5 AI Masters Degree Programs in Colorado

AI-related jobs are projected to grow by 40% by 2030. Learning about Colorado’s AI master’s degree programs makes strategic sense for your career. The state has become a competitive destination for artificial intelligence graduate programs. Universities there have developed specialized curricula to meet industry demands.

The surge in interest is remarkable. Last year alone, Coursera reported three million students enrolling in AI-related courses. That’s about six students per minute. Colorado provides diverse options, whether you want a master’s in AI focused on business applications or technical machine learning. Here are five outstanding programs worth thinking about for 2027.

1. University of Colorado Boulder – MS in Artificial Intelligence

The University of Colorado Boulder offers its Master of Science in Artificial Intelligence through an innovative online delivery model hosted on Coursera. This represents one of the nation’s first dedicated artificial intelligence graduate programs, positioning CU Boulder as a pioneer in AI education. The program delivers stackable graduate-level courses that lead to a fully accredited master’s degree.

Your credential carries similar weight to the on-campus version. The diploma contains no “online” or “Coursera” designations, and you earn the same credentials as residential students. The Center for World University Rankings placed CU Boulder in the top 0.4% globally in 2024, ranking 72nd overall and 40th nationally.

The Department of Computer Science designed this degree to expand access to graduate-level courses beyond the physical campus while maintaining academic rigor. You get access to courses taught by award-winning faculty who also teach on campus. This ensures consistent quality across delivery formats. This is a professional master’s degree, so it follows a course-based structure without thesis or independent research options.

The program operates on a pay-as-you-go model with flexible enrollment options. You can start in non-credit versions of courses right away and upgrade to for-credit status at any time. Your progress comes with you. Eight-week sessions run six times per year and allow you to control your pace and schedule.

Skills and Competencies You’ll Develop

You’ll acquire advanced theoretical understanding and practical skills in multiple AI domains. The curriculum emphasizes neural networks, deep learning, reinforcement learning and generative AI. These technical competencies prepare you to deliver production-ready AI and machine learning projects at every stage of the AI lifecycle, from model building through optimization to scalable deployment.

This program provides foundational mathematics training, unlike many computer science master’s degrees. You’ll develop skills in statistics, probability and linear algebra. This creates a solid mathematical core for AI mastery. This mathematical foundation distinguishes the program from more applied alternatives.

The curriculum also addresses ethical dimensions of AI practice. You’ll explore bias mitigation, fairness, accountability and societal effect to become a conscientious practitioner. This ethical framework becomes vital as AI technologies reshape economies and communities increasingly.

Cross-disciplinary exposure comes through access to courses from other CU Boulder degrees on Coursera. These have data science, computer science, engineering management and electrical engineering. This breadth allows you to customize your learning path based on career objectives.

Curriculum Structure and Course Delivery

The MS-AI requires 30 credit hours of graduate-level coursework delivered entirely online. The structure divides into two main components: 15 credits of required breadth courses and 15 credits of electives.

Breadth requirements have pathway courses in five specializations covering statistical learning, machine learning, ethics and AI, and reinforcement learning. These foundation courses ensure all students gain common core knowledge whatever their background. You must earn a B or better in breadth courses for credit toward your degree.

You select from a variety of topic areas for electives. These have robotics, computer vision, generative AI, data mining and natural language processing. You complete either five elective specializations or four complete specializations plus three one-credit electives totaling 15 credits. Elective courses require a C or better grade.

Each course carries one credit. Most courses arrange into three-course specializations. These specializations cover the same content a traditional three-credit, 16-week course would deliver, compressed into an efficient format.

You maintain flexibility in course sequencing. The program allows you to complete courses in any order, and you don’t need to wait for admission to make progress. You can take sessions off without charges or penalties under the pay-as-you-go structure during your learning trip.

You may apply up to six graduate-level credit hours (two specializations) from other CU degrees on Coursera toward your MS-AI. Outside electives must be graduate level, offered through Coursera, meet academic standards and earn a C or better grade.

The program requires you to maintain a minimum cumulative GPA of 3.00. You may retake courses but can only repeat the same course once. The program qualifies for grade replacement and provides additional flexibility.

Admission Requirements and Prerequisites

Performance-based admissions distinguishes this program from traditional graduate school processes. You get admission by completing a three-course pathway specialization with a grade of B or better in each course, maintaining a cumulative GPA of at least 3.00 and declaring intent to seek the degree.

The university never asks for transcripts, previous test scores like GRE or TOEFL, application essays, letters of recommendation or application fees. A previous degree is not required for admission. This accessibility opens doors whatever your educational background or professional experience.

Pathway courses function as required curriculum components, so you make direct progress toward the degree while working toward admission. Automatic admission occurs after that session when you complete all three pathway courses with qualifying grades. Credits earned before admission apply toward the degree.

The program recommends particular subject familiarity rather than requiring formal prerequisites. You should have equivalent prior knowledge of college-level coursework and comport yourself with peers, staff and faculty in a professional manner. The degree targets students with strong foundations in computer science, applied math, information science, or electrical or computer engineering through either education or professional experience.

Specific recommended preparation has programming and software development experience. You should possess college-level understanding of calculus, linear algebra, discrete math, probability and statistics. Students comfortable in self-motivated learning environments find the format most suitable.

No background check is required for enrollment because the program operates fully online.

Tuition, Financial Aid, and Scholarships

The MS-AI on Coursera costs $525.00 per credit hour. The 30-credit-hour requirement brings total program cost to $15,750.00. Tuition remains the same for all students whatever their residency status because this program operates 100% online.

The pay-as-you-go model means you only pay for courses in your next eight-week session rather than the full degree cost upfront. Tuition is due in full when you enroll for each session. Payment options have online payment from U.S. checking or savings accounts (no fee), U.S. credit or debit cards (service fee applies per transaction), or wire transfer via Flywire.

This program is not eligible for financial aid provided through the Free Application for Federal Student Aid (FAFSA) currently. CU Boulder does not offer scholarships for this program currently, though you can search for private scholarships.

Students in this program are not eligible for part-time instructor positions, teaching assistantships or research assistantships. Limited hourly appointments are available for more advanced students through the CU Boulder Student Job Board.

Alternative funding sources have employer tuition assistance programs, as many employers value the skills this program provides. The program is eligible for education benefits offered through Veterans Affairs currently. These have the GI Bill, VEAP and DEA. Tax benefits may also apply depending on your situation.

2. Regis University – MS in Applied Artificial Intelligence

Regis University’s Anderson College of Business and Computing positions its Master of Science in Applied Artificial Intelligence as a program where technical expertise meets ethical responsibility. The curriculum addresses critical issues like bias, privacy, and fairness alongside core AI competencies, rooted in Jesuit values. This dual emphasis distinguishes the program from purely technical alternatives.

The hybrid format accommodates working professionals through flexible scheduling. Physical classrooms host on-campus classes that meet at scheduled times regularly, while online courses can be completed within weekly deadlines on your own schedule. This model provides face-to-face interaction when you need it and asynchronous flexibility when you don’t.

The 30-credit-hour program takes one to two years to complete. Courses run in accelerated eight-week terms with two start dates each year in January and August. The scholar-practitioner model brings expert faculty with extensive professional experience into the classroom.

The program trains you to connect technology with organizational strategy, ethics, governance, and AI safety rather than focusing solely on model development. You’ll learn to assess organizational readiness, identify high-impact use cases, and arrange AI initiatives with core business or mission objectives in sectors like business, healthcare, creative arts, and public policy.

Merit scholarships up to $10,200 are available for new students. Graduates position themselves for roles like AI/Machine Learning Engineer, Data Scientist, AI Product Manager, Business Intelligence Analyst, Health Data Analyst, and Ethical AI Consultant.

Skills and Competencies You’ll Develop

The curriculum builds competencies in five distinct outcome areas. You’ll master foundational AI principles such as search algorithms, intelligent agents, and problem-solving techniques that enable you to design and assess AI applications. This theoretical grounding supports practical application in a variety of contexts.

End-to-end AI solution development becomes your second competency domain. You’ll manage and analyze large datasets, apply advanced machine learning and deep learning techniques, and deploy reliable, data-driven models to solve real-world problems. These skills cover the complete AI lifecycle from conception through production.

Ethical assessment forms a core competency area. You’ll assess AI’s societal implications, address bias, fairness, and privacy issues, and incorporate transparent and accountable practices into AI development and deployment. Growing concerns about AI’s social effect have made this ethical dimension essential for responsible practitioners.

Sector-specific customization represents another key skill area. You’ll adapt AI-driven strategies and models for particular industries such as healthcare, finance, and creative sectors while collaborating with stakeholders to ensure successful implementations. This versatility expands your career options in multiple fields.

Communication and leadership skills round out your competency development. You’ll communicate AI concepts to diverse audiences effectively and demonstrate collaboration abilities that encourage interdisciplinary engagement. The program upholds Jesuit values in professional settings explicitly and prepares you to lead ethically.

Technical skills you’ll gain include AI and machine learning fundamentals, data analysis and visualization, natural language processing, AI ethics and responsible use, and predictive modeling. To name just one example, you’ll explore methods for adapting pre-trained large language models to specific industries through advanced fine-tuning techniques.

Curriculum Structure and Course Delivery

The 30-credit-hour curriculum has ten three-credit courses delivered in eight-week terms. This structure allows concentrated focus on each subject before moving to the next.

The foundations course explores AI history and development and emphasizes intelligent agents, search algorithms, and problem-solving techniques while building fundamental AI programming skills. The fine-tuning course teaches you to adapt large language models to specific industries and develop strategies for assessing and optimizing model performance.

Sector-specific courses address practical applications. The business and industry applications course breaks down AI integration in finance and logistics sectors and upholds Jesuit values of ethical decision-making through case studies and practical projects. You’ll design AI solutions that boost business processes while promoting fairness and positive societal effect.

The capstone project combines your learning through an applied AI initiative. You’ll involve yourself in hands-on projects and community learning experiences that blend technical skills with ethical reflection and discernment, hallmarks of Jesuit pedagogy.

Both online and on-campus delivery options follow the same eight-week accelerated schedule. Online coursework proceeds asynchronously within weekly deadlines, while on-campus sessions meet synchronously at scheduled times.

Admission Requirements and Prerequisites

The admission process requires four components: an online application, official degree-bearing transcripts, a resume, and relevant work experience or a bachelor’s degree. This straightforward approach focuses on demonstrated capability rather than extensive documentation.

The program targets working professionals and recent graduates seeking to advance their careers in the growing AI sector. You should bring relevant work experience or a bachelor’s degree to the program.

No specific prerequisite courses are mandated, though the program is designed for those with professional experience or educational background in related fields. The curriculum assumes you can work independently and meet weekly deadlines in either format.

Tuition, Financial Aid, and Scholarships

New graduate students receive automatic assessment for the Dean’s Scholarship during the admission process. This merit-based award provides up to $10,200 for the MS in Applied Artificial Intelligence program.

The Office of Financial Aid reviews your enrollment one to two weeks before classes start and awards the scholarship based on your enrollment in semester-long or eight-week term courses. The scholarship amount adjusts when you add or drop courses quickly and disburses to your student account after the add/drop period ends.

Dean’s Scholarships continue for the posted program length provided you meet renewal requirements. You must maintain a minimum 3.0 GPA in your graduate program and meet Financial Aid Satisfactory Academic Progress requirements. You must also maintain at least half-time enrollment of three graduate-level credit hours per semester. All courses must apply to the eligible degree program.

The scholarship splits and awards per class as you register. Eligibility ends permanently if you stop out and must reapply through the re-entry process, though you’ll be assessed for current scholarship opportunities upon re-entry.

Students participating in Guild partnerships do not qualify for the Dean’s Scholarship. The Dean’s Scholarship combined with other institutional aid cannot exceed tuition costs. The scholarship covers the total credit hours required to graduate; if you withdraw or need additional time, you become responsible for remaining costs through out-of-pocket payment or other financial aid forms via FAFSA.

3. University of Colorado Denver – MS in Business Analytics and AI

CU Denver’s Business School positions its Master of Science in Business Analytics and Artificial Intelligence as your competitive edge for making strategically sound decisions in data-driven environments. This degree gives you skills to interpret complex datasets and provide actionable insights within business contexts. It’s different from purely technical artificial intelligence graduate programs.

The program prioritizes applications of mathematical models and AI-driven solutions in workplace settings rather than development of new research techniques. Coursework in data analysis, decision analysis, predictive analytics, prescriptive analytics, causal analytics, AI and deep learning, and supply chain management demonstrates this managerial emphasis. You get hands-on experience that distinguishes you in analytics roles by analyzing data from real-life businesses.

You can complete the 30-credit-hour degree in 18 to 24 months. Full-time students may finish in 12 months with careful planning and academic advisor consultation. The program requires neither a comprehensive examination nor thesis completion. You can focus entirely on applied coursework.

Graduates move into roles as business intelligence analysts, data analysts, data engineers, financial analysts, and data visualization specialists. Median annual salaries for these positions range from approximately $77,000 to more than $100,000.

Skills and Competencies You’ll Develop

You develop proficiency in industry-relevant tools through hands-on coursework. Python, R, Tableau, and machine learning frameworks are part of this. These technical capabilities combine with critical skills needed to assess, apply, and responsibly use AI in data-driven business environments.

The curriculum teaches you to apply quantitative methods and artificial intelligence to real-life problems. Modern methodologies adopted from statistics, operations research, machine learning, and management science make this possible. You learn common coding languages like Python and R while building strong proficiency in statistics, decision analysis, predictive analytics, causal analytics, and more.

Students join from diverse backgrounds with different aims for applying their business analytics skillset. The program does not require specific academic or work experience for acceptance. Successful applicants demonstrate quantitative skills through either academic or work experience or with GMAT or GRE scores.

Real data sets and business use cases are the foundations of hands-on projects. This approach enables you to graduate with confidence facing career challenges. You know how to solve the problems. Networking opportunities at the Business School help you make professional connections and get exposure to business applications of classroom learning.

Curriculum Structure and Course Delivery

The degree requires 30 total credit hours divided between seven core courses and three electives. This structure provides a complete foundation while allowing customization based on career goals.

Core curriculum has Statistics for Business Analytics, Computing and AI for Business Analytics, Decision Analysis, Predictive Analytics with AI and Machine Learning, Prescriptive Analytics with Optimization, Causal Analytics, and Artificial Intelligence and Deep Learning for Business Analytics. Each core course carries three credit hours.

You select any three courses from options for electives. Transformative Technologies Impacting Globalization, Time-Series Forecasting, Project Management, Supply Chain Analytics, Data Visualization, AI for Business, Evaluative Analytics, Global Supply Chain Management, and Applied Generative AI in Business Analytics are available. You may also choose from BANA courses numbered 6000 or higher, ISMG 6080 Database Management Systems, ISMG 6470 Text Data Analytics, or ECON 5030 Data Analysis with SAS.

The MS in Business Analytics and Artificial Intelligence allows you to petition for a maximum of six semester hours transfer from another university. This is different from other Business School MS degrees, which allow nine semester hours transfer.

Admission Requirements and Prerequisites

The Business School maintains an acceptance rate of 72%. The average undergraduate GPA is 3.16 among admitted students. Students average 28 years of age.

You should demonstrate quantitative skills through academic or work experience or with GMAT or GRE scores. The program does not mandate specific prerequisite courses. You can show quantitative capability through various pathways.

Students maintain a minimum cumulative GPA of 3.00 throughout the program. The degree attracts individuals from many different backgrounds who want to apply business analytics skills in their careers.

Tuition, Financial Aid, and Scholarships

Tuition costs $7,844 per year for Colorado residents and $18,638 per year for out-of-state students. The out-of-state per credit hour rate is $1,118.

The Business School offers scholarships to students every semester. Program-specific and class-specific scholarships are available prior to each semester. General scholarships are available to all Business School students through Scholarship Universe, where requirements and award amounts are provided.

Application deadlines vary by semester. Applications open March 15 and close May 31 for fall enrollment. Applications open September 15 and close November 15 for spring enrollment. Scholarships work a semester ahead. Incoming students with access to Scholarship Universe before deadlines may apply.

All domestic students should complete the Free Application for Federal Student Aid (FAFSA) annually. Federal and CU Denver financial aid options have grants, work-study, Federal Subsidized Direct Loan, and Federal Perkins Loan.

4. Colorado State University Global – MS in AI and Machine Learning

Colorado State University Global earned a #1 ranking for Best Online AI Degree from Successful Student. Analytics Insight named the program to its list of Top Online Masters Courses for Artificial Intelligence in 2021. The university itself received a #3 ranking for Best Colleges in Colorado from Best Value Schools and a #3 ranking for Best Value Online Graduate School from Value Colleges.

CSU Global operates as a not-for-profit public university and delivers the MS in AI and Machine Learning online. Regional accreditation from the Higher Learning Commission provides the highest form of program validation. This accreditation requires passing a peer-reviewed process that ensures consistent quality standards and makes the degree as valuable as in-person alternatives.

The program charges $0.00 in student fees. No out-of-state fees, athletic fees, per-credit fees, or hidden charges apply. So your tuition rate locks in from first class to last through the tuition guarantee. Monthly class starts, accelerated eight-week courses, and no set class times or physical locations provide maximum flexibility.

The curriculum addresses latest deep-learning libraries such as TensorFlow with proficiency focus in Python. Training applies these technologies in healthcare, manufacturing, oil/gas, and automotive industries.

Skills and Competencies You’ll Develop

You’ll gain six core competency areas throughout the program. First, you’ll use principles and techniques associated with software development. Second, you’ll apply artificial intelligence principles as needed for given problems or scenarios.

Machine learning principles form your third competency area and enable you to solve specific problems or scenarios. Fourth, you’ll develop solutions capable of modeling human behavior. Fifth, you’ll implement solutions that combine artificial intelligence and machine learning principles. You’ll review performance of applications in artificial intelligence and machine learning domains.

Curriculum Structure and Course Delivery

The program requires 30 credits delivered through eight-week accelerated courses. CSU Global structures content to build foundational knowledge, skills, and academic credentials needed for long-term AI careers.

Students must first complete advanced coursework in Discrete Mathematics and Probability and Statistics or equivalent before entering specializations. CSU Global offers these prerequisites as MTH350 Discrete Mathematics and MTH410 Quantitative Business Analysis for non-degree seeking students.

The specialization track focuses on analyzing and associating AI principles into reasoning and uncertainty, applying techniques for image analysis, and implementing integrated AI and machine-learning solutions.

Admission Requirements and Prerequisites

The program targets students with strong quantitative or technical backgrounds. Program chair review is mandatory for specialization admission. You must demonstrate completion of advanced courses in Discrete Mathematics and Probability and Statistics.

Students not meeting math requirements remain inadmissible to the specialization. But you may earn prerequisite coursework as a non-degree seeking student with CSU Global before formal admission.

Tuition, Financial Aid, and Scholarships

Total program cost is $20,250 for 30 credits. This pricing has zero additional student fees. The tuition guarantee ensures your rate remains constant throughout enrollment[211].

Many students participate in financial aid programs. Enrollment counselors work with you to explore options for educational expenses. The program qualifies for Veterans Affairs education benefits including GI Bill, VEAP, and DEA.

5. University of Colorado Boulder – MS in Data Science

CU Boulder’s Master of Science in Data Science operates through two distinct delivery formats: a residential on-campus program and an online version hosted on Coursera. Both pathways lead to the same STEM-designated degree and qualify international students for Optional Practical Training extensions. These extensions enable up to three years of U.S. work authorization after graduation.

The interdisciplinary structure draws faculty from Applied Mathematics, Computer Science, and Information Science departments. This cross-departmental collaborative effort prepares you for roles in machine learning engineering, business intelligence, quantitative finance, healthcare analytics, and cybersecurity.

Skills and Competencies You’ll Develop

You’ll gain training in machine learning, AI tools, data analytics, and statistical modeling. Hands-on projects employ cloud-based programming environments and Jupyter Notebooks with access to real-life datasets. The curriculum applies data science techniques to healthcare analytics and financial analytics domains.

Curriculum Structure and Course Delivery

The non-thesis degree requires 30 credit hours: 21 credits of core coursework in statistics and computer science, plus 9 credits of electives.

The online version uses performance-based admission through three pathway courses requiring a 3.0 GPA or better. The on-campus program requires a bachelor’s degree with minimum 3.0 GPA, mathematical background in calculus and linear algebra, and programming experience. The application deadline for on-campus admission is February 15.

Tuition, Financial Aid, and Scholarships

The online program charges $525 per credit hour whatever your residency. The on-campus version operates on traditional semester billing. Neither format offers scholarships currently, though private scholarship opportunities exist.

Get Your Start Now

Colorado’s AI master’s programs provide diverse pathways matching your career goals and learning priorities. You prioritize affordability through CU Boulder’s online option at $15,750, seek ethical AI training at Regis University with merit scholarships up to $10,200, or prefer business-focused applications at CU Denver. You’ll find quality options within the state.

Each program brings unique strengths to the table. Performance-based admissions at CU Boulder remove traditional barriers. CSU Global’s accelerated eight-week format accommodates working professionals. Assess program focus, delivery format, cost structure and admission requirements against your professional objectives for your specific situation.

The 40% job growth projection makes now an opportune time to start your AI master’s trip.