Carnegie Mellon University

How this program compares

Benchmark this program against our national recognition pages and use the key guides below to evaluate ROI, admissions difficulty, and outcomes.

Admission Snapshot

Typical admitted student: Applicants must hold a bachelor's degree with a minimum GPA of 3.0, preferably in computer science or statistics, demonstrating undergraduate-level mastery in these areas.[1

About This Program

This professional master's program focuses on developing large-scale AI solutions and preparing students for entrepreneurial and leadership careers.

Career Outcomes

Thrive as AI Engineer in Cross-Industry AI with machine learning expertise

• 1. AI Engineer
• 2. Machine Learning Engineer
• 3. AI Product Manager
• 4. AI Innovation Consultant[1]

What You'll Learn

• Identify potential AI applications for large-scale practical problems.
• Develop and deploy innovative AI systems using machine learning and language technologies.
• Engineer practical AI solutions for real-world deployment.
• Prepare for entrepreneurial ventures in AI innovation.[1]

Curriculum Highlights

The four-semester structure includes core innovation sequences, machine learning requirements, electives in big data, and a substantive capstone project.

Top Employers

Top employers include tech leaders like Google, Amazon, Microsoft, and innovative AI firms such as OpenAI and DeepMind.[1

Admissions

Applicants must hold a bachelor's degree with a minimum GPA of 3.0, preferably in computer science or statistics, demonstrating undergraduate-level mastery in these areas.[1

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 3
• Resume: Required
• Transcripts: Official transcripts required[1]

Academic Requirements

• Degree Required: Bachelor's degree
• GRE/GMAT: Optional
• TOEFL/IELTS: Required for international students (TOEFL 102+ with no subscore below 25 / IELTS 7.5+ with no band below 7.5)[1]