* On Campus is a Fall start only.

Become an expert in Applied Artificial Intelligence, a field in high demand with countless career opportunities.

Artificial Intelligence (AI) has become an integral part of our lives.  We use conversational AI daily by interacting with ChatGPT, Alexa, and other similar systems. We analyze data with the help of machine learning models. We authenticate through image & face recognition performed by neural networks and deep neural networks. This program is designed to prepare students for a variety of exciting careers in applied AI. You will gain knowledge of AI models and AI development tools, and also learn to build and utilize these models to solve specific tasks. 

Degree Requirements and Courses

View Guided Curriculum

• INFS 6070 Introduction to AI
• INFS 6140 Python Language and Programming
• INFS 6244 Database for Data Science
• INFS 6720 Data Mining
• INFS 6255 AI Ethics and Governance
• INFS 6360 AI in Cybersecurity
• INFS 6550 Natural Language Processing
• INFS 6482 Applied Machine Learning
• INFS 6580 Emerging Topics in AI
• One of the following courses:
  • INFS 7400 Applied Research in AI 
  • INFS 7903 Internship

Admissions, Tuition, and Scholarship Information

• Prospective Students should have an undergraduate GPA of 3.0 and above with a degree in computer science, information systems, mathematics, software engineering, or related fields. 
• Students from other fields are welcome to apply, but should note that some experience with introductory statistics and Python programming is recommended.
• Click here for tuition information.

Degree Program Learning Outcomes

Upon successful completion of all requirements for the following key courses in the M.S. in Applied Artificial Intelligence degree, the students will be able to

1. Formulate problems and assess the AI needs of an organization.
2. Apply appropriate techniques and tools to collect and clean the data, prepare, run and fine tune the model in solving AI tasks.
3. Select, apply, and evaluate appropriate AI/ML algorithms and models to provide solutions to data related problems.
4. Interpret and communicate analysis outcomes in oral, visual, and in written form to technical and non-technical professionals.
5. Given an AI model, formulate and explain ethical concerns that arise from using this model.
6. Given an AI model, formulate and explain cybersecurity concerns that arise from using this model.
7. Develop and apply AI solutions that improve cybersecurity.
8. Develop appropriate algorithms to run AI/ML models.
9. Given an original program that was not discussed in your classes, research and evaluate the possible AI-based solutions and choose the one that is the most efficient.

Contact Us

Natalya G. Bromall, Ph.D.

Director, CIS Graduate Programs 
Professor of Computer and Information Systems

Email: bromall@rmu.edu 
Phone: 412-397-6435 
Office Wheatley Center 305

Jamie L. Pinchot, D.Sc.

Department Head, Computer and Information Systems
Professor of Computer and Information Systems

Email: pinchot@rmu.edu
Phone: 412-397-6050 
Office: Wheatley Center 309