Program Overview
Department of Computer Science- Location: Denver, CO
- Length: 18 Months
- Tuition: $20,250
- Website: https://csuglobal.edu/academic-programs/graduate-degrees/masters-science-degree-artificial-intelligence-machine-learning
The Master of Science in Artificial Intelligence and Machine Learning from Colorado State University Global is a fully online graduate program designed for professionals seeking advanced technical skills in AI, software development, and machine learning.
The program consists of 30 credits, typically completed across 12 start dates per year, allowing flexible enrollment and pacing. Students can finish in as little as 12–18 months, depending on their schedule and background.
Cost and Delivery
Tuition is set at $675 per credit, making the total program cost approximately $20,250. As an online degree, it allows working professionals to complete coursework from anywhere, with no on-campus requirements.
CSU Global also offers a tuition guarantee, ensuring rates do not increase after enrollment.
Curriculum and Courses
The curriculum includes 10 core courses, covering topics such as programming, software development, operating systems, algorithms, artificial intelligence, machine learning, and computer vision.
CSC500 – Principles of Programming
This course introduces students to core programming concepts, including conditional logic, loops, and arrays. Students will learn to design and build simple applications using structured programming techniques.
CSC501 – Management for the Computer Science Professional
Students explore how to manage technical teams and projects, with a focus on communication, leadership, systems planning, and risk management. The course prepares students to lead in cross-functional computing environments.
CSC502 – Ethical Leadership in Software Development
This course covers ethical issues in data handling, information security, and digital communication. Students analyze real-world scenarios to develop policies and best practices for ethical decision-making.
CSC505 – Principles of Software Development
Students study object-oriented programming and software development methods, including data structures, classes, and software models. The course emphasizes sound design principles for building scalable applications.
CSC506 – Design and Analysis of Algorithms
This course focuses on algorithm efficiency and complexity, covering sorting, searching, NP-completeness, and data structure selection. Students evaluate algorithm performance in worst and average-case scenarios.
CSC507 – Foundations of Operating Systems
Students learn the fundamentals of operating systems, including abstractions, process management, and multithreading. The course provides essential knowledge for understanding how systems allocate and manage computing resources.
CSC510 – Foundations of Artificial Intelligence
This course introduces core AI techniques such as knowledge representation, optimization, and probability-based reasoning. Students explore AI strategies used in graph analysis and decision-making systems.
CSC515 – Foundations of Computer Vision
Students gain an understanding of image formation, processing, and analysis techniques. The course includes practical applications like filtering, edge detection, and image interpretation.
CSC525 – Principles of Machine Learning
This course examines key machine learning approaches, including supervised, unsupervised, and reinforcement learning. Applications in NLP, computer vision, and data mining are also covered.
CSC580 – Capstone: Applying Machine Learning and Neural Networks
Students apply machine learning and neural network principles in a capstone project. Topics include feedforward networks, perceptrons, and self-organizing systems, with a focus on real-world implementation.
The program concludes with a capstone course focused on neural networks and applied machine learning. Students gain practical experience using tools like Python and TensorFlow.
Admission Requirements
Applicants must have completed advanced coursework in Discrete Mathematics and Probability/Statistics. If not, they may be admitted provisionally and required to complete CSU Global’s equivalent prerequisites. A minimum 3.0 GPA is preferred, though applicants with a lower GPA may take an additional research course (RES500) during the program.
Career Outcomes and Fit
This program is well-suited for professionals in technical roles looking to transition into AI or expand their skills. Graduates are prepared for positions such as AI Engineer, Machine Learning Scientist, and Software Developer, with the median salary exceeding $131,000 according to BLS data. The program is ideal for those with a strong foundation in math and a desire to work on advanced, real-world AI challenges.