Duke University
MS in ECE - Data Analytics & Machine Learning
How this program compares
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Admission Snapshot
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 coursework in linear algebra, probability, and programming.
About This Program
This Master of Science program offers rigorous technical depth in computer engineering, focusing on the mathematical foundations of machine learning and the design of AI-driven systems.
Career Outcomes
Advance as Machine Learning Engineer in Cross-Industry AI with machine learning expertise
- 1. Machine Learning Engineer
- 2. Data Scientist
- 3. AI Systems Engineer
- 4. Computer Vision Specialist
What You'll Learn
- Implement and optimize machine learning models for data analytics in engineering systems.
- Apply deep learning techniques to signal processing and image analysis.
- Analyze large datasets using advanced statistical methods and algorithms.
- Design AI-driven solutions for real-world ECE applications like networking and embedded systems.
Curriculum Highlights
The track-based structure allows for deep specialization in machine learning and AI, complemented by research seminars and the option to complete a faculty-supervised thesis.
Top Employers
Top employers include tech giants like Google, Microsoft, NVIDIA, and engineering firms such as Intel and Qualcomm.
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 coursework in linear algebra, probability, and programming.
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 90+ / IELTS 7.0+)
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