Online Master of Science in Applied Artificial Intelligence

Prepare for careers in machine learning engineering, AI engineering, applied data science, and AI systems development across high-growth technical industries.

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Home » Online Programs » Masters » Online Master of Science in Applied Artificial Intelligence

At a Glance

Advance your career with the University of Oklahoma’s online Master of Science in Applied Artificial Intelligence. Designed for working professionals, emerging technologists, and STEM-focused learners, this flexible program builds advanced expertise in machine learning, deep learning, natural language processing, and AI systems.

Whether you want to deepen your technical specialization or lead AI-driven initiatives, you’ll gain the skills to design, develop, evaluate, and deploy AI solutions in real-world environments. Through rigorous coursework and flexible electives, the program combines advanced technical training with hands-on application, preparing you for high-impact roles across technology, healthcare, energy, cybersecurity, defense, government, and other AI-driven industries.

100% Online

Time to Complete:

18+ months

Credit Hours:

30 total

Time Commitment:

15 to 20 hours weekly

start dates

Fall, Spring, Summer

cost

The MS in Applied Artificial Intelligence delivers a strong return on investment by preparing you for advanced roles in machine learning engineering, AI systems development, and high-growth technical fields. OU Online is committed to making that investment accessible and transparent.

Tuition and fees for the program are approximately: $30,450 ($1015 per credit hour for 30 credit hours). Books and additional materials are not included.

*Time to completion varies based on transfer credits accepted and enrollment pace.

START HERE

Share a few details and we'll connect you with an enrollment coach to discuss your goals and next steps.

By submitting my information, I consent to being contacted by The University of Oklahoma and/or OU Education Services via SMS/text message, phone, email, and other electronic means, including through the use of an automatic telephone dialing system, AI-powered technologies, and artificial or pre-recorded voice, for purposes related to OU’s program portfolio; my contact information will not be shared with third-party affiliates. Message and data rates may apply. Opt-out of communications any time by replying STOP to SMS, asking to be removed during a call, or clicking the unsubscribe link in emails. For support, refer to the Privacy Policy and Terms of Service for more details.

About the Master of Science in Applied Artificial Intelligence Online Program

The University of Oklahoma’s online Master of Science in Applied Artificial Intelligence is a fully online, 30-credit-hour program designed for professionals seeking advanced expertise in machine learning, deep learning, natural language processing, and AI systems. Offered through the Gallogly College of Engineering and the OU Polytechnic Institute, the program prepares graduates to design, develop, evaluate, and deploy AI solutions for complex, real-world challenges.

The curriculum combines rigorous AI coursework with applied training in machine learning, responsible AI, and AI system development. Students build technical depth while developing practical skills in system design, model evaluation, and data-driven problem-solving. Flexible electives in areas such as computer vision, cybersecurity, cloud computing, DevOps, databases, and analytics allow students to tailor the program to their career goals.

The degree culminates in either an online thesis or an applied practicum, providing the opportunity to apply advanced AI competencies in a research or professional setting.

MS in Applied Artificial Intelligence: Career Paths in Machine Learning, AI Systems, & Applied Computing

OU’s online Master of Science in Applied Artificial Intelligence prepares graduates for advanced careers across artificial intelligence, machine learning engineering, data science, and AI systems development. Whether you plan to advance in your current technical role or transition into specialized AI work, this degree helps you build skills in machine learning, deep learning, natural language processing, AI system design, model evaluation, and production-oriented AI workflows. Graduates are prepared for roles in technology companies, healthcare systems, energy organizations, financial services, cybersecurity firms, government agencies, defense and aerospace sectors, and other industries that rely on intelligent systems and data-driven decision-making. Career opportunities in Applied Artificial Intelligence include:

  • MLOps Engineer
  • AI Solutions Engineer
  • AI Product Manager
  • Computer Vision Engineer
  • AI Systems Analyst
  • AI Ethics or Responsible AI Analyst

Whether you're interested in building and deploying machine learning systems, developing AI-powered applications, or leading AI-driven initiatives within organizations, OU’s MS in Applied Artificial Intelligence provides a strong foundation for careers across today’s rapidly evolving AI and machine learning landscape.

Industry Insights: Artificial Intelligence, Machine Learning, & Data Workforce Outlook

Artificial intelligence, machine learning, and data-driven systems continue to reshape how organizations operate across industries such as technology, healthcare, energy, finance, cybersecurity, government, and defense. OU’s online MS in Applied Artificial Intelligence prepares graduates to design, build, and deploy intelligent systems in environments where machine learning, automation, and predictive analytics are increasingly central to decision-making and operational performance.

As organizations expand their use of artificial intelligence, demand continues to grow for professionals who can develop machine learning models, build scalable AI systems, and evaluate the performance, reliability, and ethical implications of AI-driven technologies. Roles in this space often intersect with data science, software engineering, and systems architecture, reflecting the cross-functional nature of modern AI work.

Median Pay:

  • Data Scientists: $103,500 annually*

Job Outlook:

Employment in data science and related computational fields continues to grow faster than the average for all occupations, driven by expanding adoption of artificial intelligence, machine learning, and advanced analytics across industries.

Job Opportunities:

  • Roles in machine learning engineering, artificial intelligence engineering, and applied data science
  • Opportunities developing, deploying, and maintaining AI and machine learning systems in production environments
  • Positions focused on model evaluation, system optimization, and data-driven decision support
  • Roles supporting AI integration across cloud computing, cybersecurity, analytics, and enterprise systems

As artificial intelligence continues to expand across industries, professionals with applied machine learning and AI systems expertise are increasingly essential to building scalable, reliable, and responsible intelligent systems. Graduates may pursue opportunities across technology, healthcare, energy, finance, government, and defense or continue into doctoral study in artificial intelligence, computer science, data science, and related computational fields.

This growth reflects a broader shift toward AI-integrated systems, where technical professionals are expected not only to build models, but to understand how those systems operate within complex organizational and engineering environments.

*The median pay figures reflect earnings for professionals working in these occupations and may represent mid-career compensation. Entry-level salaries vary based on role, employer, experience, and geographic location.

Source: U.S. Bureau of Labor Statistics

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Program Outcomes: What You'll Learn

Program Outcomes: Skills That Set You Apart in Artificial Intelligence and Machine Learning

OU’s online Master of Science in Applied Artificial Intelligence equips graduates with the advanced technical expertise to design, implement, evaluate, and deploy machine learning and AI systems that support data-driven decision-making across complex technical environments. You will develop expertise in machine learning, deep learning, natural language processing, AI system development, and responsible AI while preparing for advanced careers and continued doctoral study in artificial intelligence and related computational fields.

Through this program, you’ll learn how to:

  • Apply foundational concepts of artificial intelligence and machine learning, including mathematical principles, model architectures, and computational methods that underpin modern AI systems
  • Design, implement, and evaluate machine learning and deep learning models using supervised, unsupervised, and advanced neural network approaches
  • Develop and apply natural language processing techniques to build systems that interpret, generate, and analyze human language data
  • Integrate AI models into production-oriented environments, including data pipelines, system workflows, and deployment considerations
  • Assess model performance using evaluation metrics, validation techniques, and system-level analysis to ensure reliability and robustness
  • Evaluate artificial intelligence systems in terms of fairness, transparency, privacy, accountability, and responsible AI principles
  • Communicate technical AI concepts, model behavior, and system limitations to both technical and non-technical stakeholders
  • Collaborate effectively within multidisciplinary teams to develop and deploy AI-driven solutions in real-world environments
  • Apply professional judgment, analytical reasoning, and continuous learning practices as artificial intelligence technologies evolve

Whether you plan to advance in your current role or transition into artificial intelligence-focused careers, OU’s MS in Applied Artificial Intelligence provides a strong foundation for careers in machine learning engineering, AI systems development, applied data science, and advanced computational research pathways.

Program Outcomes: What You'll Learn

Course Details

OU’s Master of Science in Applied Artificial Intelligence prepares students to build advanced expertise in machine learning systems, deep learning, natural language processing, AI system development, and responsible artificial intelligence. The curriculum combines rigorous artificial intelligence foundations with applied technical training to prepare graduates for careers in AI engineering, machine learning engineering, and applied computational fields.

Students begin with foundational graduate-level coursework in artificial intelligence, machine learning, deep learning, natural language processing, and the mathematical principles that support modern AI systems before progressing into advanced applied study focused on AI system development, model evaluation, deployment workflows, and domain-specific applications. Structured elective pathways allow students to build depth in areas such as computer vision, cybersecurity for AI systems, cloud computing, DevOps and CI/CD, advanced databases, and applied analytics, supporting both specialized technical and interdisciplinary career pathways.

The program includes a required culminating experience, completed as either a fully online thesis or an applied master’s practicum, providing a structured opportunity to apply advanced AI and machine learning skills in a research-focused or professionally applied environment.

Coursework is delivered in a flexible, fully online format designed for working professionals and emerging technologists. Students complete 30 credit hours.

Artificial Intelligence and Machine Learning Courses

  • Essential Math for AI
  • Fundamentals of Applied Machine Learning
  • Ethics of AI and Machine Learning
  • Natural Language Processing
  • Deep Learning I
  • Advanced Database Systems
  • Introduction to Cybersecurity Leadership
  • Behavioral Cybersecurity
  • Insider Threat and Risk Management
  • Software Project Management
  • DevOps - CI/CD
  • Agentic Systems
  • Master's Practicum

Expand each section below to view more about the courses included in this program, including detailed course descriptions.

Essential Math for AI

Credit Hours: 3
This course introduces the mathematical disciplines that form the foundation for AI/ML algorithms and methods. Selected topics include: linear algebra, matrix decompositions, analytic geometry, elements of vector calculus, and probability/statistics.

Ethics of AI and Machine Learning

Credit Hours: 3
This course provides a survey of legal and ethical topics associated with AI and ML. Global laws and regulations associated with AI and ML are reviewed and their impact on practitioners will be discussed. The algorithmic causes of bias will be reviewed, and methods to alleviate those will be discussed. Methods for bias measurement in AI/ML models will be presented.

Deep Learning I

Credit Hours: 3
This course will introduce deep learning through neural network programming. The course introduces the concept of the artificial neuron and progresses to describe multi-layer neural networks with a focus on the mathematics that make them work. The course describes how TensorFlow and PyTorch solve neural networks, and students build basic neural networks using these tools.

Introduction to Cybersecurity Leadership

Credit Hours: 3
This course provides an in-depth exploration of insider threats within organizations and the strategies for managing and mitigating these risks. Students will learn about the motivations behind insider threats, detection methods, prevention techniques, and deterrence mechanisms.

Insider Threat and Risk Management

Credit Hours: 3
This course provides an in-depth exploration of insider threats within organizations and the strategies for managing and mitigating these risks. Students will learn about the motivations behind insider threats, detection methods, prevention techniques, and deterrence mechanisms.

DevOps - CI/CD

Credit Hours: 3
This hands-on Development and Operations (DevOps) course delves into the concepts of containerization, orchestration, and Infrastructure as Code using popular tools and platforms. It focuses on practical skills such as continuous integration and deployment (CI/CD), emphasizing security best practices and automated testing. Students will learn to build and deploy to the cloud, demonstrating proficiency in end-to-end development pipelines.

Master's Practicum

Credit Hours: 3
The course provides students with knowledge and skills in all areas of artificial intelligence. Students will work in small groups to identify and solve current artificial intelligence challenges. Students will be required to write a proposal about their project, create a work plan to solve the problem/challenge, and create a final report, with final presentation.

Fundamentals of Applied Machine Learning

Credit Hours: 3
This course explores mathematical concepts in ML. Integrating theory and applications, topics include types of learning, classical machine learning methods, neural networks, probabilistic modeling, and optimization. Through Python-based Jupyter notebooks and open-source software, students develop fluency in designing, analyzing, evaluating ML systems, and preparing for impactful research and innovation in both academic and industry settings.

Natural Language Processing

Credit Hours: 3
This course will provide a review of natural language processing (NLP) methods. It presents the intuition behind major approaches to NLP problems such as translation. Concepts include word corpora, probabilistic methods, and Python libraries including NLTK and SpaCy. The course presents generative AI with a focus on transformers and modern tools such as OpenAI.

Advanced Database Systems

Credit Hours: 3
This course focuses on technologies used for massive datasets and unstructured data. Students learn how to implement Spark RDBs with distributed computing resources. The course presents NoSQL databases, their use and implementation. Graph databases and management of unstructured data and its incorporation into databases are presented. In all cases, students will build and manage databases using current common application frameworks.

Behavioral Cybersecurity

Credit Hours: 3
This course explores the interdisciplinary field of behavioral cybersecurity, emphasizing the role of human personality in cybersecurity practices. It aims to address the growing challenges posed by the digital age. Course will examine the application of psychological methods, profiling techniques, and the use of game theory in understanding human behavior.

Software Project Management

Credit Hours: 3
This course introduces project management techniques and their application to software development. The course will cover waterfall and agile project management approaches and will cover tools and methods of each approach. Students will work in small teams to build an application to develop a database application aimed at solving a typical task applying agile techniques using project management software.

Agentic Systems

Credit Hours: 3
Introduces agentic AI systems that perform goal-directed work across digital tools and workflows. Topics include planning, orchestration, tool integration, human oversight, evaluation, governance, and the redesign of information work. Students analyze, prototype, and assess agentic systems for reliability, usability, and organizational effectiveness.

Why OU

Why OU Online: Flexible Learning for Future Artificial Intelligence Professionals

OU Online delivers high-quality, career-focused programs designed for working professionals, emerging technologists, and STEM-focused learners, combining the flexibility of online learning with the academic excellence of the University of Oklahoma’s Gallogly College of Engineering and the OU Polytechnic Institute.

With a curriculum grounded in machine learning systems, deep learning, natural language processing, AI system development, and responsible artificial intelligence, this degree helps students build skills in model development, system design, deployment workflows, and applied computational problem-solving. A required culminating experience—completed as either a fully online thesis or applied master’s practicum—provides a structured opportunity to apply advanced AI and machine learning skills in either a research-focused or professionally applied environment.

Whether you plan to advance your education, deepen your technical specialization, or transition into artificial intelligence-focused roles, OU Online provides the flexibility, support, and academic rigor to help you reach your goals while balancing work, career, and other responsibilities.

Faculty Expertise: Real-World Leadership in Artificial Intelligence and Machine Learning

Learn from faculty who bring both academic expertise and applied experience in artificial intelligence, machine learning, deep learning, natural language processing, and data-driven systems. Faculty in the Gallogly College of Engineering and the OU Polytechnic Institute are engaged in research, teaching, and applied work that informs the rapidly evolving field of artificial intelligence and computational systems. Their mentorship helps you build advanced, industry-relevant knowledge and prepare for careers and doctoral study in artificial intelligence, machine learning, and applied computing fields.

Robust Student Support

OU Online provides comprehensive student support services designed to help students succeed in fully online artificial intelligence programs. From academic support and online tutoring to advising and career development resources, students in the MS in Applied Artificial Intelligence receive guidance throughout their academic journey. The program’s flexible format is designed to support working professionals and emerging technologists balancing graduate study with professional and personal responsibilities.

Global Alumni Network

When you earn your degree from the University of Oklahoma, you join a broad network of alumni working in artificial intelligence, machine learning engineering, data science, software engineering, and technology-driven industries around the world. OU graduates contribute to innovation across technology, healthcare, energy, finance, government, and defense, creating connections that can support mentorship, professional growth, and career opportunities in AI and related fields.

Why OU

Flexible Format

The MS in Applied Artificial Intelligence is delivered in a flexible, 100% online format designed for working professionals, emerging technologists, and STEM-focused learners. Courses are structured to support asynchronous learning, allowing you to study on your schedule while balancing work and personal commitments. With fall, spring, and summer start terms, the program supports continuous academic progress at a pace that fits your goals.

Tailored Experience

Structured elective pathways allow you to tailor your degree based on your interests and career goals. Students build depth in areas such as computer vision, cybersecurity for AI systems, cloud computing, DevOps and CI/CD, advanced databases, and applied analytics, creating flexible pathways into roles in machine learning engineering, AI systems development, applied data science, and specialized AI applications, as well as preparation for doctoral study in artificial intelligence and related fields.

Cost & Financial Aid

Earning your Master of Science in Applied Artificial Intelligence is an investment in your future, and OU Online is committed to providing clear and transparent cost information.

Tuition and fees for the program total $30,450 ($1015 per credit hour). Books and additional materials are not included.

Financial aid, scholarships, and employer tuition assistance may be available to help reduce your out-of-pocket costs. Our dedicated financial services team will guide you through every step of the funding process—so you can stay focused on your education and career goals.

For questions about financial aid for your online program, contact the Online Aid office at onlineaid@ou.edu or call 405-325-2929.

A nonrefundable deposit of $350 is required upon admission to secure your place in the program. This deposit guarantees your spot in your first semester of courses and will be applied toward your first semester’s tuition.

*Please be aware that tuition and fees may change, as determined by the Oklahoma State Regents for Higher Education.

Transfer Credit

You can transfer up to 12 credit hours of graduate-level coursework per Graduate College policy and with approval of the department. Credit must be graduate level with a grade of B or better. The credit must be less than 5 years old and can’t have been used toward any other degree.

Take the Next Step

To apply to the online Master of Science in Applied Artificial Intelligence, you must hold a bachelor’s degree from a regionally accredited college or university (or the international equivalent). Applicants should have a foundational background in programming and mathematics appropriate for graduate-level study in artificial intelligence and machine learning.

Admission Requirements

  • Hold a bachelor’s degree from a regionally accredited college or university (or international equivalent)
  • Have a minimum cumulative GPA of 2.5
  • Complete the online application at https://gograd.ou.edu/apply/
  • Submit official transcripts from all previously attended institutions
  • Provide a current professional resume
  • Submit a written personal statement
  • International applicants whose first language is not English must submit TOEFL or IELTS scores

Admissions Process

  • Complete the online application at https://gograd.ou.edu/apply/
  • Submit official transcripts from all previously attended institutions
  • Provide a current professional resume
  • Submit a written personal statement
  • International applicants whose first language is not English must submit TOEFL or IELTS scores

Application Timeline

The admissions committee follows a rolling admissions process, reviewing applications as they are received. While admissions may remain open until two weeks before classes begin, applicants are encouraged to apply early to ensure timely consideration.

Once your application is complete, the committee typically responds within two weeks, helping you move forward with your academic and professional goals efficiently.

Step 1

Contact an Enrollment Coach to discuss your qualifications and interest in the program.

Step 2

Step 3

Provide undergraduate transcripts for all prior institutions.

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START HERE

Share a few details and we'll connect you with an enrollment coach to discuss your goals and next steps.

By submitting my information, I consent to being contacted by The University of Oklahoma and/or OU Education Services via SMS/text message, phone, email, and other electronic means, including through the use of an automatic telephone dialing system, AI-powered technologies, and artificial or pre-recorded voice, for purposes related to OU’s program portfolio; my contact information will not be shared with third-party affiliates. Message and data rates may apply. Opt-out of communications any time by replying STOP to SMS, asking to be removed during a call, or clicking the unsubscribe link in emails. For support, refer to the Privacy Policy and Terms of Service for more details.

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