The 2 Best AI Masters Degree Programs in Kansas
Kansas has AI master’s degree programs that position you at the vanguard of one of the fastest-growing fields today. AI transforms nearly every industry and aspect of society, and the just need for AI professionals continues to grow across industries such as healthcare, finance, cybersecurity, entertainment, manufacturing, and beyond. Employers struggle to integrate this technology and create most important opportunities for qualified graduates. Kansas universities provide excellent options to advance your career in this ever-changing field, whether you’re thinking over a traditional AI master’s program or learning about AI master’s programs online.
1. Kansas State University – MS in Computer Science with AI Concentration
Kansas State University guides the state with a specialized Master of Science in Artificial Intelligence Systems and their Applications, scheduled to launch in Spring 2027. Kansas State becomes one of the first institutions in the region to offer a dedicated graduate degree focused on AI rather than just a concentration within computer science. This represents a major milestone.
Program Overview and Key Features
The 33-credit-hour program addresses two distinct professional pathways in the AI field. First, it prepares students to develop novel AI systems and advance the field through research. Second, it trains professionals who can apply and adjust state-of-the-art AI models to solve ground problems across industries.
Kansas State’s Department of Computer Science brings high research credentials to this program. The department houses over a dozen research-active faculty members whose work spans AI system design and applications in critical domains such as agriculture, medicine, and cybersecurity. They also tackle security and privacy challenges in AI. These faculty have produced hundreds of peer-reviewed publications in artificial intelligence and related fields. Students learn from scholars advancing the state of the art in AI research and practice.
The university positions this program to serve Kansas industries. Graduates contribute not just to the AI research and development sector but to any industry in the state that uses AI to improve process effectiveness. This dual focus on theoretical advancement and practical application distinguishes the program from purely academic research degrees.
Kansas State also offers an online Master of Science in Computer Science with an AI concentration to students seeking flexibility. Fortune.com ranked this alternative #9 in Best Online Master’s in Computer Science Degrees in 2022. The online format allows working professionals to pursue AI education without relocating, though the dedicated MS in AI program offers a more specialized curriculum.
Curriculum and Core AI Courses
The curriculum follows a well-laid-out approach. Students must complete core AI courses, demonstrate breadth across AI subfields, and select electives aligned with career goals. The program requires 30 credit hours of coursework.
Core AI Courses
Five mandatory courses establish the foundation:
- CIS 730: Principles of Artificial Intelligence
- CIS 732: Machine Learning and Pattern Recognition
- CIS 733: Data Science Foundations
- CIS 831: Deep Learning
- CIS 835: Neuro-Symbolic AI: Deep Learning and Knowledge Representation
These courses progress from fundamental AI principles through machine learning techniques to advanced topics like deep learning and neuro-symbolic approaches that combine neural networks with knowledge representation.
AI Breadth Requirements
Students must complete 9 credit hours across three distinct areas to ensure well-rounded expertise. The first area, Data & Analytics, offers courses that include CIS 731 (Programming Techniques for Data Science and Analytics), STAT 705 (Regression and Analysis of Variance), STAT 770 (Theory of Statistics I), and ECE 647 (Digital Signal Processing).
The Knowledge Representation & Reasoning area provides options such as CIS 775 (Analysis of Algorithms), CIS 761 (Data Base Management Systems), CIS 836 (Knowledge Graphs), CIS 740 (Software Engineering), and ECE 861 (Applied Probability Theory & Random Processes). Students can also take CIS 830 when it covers Current Topics in Artificial Intelligence.
The third breadth area focuses on Applications & Integration and features courses like CIS 744 (Advanced Software Analysis and Design) and ECE 840 (Computer Engineering Methods for Analysis, Simulation, and Design).
Elective Options
The remaining 6 to 9 credit hours come from AI electives and allow students to specialize based on career interests. Options include CIS 721 (Real-time Systems), CIS 738 (Ethics in Artificial Intelligence and Machine Learning), CIS 739 (Natural Language Processing), ECE 670 (Engineering Applications of Machine Intelligence), STAT 713 (Applied Linear Statistical Models), and CIS 890 (Special Topics in Computer Science).
This curriculum design ensures graduates possess both theoretical knowledge and practical skills that employers value. The ethics course addresses growing concerns about responsible AI development. Specialized courses in natural language processing and computer vision prepare students for high-demand roles.
Admission Requirements and Prerequisites
Kansas State sets specific academic standards to admit students. You need graduation from an accredited institution with a baccalaureate degree in computer science or a related field. The program requires a minimum grade point average of 3.0 out of 4.0.
GRE scores must meet these minimum thresholds: verbal – 146; quantitative – 151; analytical – 3.0. The institution code for submitting GRE scores is 6334, with department code 0402.
International students face additional requirements. TOEFL scores must reach at least 79 on the internet-based test. Alternative English proficiency tests include IELTS with a minimum score of 6.5 or Pearson Test of English with a score of 58. The TOEFL institution code is 6334 with department code 78.
Application deadlines vary by semester. Submit materials by January 8 for fall admission. Spring admission requires submission by August 1. These deadlines apply, so plan to gather transcripts, test scores, and other required documents.
Students in the general MS in Computer Science program can transfer up to 10 hours from other accredited graduate programs. Each new student receives assignment to a faculty adviser who helps select courses and reviews progress until a major professor is chosen.
The Graduate School requires all graduate students to file a program of study, which is a formal list of courses you intend to take to fulfill degree requirements. Full-time students must submit this by the end of their second semester. Part-time students submit upon completing nine credit hours.
Career Prospects and Job Outcomes
The program prepares graduates for many high-paying positions across multiple industries. Machine Learning Engineer roles involve designing, building, and deploying machine learning models for recommendation systems, automated decision making, and predictive analytics. ZipRecruiter data shows annual salaries for machine learning engineers range between $101,000 to $155,000.
AI Engineers design, implement, and maintain AI systems with salaries ranging from $106,000 to $160,000. Data Scientists collect, analyze, and interpret datasets to uncover insights for business decisions and earn a median salary of $112,000 in 2024.
AI R&D Scientist positions focus on expanding the boundaries of AI technology through experiments and algorithm development for research-oriented graduates. These roles require advanced degrees such as a master’s or PhD, with salaries varying based on industry and experience.
Specialized technical roles include Computer Vision Engineers who develop systems that analyze visual data and Natural Language Processing Specialists who create systems that interact with human language and power chatbots, translation services, and document analysis platforms.
Graduates pursue AI Product Manager roles beyond purely technical positions and serve as the bridge between technical AI teams and business stakeholders. These professionals oversee AI product development and deployment to ensure alignment with business goals. AI Consultants advise businesses on strategic implementation of AI and machine learning solutions to improve efficiency, reduce costs, and create new opportunities.
Emerging career paths include AI Cyber-Physical Systems Engineers who design intelligent systems that integrate computational intelligence with physical processes and components to achieve autonomous decision-making and performance optimization.
Workforce need for AI experts grows across all industries. Technology and software companies lead hiring, but finance and banking, healthcare and biotechnology, manufacturing and automation, and retail and e-commerce sectors also seek AI talent. Agriculture presents unique opportunities, with AI applications that monitor crops, predict yields, and optimize treatment strategies.
Kansas State emphasizes that providing high-level AI education within the state helps retain talented students rather than losing them to other states with more developed AI programs. This focus on state workforce development creates opportunities for graduates to build careers close to home and contribute to Kansas industries.
Tuition Costs and Financial Aid Options
The program lists tuition at $479.16 per credit hour. The complete 33-credit-hour program amounts to $15,812. Student fees add $289.70 per credit hour and bring additional costs to roughly $9,560 for the full program.
Based on these figures, the total program cost including both tuition and fees is $25,372 before books, materials, or living expenses. These rates reflect current pricing and may adjust for future cohorts.
Graduate students in the Computer Science department often receive financial support through teaching assistantships, research assistantships, and fellowships. Preference for support goes to doctorate students, but master’s students may qualify for these opportunities.
Graduate Research Assistants work with faculty members on specific research projects for a certain number of hours each week. They receive tuition fee waivers and stipends in exchange and reduce the financial burden of graduate education.
The MS in Computer Science program offers three completion options: thesis, report, or non-thesis/non-report. The thesis option requires six credit hours of CIS 899 for original research that culminates in a written thesis. The report option involves one credit hour of CIS 897 and two credit hours of CIS 898 for project work and a written report. The non-thesis/non-report option requires 30 credit hours of coursework followed by an exit interview.
Students must receive a grade of ‘B’ or better for each course that satisfies program requirements. This standard ensures graduates demonstrate strong competency across all required areas before they receive their degree.
2. Newman University – Applied Artificial Intelligence Master’s Program
Newman University offers an available path into artificial intelligence education with its Master of Science in Applied Artificial Intelligence, scheduled to launch in August 2026 pending accreditation review. What makes this program different is that it welcomes students from all academic backgrounds, eliminating the barrier that prevents many professionals from transitioning into AI careers.
Program Overview and Key Features
Newman positions itself as Kansas’s only graduate program in Applied Artificial Intelligence, building on the success of its MS in Data Science program that’s been running for several years. The development involved hiring three full-time faculty members in Computer Science, Data Science, and Mathematics, alongside sustained input from 18 industry advisors who helped shape the curriculum to meet regional workforce needs.
The program architecture reflects a commitment to availability. Unlike traditional AI programs requiring extensive quantitative or computing backgrounds, Newman provides bootcamp experiences for every key aspect of the curriculum. These preparatory courses allow students from humanities, business, healthcare, or other non-technical fields to build foundational skills before beginning formal coursework. This design acknowledges that AI expertise benefits from diverse views beyond pure technical training.
Professionals seeking focused training without committing to a full master’s degree can pursue Newman’s 12-credit Graduate Certificate in Applied AI. This option serves graduates who already hold master’s degrees in other fields but want specialized AI capabilities. Certificate students can also participate in the Applied AI Projects course for additional hands-on experience.
The Applied AI Projects course functions as connective tissue across Newman’s graduate programs. This repeatable course enables students from Applied AI, Data Science, and MBA programs to cooperate on cross-functional teams throughout their degree timeline. Teams design, build, and test real-life AI implementations while receiving feedback from regional industry advisors. This structure mirrors actual workplace dynamics where AI professionals work alongside business analysts, domain experts, and stakeholders from various backgrounds.
Newman emphasizes ethical AI development through what it calls a “human flourishing framework”. The program teaches students to ask fundamental questions: What does it take to build ethical, responsible, trustworthy, professional-grade AI applications? The university believes AI, like any technology, requires management with wisdom. This philosophical foundation distinguishes Newman from programs focused purely on technical capabilities.
The program offers flexibility for working professionals with evening and flexible scheduling options. While many components are available online, some courses benefit from in-person collaboration, and hybrid attendance options accommodate different student needs.
Curriculum and Core AI Courses
The curriculum positions four specialized Applied AI courses atop a solid Data Science foundation. This layered approach ensures students understand data fundamentals before advancing to AI-specific techniques. The program organizes learning into three main competency categories.
Core AI Competencies cover the technical foundation. Students develop skills in AI Foundations, Descriptive Analytics, Database Systems, Machine Learning, Deep Learning, and MLOps. These courses progress from understanding AI concepts through implementing machine learning models to deploying and maintaining AI systems in production environments. MLOps particularly addresses the gap between experimental models and operational systems that deliver business value.
Strategic Leadership Skills prepare graduates to drive organizational AI adoption. The curriculum includes AI Implementation, Strategic AI Leadership, Process Optimization, Change Management, and ROI Analysis. Successful AI projects require more than technical execution. Students learn to communicate AI capabilities to non-technical stakeholders, manage resistance to automation, and demonstrate business value through return on investment metrics.
Ethical and Professional Development components integrate throughout the program. Students study AI and Human Flourishing, Legal and Regulatory Compliance, Stakeholder Communication, Responsible AI Design, and Global AI Perspectives. These courses address urgent questions about data privacy, algorithmic fairness, and societal impacts of AI technologies. The global perspective component examines how different cultures and regulatory environments approach AI governance.
The program emphasizes practical applications over theoretical abstraction. Students learn to review trustworthiness of AI outputs, protect privacy and intellectual property, deploy Large Language Models, and build both predictive and prescriptive AI systems. This curriculum prepares graduates to work with generative AI, neural architecture design, and other cutting-edge techniques transforming industries.
Admission Requirements and Prerequisites
Newman’s admission philosophy prioritizes potential over pedigree. The program explicitly does not require a quantitative or computing background. This open-door approach makes AI education available to professionals in healthcare, business, education, agriculture, and other fields who recognize AI’s relevance to their domains.
Students without programming experience can take foundational courses such as Programming for Everyone I and II. Basic understanding of programming, preferably Python, helps students succeed once formal coursework begins. The university provides bootcamp experiences for those needing preparatory work prior to beginning formal courses.
International students must demonstrate English proficiency. Students considering graduate studies or more advanced technical roles receive guidance to pursue additional coursework in algorithms, probability, linear algebra, and calculus. These mathematical foundations support deeper understanding of machine learning theory, though they’re not mandatory for admission.
Graduate program admissions at Newman generally require completed applications and official transcripts from all undergraduate institutions attended. The flexibility extends to students with advanced standing, who may gain admission through Recognition of Prior Experiential Learning or Recognition of Prior Certificated Learning processes. Mature applicants with requisite prior learning or relevant work experience receive individual consideration, particularly those with more than two years of industry experience.
This inclusive admission structure reflects Newman’s belief that diverse backgrounds strengthen AI development. Teams comprising members from technical and non-technical fields often produce more robust solutions than homogeneous groups of computer scientists.
Career Prospects and Job Outcomes
Graduates enter a field experiencing remarkable expansion. Between 2020 and 2025, more than 73,000 employers actively sought qualified candidates with AI expertise, averaging nearly 10,000 new hires per month. The number of U.S. job listings requesting AI skills increased more than 600% over the last decade. Newman cites 88% annual growth in demand for AI professionals.
The program prepares students for diverse roles. Machine Learning Engineers design, build, and deploy machine learning models for recommendation systems, automated decision making, and predictive analytics. AI Engineers focus on designing, implementing, and maintaining AI systems across various applications. Data Scientists apply AI and statistical techniques to extract insights from complex datasets.
Specialized positions include Deep Learning Specialists who work with neural networks for image recognition and natural language processing. Computer Vision Engineers develop systems analyzing visual data for applications ranging from medical imaging to autonomous vehicles. NLP Engineers create systems interacting with human language, powering chatbots, translation services, and document analysis platforms.
Emerging roles include AI Product Managers who bridge technical teams and business stakeholders, Prompt Engineers who optimize interactions with large language models, and AI Specialists in specific domains like healthcare CT imaging. The program’s cross-functional project experience particularly prepares graduates for product management and consulting roles requiring both technical understanding and communication skills.
Kansas presents specific regional advantages for AI graduates. Newman highlights opportunities in aviation with companies like Textron, Spirit, and Bombardier. Agriculture employers including Cargill and ADM seek AI expertise for crop monitoring and yield optimization. Healthcare systems such as Via Christi and Wesley implement AI for diagnostics and patient care. Manufacturing firms like Koch and Coleman automate processes and improve quality control. Energy companies Evergy and Black Hills optimize grid management and resource allocation. Financial services institutions develop fraud detection and risk assessment systems.
A national report found that 88% of organizations have adopted AI in some form, but fewer than 10% have integrated it into how work gets done. This implementation gap creates opportunities for graduates who understand both AI capabilities and organizational change. Regional surveys show 81% of respondents using AI tools, yet 68% still need AI training. These statistics demonstrate sustained demand for professionals who can bridge the gap between AI availability and effective deployment.
Tuition Costs and Financial Aid Options
Newman University’s graduate tuition structure varies by program. Based on the 2025-26 cost of attendance for graduate students enrolling in 6 credit hours per semester, tuition runs $520 per credit hour for most graduate programs. A typical master’s program requiring 30-36 credit hours would cost between $15,600 and $18,720 before fees.
Additional fees add $365 per semester for part-time enrollment. Books and supplies cost approximately $685 per semester, though actual expenses vary based on specific course requirements. Students should budget for these additional costs when planning their investment in the program.
Newman froze undergraduate tuition rates at $35,500 annually, bucking national trends where private nonprofit four-year institutions increased tuition by 4%. This commitment to affordability extends across the university’s programs. Average institutional aid reaches $26,518, reducing the average net cost substantially for aided students.
Graduate students can access various financial aid resources. The university encourages all students to file the FAFSA, which serves as the gateway to federal loans and many merit aid considerations. The financial aid office assists students in exploring scholarships, grants, and other aid resources to minimize financial stress.
Students uncertain about committing to a full master’s program can pursue the 12-credit Graduate Certificate in Applied AI as a lower-cost entry point. At $520 per credit hour, the certificate would cost approximately $6,240 plus fees. This allows professionals to test their interest in AI and gain immediately applicable skills before deciding whether to pursue the complete master’s degree. Credits earned through the certificate can often transfer toward the full MS program if students choose to continue their education.
The program’s evening and flexible scheduling specifically accommodates working professionals who want to maintain employment while studying. This allows students to apply new knowledge immediately in their current roles while earning income to offset educational costs. The hands-on Applied AI Projects course provides portfolio-worthy work that demonstrates capabilities to potential employers, potentially accelerating career advancement and salary increases that offset tuition investment.
Next Steps
Artificial Intelligence is the future and a masters in AI is a worthy path to consider as it will provide you with the knowledge and skills to be at the forefront. Continue your education with one of these Kansas schools and you will be prepared for the career of your choosing.