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

About This Program

This graduate degree prepares students for employment in industries using data-driven methods for analysis, design, and autonomous systems.

Career Outcomes

Advance as Machine Learning Engineer in Engineering AI with machine learning expertise

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

What You'll Learn

Design and implement machine learning models for real-world engineering problems.
Analyze large-scale datasets using advanced statistical and computational techniques.
Apply deep learning to signal processing, computer vision, and embedded systems.
Optimize AI algorithms for hardware-efficient deployment in ECE applications.

Curriculum Highlights

The program structure focuses on probability for engineers, linear algebra, and technical electives in areas like internet and cloud computing.

Top Employers

Top employers include tech giants like Google, Amazon, NVIDIA, and engineering firms such as Qualcomm and Intel.

Admissions

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

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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