Artificial Intelligence Master's Degree Online

About the Artificial Intelligence Master’s Degree Online

The online Master of Science in Artificial Intelligence (MSAI) program at Columbia University is designed for highly motivated graduate students who wish to broaden their knowledge and skills in AI and related technologies. Students completing the program will be awarded a Master of Science in Artificial Intelligence degree, and they will receive an annotation of the specific concentration (e.g., AI infrastructure) on their transcript.

This online AI master's degree program is a part-time, fully online, cohort-based program, with a rigorous five-semester AI curriculum anchored in Computer Science and Engineering with formalized pathways to apply AI in various fields. These specialized concentrations are designed to leverage Columbia Engineering’s unique excellence in related fields in Engineering, such as operations/finance, AI infrastructure, and advanced computing.

What jobs can an Artificial Intelligence Master’s lead to?

Columbia Engineering’s online AI master’s degree program prepares you for a pioneering career bridging the gap between emerging AI technologies and the various disciplines it is impacting. You will have access to career support services at Columbia Engineering to determine the best way to bring your unique skills to your chosen field. In addition to providing students with career counseling resources such as resumé and cover letter help, our career team also networks with industry leaders to source job opportunities that align with the program’s curriculum.

With the prevalence of artificial intelligence (AI) across society and its rapid advancement, there are unprecedented demands for talented graduates trained with solid AI foundational skills as well as novel applications in specific domains. Students who complete the online AI masters degree program will be qualified to work in leadership and other roles that fill the gap between technical understanding and domain verticals.

Admission Requirements

Education: A bachelor's degree received from an institution of acceptable standing. An undergraduate STEM degree is recommended, but not required.

Technical Skills: Proficiency in programming (especially Python), data structures/algorithms, linear algebra, and calculus/probability.

Please submit your application by August 15 to guarantee a decision for the Fall 2026 cohort.

Apply to the Online AI Master’s Degree

GRE test scores are optional. If you have taken the exam and would like to provide your scores, you may do so, but it is not required. Students who do not submit scores will not be penalized in the graduate admissions review process.

Copies of transcripts from all previously attended post-secondary colleges/universities. Unofficial transcripts are sufficient for the application. If given an offer of admission, you will be required to send official transcripts.

Three (3) recommendation letters

Include a copy of your resume or CV.

The personal/professional statement is an essay that serves as both a writing sample and an opportunity to discuss who you are and why you are a good fit for our program. A wide range of topics—including background information, descriptions of professional experiences or important personal choices, and reflections on life—may be addressed in the essay. Ideally, applicants should reveal qualities demonstrative of their intelligence, compassion, good judgment, energy, leadership, communicative ability, self-awareness, commitment, motivation and integrity. It should be roughly 250–1,000 words.

Required for applicants whose undergraduate or graduate degree was earned in a country other than Australia, Canada, Ireland, New Zealand, Singapore, the UK, Ghana, Nigeria, Kenya, and the United States of America.

Acceptable exams include TOEFL, IELTS, PTE Academic Test, or Duolingo English Test

Completion Requirements

Students must complete all core courses and designated electives for a total of 30 graduate points of academic work via Columbia Engineering Online while maintaining an overall grade point average of 2.67 or better. These courses will be completed in five sequential semesters following the online cohort course schedule. Cohorts will start in both spring and fall semesters, and courses will occur in all three terms (fall/spring/summer).

Course List

Core Courses (12 points)

The four core courses will educate students in both the fundamentals and the advanced, cutting-edge developments in artificial intelligence, including machine learning, deep learning, and natural language processing. Students must complete all four classes:

  • COMS W4701: Artificial Intelligence
  • COMS W4771: Machine Learning
  • COMS W4705: Natural Language Processing
  • COMS W4710: Ethical and Responsible Artificial Intelligence

Elective Courses (12 points)

MSAI students will select a concentration, and must complete four - six courses according to their chosen concentration. Within each concentration, students will select from electives on topics including:

AI in Finance & Operations Concentration

  • Quantitative Finance & FinTech AI
  • Optimization & Prescriptive Analytics
  • Stochastic Modeling & Simulation
  • Networks, Markets & Supply Chains

AI Infrastructure Concentration

  • Systems Implementation at Scale
  • Networking, Security & Reliability
  • Embedded Intelligence
  • Heterogeneous Accelerators

AI and Advanced Computing

  • Foundations of AI & Intelligent Algorithms
  • Scalable & Robust Computing Systems
  • Data, Perception & Multimodal Intelligence
  • Trustworthy, Human‑Centered & Secure AI

Additional electives and/or capstone (6 points)

In addition to a list of approved electives, our online AI master’s degree program allows for a capstone project integrating the skills students developed in the core curriculum with the knowledge from their elective concentration. The independent research component of the Capstone is conducted in close collaboration with one or more faculty advisors and builds directly on the skills developed in project management, team formation, and conflict resolution. Capstone projects are expected to have strong engagement from industry partners to ensure that projects address real-world challenges.