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An online artificial intelligence bachelor’s degree is a computing-focused undergraduate degree that builds skills in programming, applied mathematics, and machine learning. Most programs pair a general computer science foundation with a required mathematics sequence, then move into machine learning, neural networks, and one or more applied branches such as natural language processing or computer vision.
A BS in Artificial Intelligence is a newer degree title, and it is worth knowing that many students reach the same skill set through a computer science degree with an AI concentration. Compare required course lists across both routes rather than deciding on the degree name.
It is an undergraduate computing degree that builds programming, applied mathematics, and machine learning skills through online coursework, usually awarded as a BS in Artificial Intelligence.
A BS in AI covers the same computing foundation but devotes more required coursework to machine learning and its applied branches. A computer science degree is broader and more widely recognized, with AI available as a concentration inside it.
Most programs include general education, a computing foundation core, a mathematics sequence, an AI and machine learning core, electives or a concentration, and a capstone project.
Coursework commonly includes programming in Python, data structures and algorithms, linear algebra, probability and statistics, machine learning, deep learning, and AI ethics, plus electives in natural language processing, computer vision, or robotics.
Requirements vary by school, but commonly include a high school diploma or equivalent and official transcripts. Some programs specify a math prerequisite such as precalculus or a minimum GPA.
Transfer credits can reduce how many courses you need, but policies vary by institution and by whether the credits satisfy the AI major core or only general electives.
For a full map of this program area, start here: Artificial Intelligence Program Guide
Every school list on this site is ordered by the BOC Score, computed from the most recent school-level data published by the U.S. Department of Education (College Scorecard and IPEDS). To qualify, a school must be currently operating and accredited by an agency recognized by the U.S. Department of Education. Each eligible school is then scored on five measures, percentile-ranked against schools at the same credential level:
Schools without enough outcome data appear after ranked schools, without a score. Advertising never affects these rankings. Read the full methodology.
Source:IPEDSCollege Scorecard
Source:Accreditor: Western Association of Schools and Colleges Senior Colleges and University CommissionIPEDSCollege Scorecard
Source:IPEDSCollege Scorecard
Source:IPEDSCollege Scorecard
Source:IPEDSCollege Scorecard
Source:IPEDSCollege Scorecard
Source:IPEDSCollege Scorecard
Source:IPEDSCollege Scorecard
Most online AI bachelor’s programs follow a similar structure:
This is the structural detail most worth checking. In a well-built AI program, linear algebra and probability are separate required courses that come before the machine learning core, not corequisites taken alongside it and not folded into a single survey. Machine learning coursework assumes you can already work with matrices, distributions, and gradients. If a program’s catalog shows the math and the modeling running in parallel, ask how they handle the dependency.
Online formats may be asynchronous, but most still carry weekly deadlines, programming assignments, and participation requirements. To compare how formats differ, see How Online AI Degrees Work.
If you are trying to move faster, compare this degree level to a compressed timeline: Accelerated AI Programs
| Course Topic | What You Learn |
|---|---|
| Programming and Data Structures | Python fundamentals, data structures, and algorithmic problem solving |
| Linear Algebra | Vectors, matrices, and transformations that underlie model computation |
| Probability and Statistics | Distributions, inference, and the statistical basis of learning |
| Machine Learning | Supervised and unsupervised methods, training, and model evaluation |
| Neural Networks and Deep Learning | Network architectures, backpropagation, and training practice |
| Natural Language Processing or Computer Vision | Applied AI in text or image domains, depending on electives |
| AI Ethics and Governance | Bias, explainability, privacy, and the regulatory landscape |
| Capstone Project | An end-to-end project from problem framing through evaluated results |
Program outcomes vary, but many curricula emphasize:
Admissions requirements vary by school and student type. Some programs admit first-time college students; others are built primarily around transfer students.
Common requirements include:
Prior programming experience is generally not required. Most programs teach the first language from the beginning.
Transfer credits can reduce how many courses you need, but rules vary by institution.
Before you enroll, confirm:
See Affordable Online AI Degrees for more on managing total program cost.
Accreditation is the baseline quality indicator. Verify that the institution holds accreditation from a recognized institutional accreditor – such as HLC, SACSCOC, MSCHE, or NECHE – through the U.S. Department of Education database, then compare how the program is structured and delivered online.
A bachelor’s in AI is generally the entry credential for engineering-track roles: machine learning engineer, software engineer on an AI team, or analyst positions attached to a modeling function. A master’s in AI is typically pursued to move into research-oriented work, to pivot into AI from another field, or to reach data science roles that commonly expect graduate coursework.
If you are comparing degree levels and routes, these pages can help:
Data verified: August 10, 2026. Salary, employment, and tuition figures on this page are sourced from the U.S. Bureau of Labor Statistics (OEWS May 2025; Employment Projections 2024–2034) and the U.S. Department of Education College Scorecard (2023 cohort). The source agency and data year are cited inline with every statistic.
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