Typical admitted student: A bachelor's degree in electrical engineering, computer engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with programming experience and coursework in linear algebra, probability, and data structures.

About This Program

This interdisciplinary master's degree provides formalized training in mathematical modeling and computational methods for navigating and understanding big data.

Career Outcomes

Position as Data Scientist in Engineering AI with deep learning expertise

1. Machine Learning Engineer
2. Data Scientist
3. AI Systems Engineer
4. Research Scientist in AI

What You'll Learn

Implement supervised and unsupervised machine learning models for data analysis.
Design probabilistic models for AI decision-making and reasoning.
Develop recommender systems and natural language processing pipelines.
Optimize data systems for scalable machine learning applications.

Curriculum Highlights

The plan requires 48 units, including core courses in data analysis and probability, with electives in deep learning and a comprehensive exam option.

Top Employers

Top employers include tech companies like Google, Microsoft, Amazon, and NVIDIA, as well as research labs and AI-focused firms.

Admissions

A bachelor's degree in electrical engineering, computer engineering, computer science, or a related field with a minimum GPA of 3.0 is required, along with programming experience and coursework in linear algebra, probability, and data structures.

Application Materials

Statement of Purpose: Required
Letters of Recommendation: 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+)

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