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Admission Snapshot
Typical admitted student: A bachelor's degree in computer science, engineering, or a related field with a strong GPA (typically 3.0+), relevant coursework in programming and mathematics, and GRE scores (optional at many programs) are required. Relevant technical experience or projects in AI/ML strengthen applications.
About This Program
This master's program offers advanced study in the foundations of computer science with a specialized track in artificial intelligence.
Career Outcomes
Thrive as Machine Learning Engineer in Cross-Industry AI with natural language processing expertise
- 1. Machine Learning Engineer
- 2. AI Research Scientist
- 3. Data Scientist
- 4. Computer Vision Engineer
What You'll Learn
- Design and implement machine learning models for real-world applications
- Apply deep learning techniques to process and analyze large datasets
- Develop AI systems for tasks like natural language understanding and computer vision
- Evaluate and optimize AI algorithms for performance and scalability
Curriculum Highlights
The structure requires core courses in theory and systems, plus concentration courses in deep learning and ethical algorithm design.
Top Employers
Top employers include Google, Meta, Amazon, Microsoft, and AI research labs at companies like OpenAI and NVIDIA.
Admissions
A bachelor's degree in computer science, engineering, or a related field with a strong GPA (typically 3.0+), relevant coursework in programming and mathematics, and GRE scores (optional at many programs) are required. Relevant technical experience or projects in AI/ML strengthen applications.
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 100+ / IELTS 7.0+)
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