Fairfax University of America

MS in Artificial Intelligence and Machine Learning

• Apply AI and ML algorithms to draw inferences, design smart applications to solve real-world problems, and automate the development of AI systems and components.
• Model human behaviors to develop Human-AI systems and evaluate their performance.
• Improve overall integrated system performance to influence human performance and learning.
• Apply social, ethical, and legal principles of technologies and their applications in the AI and ML field.
• Communicate effectively individually or in cross-functional teams.

• AI Specialist
• Applied Artificial Intelligence and Machine Learning-Scientist
• AWS Machine Learning Engineer
• Robotic Process Automation Programmer
• Artificial Intelligence Engineer
• Robotics Programmer
• Machine Learning Engineer
• Instructor at a college or university teaching AI and ML in addition to Computer Science courses

The Master of Science in AI and ML requires the completion of 36 credits. Students will take 12 credits of core courses, 6 credits for career application, and 18 credits in AI and ML content areas.

Program Prerequisites

All new AI and ML program students need certain basic skills to prepare them for success in the AI and ML Program. The AI and ML degrees provide a broad understanding of the theory and technology of this field. Students who do not have the required background need to take some or all of the prerequisites before taking the core courses. Thus, to be successful, students must have a background in the following courses.

• COMP 109 Computer Algorithm and Programming Logic Using Python
• COMP 260 Introduction to Operating Systems
• COMP 270 Essentials of Networking
• COMP 329 Data Structures and Algorithm Analysis
• COMP 350 Database Concepts

Core Courses (4 Courses – 12 Credits)

These courses provide a breadth of foundational knowledge to implement computer interfaces, software design, communication between systems, and how to manage IT systems. These are all crucial elements for IT professionals to apply these building blocks to any given system or project.

• COMP 501 Advanced Operating Systems
• COMP 502 Design and Analysis of Algorithms
• COMP 503 Networking and Telecommunications
• COMP 504 Database Management Systems

Application Courses (2 Courses – 6 Credits)

These courses offer an opportunity for students to apply what they have learned throughout the program to a practical project or to a master’s thesis. While the practical project provides for the application of knowledge acquired throughout the program and would represent work that could demonstrate career readiness to potential employers, the thesis would generally serve to demonstrate a student’s research potential and could be used to demonstrate readiness for doctoral work. Regardless of the option, students will demonstrate basic research knowledge and abilities, which would be used toward the completion of either the project or thesis.

• COMP 505 Research Methods
• Choose One:
• COMP 681 AI and ML Capstone Project
• COMP 698 Master Thesis
  • COMP 681 AI and ML Capstone Project
  • COMP 698 Master Thesis

Specialization Courses (Any 6 Courses – 18 Credits)

These advanced courses cover the depth of topics related to AI and ML and allow students to develop their knowledge based upon their intended professional trajectories.

• COMP 513 Robotics Design and Programming
• COMP 514 Neural Networks
• COMP 515 Pattern Recognition
• COMP 516 Deep Learning
• COMP 517 Special Topics in AI
• COMP 518 Special Topics in ML
• COMP 521 Smart Devices Design and applications
• COMP 522 Data Mining
• COMP 593 Internship I in AI and Machine Learning
• COMP 610 Cognitive Computing
• COMP 611 Data Warehousing
• COMP 613 Game Design
• COMP 614 Speech Recognition
• COMP 617 AWS Certified Machine Learning
• COMP 618 10 Google Machine Learning
• COMP 693 Internship II in AI and Machine Learning

Note: Students who wish to take a course that is offered by another program may petition to do so to their advisor by providing justification for the relevance of the addition as part of their professional trajectory, their intended consulting project, and/or personal interest. A maximum of 2 courses can be applied to another program.