Artificial Intelligence · South Dakota
Artificial Intelligence colleges in South Dakota
CampusPin lists 15 U.S. colleges in South Dakota that offer Artificial Intelligence programs. Compare tuition, acceptance rate, and enrollment in the table below, every figure links back to the institution's official IPEDS data.
Artificial intelligence is the study of building systems that learn, reason, perceive, and make decisions from data, for students who enjoy math, programming, and modeling.
Schools in South Dakota that offer Artificial Intelligence
Augustana University
Sioux Falls, SD · University · Private
Tuition
$39,190
Acceptance
59%
Enrollment
2,105
California Intercontinental University
Sioux Falls, SD · University · Private
Tuition
$9,054
Acceptance
100%
Enrollment
484
Dakota State University
Madison, SD · University · Public
Tuition
$9,633
Acceptance
98%
Enrollment
2,527
Kairos University
Sioux Falls, SD · University · Private
Tuition
$13,120
Acceptance
74%
Enrollment
1,105
Lake Area Technical College
Watertown, SD · Community College · Public
Tuition
$6,718
Acceptance
100%
Enrollment
1,710
Mitchell Technical College
Mitchell, SD · Community College · Public
Tuition
$7,524
Acceptance
100%
Enrollment
953
National American University-Rapid City
Rapid City, SD · University · Private
Tuition
$16,065
Acceptance
100%
Enrollment
1,022
Northern State University
Aberdeen, SD · University · Public
Tuition
$8,845
Acceptance
93%
Enrollment
1,828
Oglala Lakota College
Kyle, SD · University · Public
Tuition
$2,684
Acceptance
100%
Enrollment
1,205
Sinte Gleska University
Mission, SD · University · Public
Tuition
$4,714
Acceptance
100%
Enrollment
655
South Dakota State University
Brookings, SD · University · Public
Tuition
$9,299
Acceptance
99%
Enrollment
10,119
Southeast Technical College
Sioux Falls, SD · Community College · Public
Tuition
$7,650
Acceptance
100%
Enrollment
2,164
University of Sioux Falls
Sioux Falls, SD · University · Private
Tuition
$20,740
Acceptance
82%
Enrollment
1,491
University of South Dakota
Vermillion, SD · University · Public
Tuition
$9,432
Acceptance
99%
Enrollment
8,012
Western Dakota Technical College
Rapid City, SD · Community College · Public
Tuition
$8,008
Acceptance
100%
Enrollment
733
Artificial Intelligence programs in South Dakota: by the numbers
A quick comparison of the 15 schools listed above, drawn from each institution's published IPEDS data.
Schools listed
15
Public / private
10 / 5
Universities / 2-year
11 / 4
Cities represented
10
In-state tuition range
$2,684–$39,190
Median in-state tuition
$9,054
Lowest published in-state tuition
Oglala Lakota College
$2,684
Most selective
Augustana University
59% acceptance
Largest by enrollment
South Dakota State University
10,119 students
Figures reflect the schools currently listed and each institution's most recent reported data. Verify current tuition and admissions details with the school before applying.
What you'll study in a Artificial Intelligence program
- Machine learning algorithms and model training
- Deep learning and neural network architectures
- Natural language processing and language models
- Computer vision and image recognition
- Knowledge representation, search, and automated reasoning
- Probability, linear algebra, and statistics for modeling
- Programming and data structures for AI systems
- Robotics, perception, and motion control
- Ethics, bias, and responsible deployment of AI
Where a Artificial Intelligence degree can lead
- AI Engineer
- Machine Learning Engineer
- Research Scientist
- Data Scientist
- Natural Language Processing Engineer
- Computer Vision Engineer
Typical pay: Early-career wages vary by employer, region, and experience (BLS, 2024 computer and information research scientists median $140,910).
An artificial intelligence major teaches you to design software that can learn from data, draw inferences, understand language, and interpret images or motion. Students dig into the theory behind machine reasoning, then build it in code: training models to recognize patterns, representing knowledge so a system can act on it, processing human language, and giving machines a sense of their surroundings through computer vision and robotics. The work blends mathematics, statistics, and programming with hands-on experimentation, and you spend much of your time measuring how well a model performs, finding where it fails, and weighing the ethical and human-factors questions that come with automated decisions. It sits close to computer science but is narrower and more applied: where computer science covers computing broadly and data science centers on drawing conclusions from data, an AI program focuses specifically on building systems that learn and reason, and it leans more toward research methods than the day-to-day product focus of software engineering.
AI programs are commonly offered as a bachelor's or master's degree, and many students continue to graduate study because research-oriented and model-building roles often draw on advanced coursework. Coursework is project-heavy: lab assignments where you train and tune models, a capstone or research project, and often a thesis at the graduate level, since AI is not a licensed profession in the way some health or engineering fields are. There is no general license to practice AI, though work that touches regulated areas such as healthcare or finance may carry its own legal and compliance requirements that should be verified, and some related engineering tracks may involve programmatic accreditation worth confirming. Graduates work across software and technology firms, research labs, healthcare and finance organizations, manufacturing and robotics, government, and academia, typically as engineers who put models into production or as scientists who develop new methods.
In federal data for the closely related occupation of computer and information research scientists, the U.S. Bureau of Labor Statistics reports a 2024 median wage of $140,910 and projects employment to grow about 19.7% from 2024 to 2034; a master's degree is the typical entry-level education for that occupation. National figures are occupation-wide medians across all experience levels, not starting wages or graduate outcomes.
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