Program Overview

MS-AI Online Curriculum and Degree Requirements

The MS-AI requires a minimum of 30 credit hours of approved, degree-eligible graduate-level coursework. Before graduation, students must have a minimum cumulative grade-point average (GPA) of 3.00 and a grade of B or better in each breadth class (including the two required pathways).

Prerequisites

This program does not require formal prerequisites, but learners are recommended to be familiar with particular subjects. These suggested courses are not required and do not count for credit toward the MS-AI degree.

What to Expect

• This is a graduate-level program, and students should have equivalent prior knowledge of college-level coursework and comport themselves as a graduate professional with their peers, program staff, and faculty.
• Students should be comfortable in a self-motivated learner environment.
• Students are expected to read and understand program policies, follow course instructions, and reach out through proper channels for support.

Degree Requirements

The MS-AI on Coursera is a non-thesis degree program that requires 30 credit hours of graduate-level coursework. This includes 15 credits of required Breadth courses, including the Pathway courses, and a choice of 15 Elective credits. Students must either complete 5 Elective specializations or a combination of 4 complete Elective specializations and three 1-credit Electives totaling 15 credits.

Performance-Based Admissions

The MS-AI on Coursera uses performance-based admissions, which means students earn program admission simply by performing well in a three-course Pathway specialization. To be admitted to the program, students enroll in and complete their preferred three-course Pathway specialization with a grade of B or better in each of the three courses, have a cumulative GPA of at least 3.00 for all for-credit courses taken to date, and declare intent to seek the degree via the enrollment form.

Curriculum Overview

The Master of Science in Artificial Intelligence (MS-AI) program hosted online through the Coursera platform offers stackable graduate-level courses and a fully accredited master’s degree in artificial intelligence. MS-AI on Coursera students earn the same credentials as on-campus students.

Pathway Specializations

• Machine Learning: Theory & Hands-On Practice with Python Specialization (3 credits)
  • CSCA 5622: Introduction to Machine Learning: Supervised Learning (1 credit) – Cross-listed with DTSA 5509
  • CSCA 5632: Unsupervised Algorithms in Machine Learning (1 credit) – Cross-listed with DTSA 5510
  • CSCA 5642: Introduction to Deep Learning (1 credit) – Cross-listed with DTSA 5511
• Foundations of Probability and Statistics (3 credits)
  • APPA 5001: Probability Foundations for Data Science and AI (1 credit) - Cross-listed with DTSA 5001
  • APPA 5002: Discrete-Time Markov Chains and Monte Carlo Methods (1 credit) - new course for MS-AI degree, in development (Available Fall 1, 2025)
  • APPA 5003: Statistical Estimation for Data Science and AI (1 credit) - Cross-listed with DTSA 5002

Breadth

There are 15 required Breadth courses, including the Pathway Breadth courses. Once you complete a Pathway Breadth specialization with a B or better in each course, you are admitted to the program.

• Machine Learning: Theory & Hands-On Practice with Python Specialization (3 credits)
  • CSCA 5622: Introduction to Machine Learning: Supervised Learning (1 credit) – Cross-listed with DTSA 5509
  • CSCA 5632: Unsupervised Algorithms in Machine Learning (1 credit) – Cross-listed with DTSA 5510
  • CSCA 5642: Introduction to Deep Learning (1 credit) – Cross-listed with DTSA 5511
• Foundations of Probability and Statistics (3 credits)
  • APPA 5001: Probability Foundations for Data Science and AI (1 credit) - Cross-listed with DTSA 5001
  • APPA 5002: Discrete-Time Markov Chains and Monte Carlo Methods (1 credit) - new course for MS-AI degree, in development (Available Fall 1, 2025)
  • APPA 5003: Statistical Estimation for Data Science and AI (1 credit) - Cross-listed with DTSA 5002
• Artificial Intelligence Ethics Specialization (title TBD) (3 credits)
  • CSCA 5204: Current Issues in Ethics and AI (1 credit) (Available Fall 2, 2025)
  • CSCA 5274: AI Regulation (1 credit)
  • CSCA 5284: AI and the Future of Society (1 credit)

Electives

Select 15 Elective credits, including at least four full specializations.

• Data Mining Foundations and Practice Specialization (3 credits)
  • CSCA 5502: Data Mining Pipeline (1 credit) – Cross-listed with DTSA 5504
  • CSCA 5512: Data Mining Methods (1 credit) – Cross-listed with DTSA 5505
  • CSCA 5522: Data Mining Project – Cross-listed with DTSA 5506
• Introduction to Robotics with Webots Specialization (3 credits)
  • CSCA 5312: Basic Robotic Behaviors and Odometry (1 credit) - Cross-listed with MS-CS
  • CSCA 5332: Robotic Mapping and Trajectory Generation (1 credit) - Cross-listed with MS-CS
  • CSCA 5342: Robotic Path Planning and Task Execution (1 credit) - Cross-listed with MS-CS
• Natural Language Processing: Deep Learning Meets Linguistics (3 credits)
  • CSCA 5832: Fundamentals of Natural Language Processing (1 credit) – Cross-listed with DTSA 5747
  • CSCA 5842: Deep Learning for Natural Language Processing (1 credit) – Cross-listed with DTSA 5748
  • CSCA 5852: Model and Error Analysis for Natural Language Processing (in development) (1 credit) – Cross-listed with DTSA 5749

Outside Electives

You can apply up to six graduate-level credit hours/2 specializations of courses offered by other CU degrees on Coursera toward the MS-AI on Coursera degree.

Non-Degree Courses

Non-degree courses will not count toward the MS-AI degree and students will not be allowed to use them toward any degree requirements.

• DTSA 5302 Cybersecurity for Data Science
• DTSA 5303 Ethical Issues in Data Science
• DTSA 5501 Algorithms for Searching, Sorting, and Indexing
• DTSA 5502 Trees and Graphs: Basics
• DTSA 5707 Deep Learning Applications for Computer Vision

CU Boulder Graduate Certificates on Coursera

You can also pursue graduate CU certificates on Coursera on the way to your MS-AI degree. Currently, the following programs offer graduate CU certificates on Coursera:

• Master of Science in Computer Science, (AI graduate certificate) on Coursera
• Master of Engineering in Engineering Management (ME-EM) on Coursera
• Master of Science in Data Science (MS-DS) on Coursera
• Master of Science in Electrical Engineering (MS-EE) on Coursera

CU certificates on Coursera are stackable. That means you can count credits first earned as part of a CU certificate toward the 30-credit MS-CS degree. To earn a CU certificate on Coursera, you must maintain a cumulative certificate GPA of 3.00 or higher. Individual certificates may have additional requirements. CU certificates on Coursera are automatically awarded once all requirements are met.