1. Carnegie Mellon University
  2. Program
  3. Masters
  4. MS in Electrical and Computer Engineering(Artificial Intelligence)

MS in Electrical and Computer Engineering(Artificial Intelligence)

2 Years On Campus Masters Program

Carnegie Mellon University

Program Overview

Carnegie Mellon University’s Master of Science in Artificial Intelligence (MSAI) is a rigorous, STEM-designated graduate program offered under the Department of Electrical and Computer Engineering (ECE). The program provides a strong foundation in the fundamentals of electrical and computer engineering while enabling in-depth specialization in artificial intelligence, machine learning, robotics, and related domains. It is designed to prepare students for advanced technical, research, and leadership roles in AI-driven industries and academia.

Located in Pittsburgh, CMU is globally recognized for its pioneering work in AI, robotics, and computer science. The MSAI program leverages this ecosystem, allowing students to learn from and collaborate with world-class faculty, research labs, and industry partners. With the guidance of an academic advisor and faculty mentor, each student designs a personalized curriculum aligned with their background, skills, and career goals.

Program Format & Duration

  • Full-time (2 years)

  • Students typically complete 96 units (approx. 8–10 courses)

  • Flexible curriculum blending core ECE training with AI-focused electives

  • Opportunities for research projects, independent study, or industry collaboration

Core Curriculum Components

The MSAI program ensures mastery of core ECE concepts along with cutting-edge AI techniques.

Core Areas (Required):

  • Fundamentals of Electrical & Computer Engineering

  • Probability & Statistics for Engineers

  • Machine Learning Fundamentals

  • AI Systems & Applications

  • Linear Algebra for AI and Data Science

AI-Focused Electives:
Students choose from a wide range of advanced courses, such as:

  • Deep Learning

  • Natural Language Processing

  • Computer Vision

  • Reinforcement Learning

  • Robotics & Perception

  • Optimization Methods in AI

  • Ethics and Responsible AI

Electives are drawn from ECE, the School of Computer Science, Robotics Institute, and related CMU programs.

Capstone or Research Thesis (Optional)
Students may:

  • Complete a Capstone Project with industry or research partners, focusing on AI applications, or

  • Undertake a Research Thesis under faculty supervision, often leading to publications or PhD pathways.

Experiential Learning (Research, Projects, Internships etc.)

  • Opportunities to collaborate with CMU’s world-renowned AI research centers including the Robotics Institute, CyLab, and Software Engineering Institute

  • Hands-on involvement in cutting-edge research on computer vision, natural language processing, and autonomous systems

  • Participation in interdisciplinary projects integrating AI with biomedical engineering, cybersecurity, and IoT

  • Industry partnerships providing real-world problem statements and mentorship from leading AI practitioners

  • Summer internships with top-tier companies such as Google, Microsoft, Amazon, Meta, and AI-driven startups

  • Access to CMU’s global alumni network for research collaboration and internship placement

  • Engagement in applied AI challenges through CMU-affiliated events like Build18 and TartanHacks

  • Opportunities to publish in leading AI conferences and journals under faculty supervision

  • Course-integrated projects that simulate industry-scale AI system design and deployment

Progression & Future Opportunities

  • Career pathways into specialized AI domains such as robotics, autonomous vehicles, healthcare AI, fintech, and smart manufacturing

  • Progression from entry-level AI engineering roles to principal engineer, lead scientist, or technical fellow positions

  • Opportunities to transition into AI product management, technical program management, or strategic innovation roles

  • Academic progression into postdoctoral research, faculty appointments, or research scientist positions

  • Potential to join think tanks, NGOs, or policy organizations focusing on AI governance and ethics

  • Entrepreneurship support through CMU’s Swartz Center and venture funding for AI-driven startups

  • Global mobility and placement opportunities due to CMU’s industry reputation and employer connections

  • Long-term potential to influence AI strategy at the C-suite level in technology-led enterprises

Program Key Stats

$57,436
$ 100
Sept Intake : 15th Dec


11 %
No
Yes
Yes
No

Eligibility Criteria

3.00 GPA
3 Year

320
163
153
686
7.5
102
2:1

Additional Information & Requirements

Career Options

  • Machine Learning Engineer AI Engineer Data Scientist AI Product Manager Research Scientist (AI/ML/NLP/Robotics) Senior Machine Learning Engineer / AI Specialist AI Architect AI Program Manager / Project Lead Head of AI / AI Director Chief AI Officer (CAIO)

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