives allow customization with AI-focused classes in:
- Machine learning
- Computer vision
- Natural language processing
- Robotics
- Data mining
A CS degree equips students with versatile skills to develop AI applications. Graduates can pursue roles like:
- AI Engineer
- Machine Learning Engineer
- Computer Vision Engineer
- Data Scientist
- Robotics Programmer
- Software Developer
When paired with AI specialization, a computer science degree offers an optimal foundation for AI programming and development jobs.
Data Science
Data science applies statistics, programming, modeling, and analytics to extract insights from complex data A data science curriculum typically includes
- Programming – Python, R, SQL
- Statistical analysis
- Data visualization and storytelling
- Data mining and warehousing
- Machine learning
- Predictive modeling
- Big data analytics
Data science develops valuable abilities for AI tasks like
- Collecting and preparing training data
- Selecting optimal data features
- Statistical modeling and analysis
- Validation and improvement
- Deploying and monitoring AI models
For data-driven AI roles, a data science degree provides directly relevant training.
Software Engineering
A software engineering degree focuses on developing, testing, and maintaining software applications. Core topics include:
- Programming – Java, C#, JavaScript
- Software design patterns
- Requirements analysis
- Software quality and testing
- Software project management
- Algorithms and data structures
Software engineering electives related to AI include:
- Machine learning software architectures
- Data pipelines and workflows
- Programming computer vision and NLP systems
- Embedded software for robotics
The software engineering mindset is key for integrating AI capabilities into real-world systems. This degree equips students for AI-focused engineering roles.
Cognitive Science
Cognitive science explores the inner workings of the human mind through psychology, neuroscience, linguistics, and computer modeling. A cognitive science curriculum covers areas like:
- Cognitive psychology – thinking, memory, perception, language
- Neurobiology and neural networks
- Logic and knowledge representation
- Artificial intelligence
- Philosophy of mind
- Human-computer interaction
This cross-disciplinary degree provides unique insight into building AI with human-like cognition. Graduates pursue careers such as:
- AI Research Scientist
- Cognitive Systems Architect
- Human-AI Interaction Designer
- Neuroscience Engineer
Specialized AI Degrees
Some universities now offer specialized undergraduate AI degrees, such as:
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BS in Artificial Intelligence – Courses in machine learning, computer vision, robotics, natural language processing, etc.
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BS in Applied Artificial Intelligence – Emphasizes applying AI capabilities to real-world problems.
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BS in Mathematics and Artificial Intelligence – Combines math, statistics, and theoretical foundations of AI.
Specialized AI programs allow more targeted study compared to broader computer science or data science degrees. However, specialized degrees are still fairly new and less common.
Double Majors
Given the interdisciplinary nature of AI, some students choose to couple degrees:
- Computer Science + Statistics
- Computer Science + Cognitive Science
- Software Engineering + Data Science
- Applied Math + Machine Learning
Double majoring allows you to gain skills from multiple AI-related fields. This provides breadth and depth of knowledge at the tradeoff of extra coursework.
Master’s and PhD Degrees
While you can launch an AI career with a bachelor’s degree, advanced study provides deeper expertise:
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MS in Artificial Intelligence – Further specialization through advanced AI coursework and research.
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MS in Machine Learning – Focused training in ML algorithms, neural networks, data modeling, and applications.
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PhD in Artificial Intelligence – Original research expanding scientific knowledge in AI/ML. Prepares for senior roles.
Graduate degrees lead to higher-level AI positions in research, architecture, and engineering. They’re required for academic careers.
Which Undergraduate Degree is Best?
There are several solid paths to start an artificial intelligence career, but which undergraduate degree is optimal depends on your interests:
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Want to develop AI software applications? Computer science, software engineering, or specialized AI degrees are best.
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Excited to unlock insights from data? A data science degree is a great match.
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Fascinated by human and machine cognition? Consider cognitive science.
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Want to combine disciplines? Double major or minor to gain multifaceted skills.
With any degree, pursue AI-focused electives, clubs, internships, and projects. Specialization is valued in this fast-moving field.
Choosing the Right University
Beyond picking the right degree, it’s wise to consider universities leading AI research and education:
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Stanford – Top for AI driven by key faculty like Andrew Ng.
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MIT – Pioneered AI research and education through the MIT Computer Science and Artificial Intelligence Laboratory.
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CMU – Highly regarded for AI, robotics, and machine learning programs.
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UC Berkeley – Strong in AI plus big data, optimization, and statistics.
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University of Washington – Leads development of industrial AI applications.
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NYU – Prominent research in AI safety and algorithms.
Attending a university recognized for AI innovation can open doors to coveted research roles. But rising young stars also come from small colleges with the drive to create and publish.
Launching Your AI Career
An undergraduate education in computer science, data science, cognitive science, software engineering, or specialized AI establishes a strong foundation for artificial intelligence careers. Equally important is gaining hands-on experience through AI projects, research, and internships.
Over the next decade, we’ll see remarkable growth in roles that leverage AI to solve real-world problems. Graduates skilled in areas like machine learning, data analysis, and human-AI interaction will have amazing opportunities to shape the future through their work in artificial intelligence.
Computational Linguistics and Natural Language Processing Degrees
Computational linguistics and natural language processing (NLP) degrees are important for artificial intelligence careers that involve autonomous analysis of human language, both written and spoken. A degree in this field provides students with a deep understanding of the complexities of language.
Many factors affect the meaning of language, which can be difficult for AI to understand. A specialization in natural languages makes students more capable of designing AI that successfully processes natural language. This is necessary knowledge for a wide range of industries, including web search, retail, voice-controlled electronics, and e-learning.
Robotics, Engineering, and Autonomous Systems Degrees
A degree in robotics, engineering, or autonomous systems generally involves more electrical and mechanical engineering courses than a broader artificial intelligence degree. Team projects include designing physical systems in addition to designing and implementing AI to control the systems.
A Bachelor’s or Master’s in Robotics, Engineering, or Autonomous Systems prepares students for working in AI for physical systems like vehicles and manufacturing. Students with these degrees are expected to understand mechanical, electronic, and software design of systems.
AI/ML Engineer path – The Harsh Truth
What degree do you need to work in artificial intelligence?
When you’re interested in working in AI, earning a bachelor’s or master’s degree in the field can be a great way to develop or advance your knowledge. Artificial intelligence (AI) stands to add $15.7 trillion to the global economy by 2030, according to Price Waterhouse Cooper [ 1 ].
Where can I get a degree in artificial intelligence (AI)?
Some offer bachelor’s, master’s and doctorate degrees in AI, while others focus more on computer science disciplines with a specialty or research program in AI. Explore the undergraduate and graduate options below, listed alphabetically, for some prestigious programs available to kick off a career in AI. 1. California Institute of Technology
How long does a master’s degree in artificial intelligence take?
Beyond in-person programs, there are a number of online master’s degrees in artificial intelligence, as well as professional master’s degrees, which tend to take less time (around one year) and focus more on practical skills development.
Why should you pursue a degree in artificial intelligence?
This means a degree that either focuses on artificial intelligence, or one in a related field — computer science, computer engineering, or data science — where you build and eventually show off your AI skills, will make you highly competitive on the job market.
