Stanford 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: A bachelor's degree in computer science or related field with a strong GPA (typically 3.0+), programming experience, and relevant coursework in algorithms, data structures, and mathematics are required. GRE is optional for most applicants.

About This Program

This online master's degree provides the same rigorous academic training as the on-campus program, focused on developing cutting-edge AI technologies.

Career Outcomes

Advance as Machine Learning Engineer in Cross-Industry AI with machine learning expertise

• 1. AI Research Scientist
• 2. Machine Learning Engineer
• 3. Computer Vision Specialist
• 4. NLP Engineer

What You'll Learn

• Design and implement machine learning models for real-world applications.
• Apply deep learning techniques to image recognition and generative tasks.
• Develop natural language processing systems for text analysis and generation.
• Analyze ethical implications and biases in AI systems.

Curriculum Highlights

The coursework includes depth requirements in artificial intelligence, supplemented by breadth courses in systems and theoretical computer science.

Top Employers

Top employers include Google, Meta, OpenAI, and NVIDIA.

Admissions

A bachelor's degree in computer science or related field with a strong GPA (typically 3.0+), programming experience, and relevant coursework in algorithms, data structures, and mathematics are required. GRE is optional for most applicants.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 2–3
• Resume: Required
• Transcripts: Official transcripts required

Academic Requirements

• Degree Required: Bachelor's degree
• GRE/GMAT: Optional
• TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)