Applied Artificial Intelligence M.S.

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Availability
Available - On Campus
Available - Online
Program Credits
30

* On Campus is a Fall start only.

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

The Master of Science in Applied Artificial Intelligence is a graduate degree aimed at fulfilling the growing demand for the AI and ML professionals. It is geared toward applied AI and includes the theoretical concepts of AI/ML, as well as its practical implications, platforms, training techniques and many others. Classes cover common areas of AI, such as general AI models, image processing, Natural Language Processing (NLP), AI in security, AI ethics.

  • Theory: Become familiar with the models used in AI and ML: classification models, neural networks, deep neural networks, and many others.
  • Practical Knowledge:  Design all stages of AI life cycle, from problem definition and preparing data to model development/training, evaluation, and deployment. 
  • Scholar-Practitioner Faculty: Study with professors who are recognized specialists in AI and other relevant fields, such as cloud computing and cybersecurity.
  • Fully Online or On Campus: Complete your degree on-campus or fully online-anywhere/anytime.

$145,000* Average Salary

Possible career paths:

  • AI or ML engineer
  • Data engineer
  • NLP engineer
  • Data scientist
  • AI ethics officer
  • Computer vision engineer
  • AI product manager
  • AI solutions architect

* per the US Bureau of Labor for computer and information research scientists

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A Booming Industry

In 2023, BuiltIn employment platform listed more than 30 local (Pittsburgh) AI companies, all of which were looking to recruit AI/ML professionals. In addition to that, there are countless job opportunities outside of Pittsburgh. CompTIA lists Machine Learning as the 8th top required skills in IT. This degree will provide you with the knowledge and skills that are in extremely high demand in the current job market.

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 must take two prerequisite courses at the undergraduate level, one in statistics and one in Python programming, before beginning the MS Applied AI program. The prerequisite courses can be taken at RMU or another institution and include:
    • Basic knowledge of statistics: STAT2110 Statistics or a similar course
    • Basic knowledge of Python: INFS3240 Python Programming or a similar course
  • Comparable prerequisite courses transferred from another university may be accepted upon review.
  • 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. PinchotJamie 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

Sample Courses:

These are some of the classes for students in this academic program:

Python Language & Programming
Database for Data Science
Introduction to AI

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