Which Degree Is Best for Artificial Intelligence?
- Bachelor’s degrees in AI are rare, but many others teach skills to work in AI.
- The most fundamental AI degrees include computer science and data science.
- Degrees in data analytics and business analytics are among the most in-demand.
- Other relevant degrees include mathematics, statistics, and engineering.
As the revolution in artificial intelligence (AI) continues to explode, many people are looking into studying AI. But degrees in AI specifically are rare. For now, at least.
But don’t worry. AI is an interdisciplinary field. It combines many subjects, such as computer science, mathematics, and philosophy. Each of these disciplines has subdisciplines that branch off. Having a background in many of them could still lead to an entry-level role in AI.
So, which degree is best for AI? It’s difficult to say. A computer science degree is a common choice since AI is a subdiscipline of computer science. But a data science degree, which also comes with AI skills, may be equally useful because it’s one of the most in-demand.
We’ve created a list to narrow the options down. Our list considers “best” AI degrees to be degrees that fit somewhere into one of three categories:
- Most Fundamental: Degrees that study AI specifically or its major principles.
- Most Demand: Degrees related to AI with high demand in the job market.
- Most Relevant: Degrees that often appear on AI job postings.
Note: Many degrees can lead to stable and well-paying careers in AI or other fields. This is a non-exhaustive list to give you an idea of some available options. It doesn’t distinguish between types of bachelor’s degrees, including arts, science, and applied science.
Most Fundamental
Some schools offer programs or concentrations specifically for AI. But they’re not always available. It’s more common to find degrees covering the major principles of AI, which provide skill sets needed for many AI roles:
- Computer Science: Computer science programs focus on programming, algorithms, data structures, and computer systems. Computer science is the backbone of AI and fundamental to understanding and developing AI algorithms and systems.
- Data Science: A bachelor’s in data science teaches techniques for extracting insights and making predictions about data. Data science enables AI systems to learn from data, make predictions, and take action, increasing their effectiveness.
- Robotics: Robotics degrees explore the design and development of robotic systems, including those that use AI. Robotics is a physical embodiment of AI systems, capable of self-reliance, interacting with their environment, and performing tasks.
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Most Demand
Some of the fastest-growing jobs today are related to AI. The World Economic Forum predicts a 30% growth for roles such as data analysts, machine learning specialists, and business intelligence analysts by 2027. Demand for degrees in these fields could also be on the rise:
- Data Analytics: Data analytics programs teach how to analyze and interpret data to support decision-making. They often combine mathematics, statistics, computer science, and business. Data analysts use their backgrounds to optimize AI models.
- Machine Learning: Machine learning degrees are less common but provide a crucial skill set. Machine learning is a type of AI capable of learning from or adapting to data without human help. Machine learning specialists help businesses improve efficiency.
- Business Analytics: Business analytics programs teach how to collect and analyze data. Some programs introduce AI concepts and the use of AI technologies to make business decisions, including data analysis, prediction, and optimization.
Most Relevant
The same degree requirements appear often when you look through AI job postings. Besides popular degrees like computer science and data science, numerous others provide the skills to work in AI. The most relevant AI-related degrees include:
- Mathematics: Mathematics is at the core of AI. A bachelor’s in mathematics provides a strong foundation in AI-related areas such as linear algebra, mathematical modeling, and optimization techniques.
- Statistics: Statistics programs are highly relevant for several reasons, including the focus on data analysis, training with statistical software, and emphasis on data visualization, making it easier to understand and apply statistical concepts to AI.
- Engineering: Engineering degrees often include courses with numerous AI applications. For example, systems thinking courses could apply to how an AI interacts between components and subsystems. Courses teaching programming are also common.
Frequently Asked Questions About Artificial Intelligence Degrees
Are AI degrees worth it?
Studying AI comes with two big advantages: demand and experience. The demand for AI workers is rapidly growing across industries. As industries widely invest in AI, it creates numerous job opportunities. The specialized knowledge AI degrees can deliver could give you an edge in the job market.
A typical AI degree also includes hands-on experience, such as practical projects, internships, and training with real-world AI applications. These experiences can be useful for building your portfolio and demonstrating your capabilities to employers after graduation.
Is majoring in AI hard?
Majoring in AI can be challenging. But, the difficulty sways up or down depending on your background and abilities. AI is an interdisciplinary field combining elements such as computer science, math, and statistics. Being comfortable in these areas will make the concepts and techniques easier to learn and understand.
What are the highest-paying AI careers?
The highest-paying careers in AI-related fields include computer scientists, information research scientists, and computer network architects. According to the Bureau of Labor Statistics (BLS), computer and information research scientists earned a median salary of $155,880 as of May 2022.
Computer network architects earned $129,490. Other high-paying AI roles include machine learning engineers ($114,967), database architects ($136,540), software developers ($132,930), and data scientists ($115,240).
