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Admission Snapshot
Typical admitted student: Applicants must hold a bachelor's degree with a strong background in computer science, including programming skills, and mathematics such as probability, statistics, matrix algebra, and multivariate calculus. GRE scores are optional, with TOEFL/IELTS required for international students.
About This Program
This 16-month program offers advanced study in the principles and practice of machine learning for data analysis and improvement.
Career Outcomes
Advance as Machine Learning Engineer in Cross-Industry AI with machine learning expertise
- 1. Machine Learning Engineer
- 2. AI Research Scientist
- 3. Data Scientist
- 4. Applied ML Specialist
What You'll Learn
- Develop and analyze machine learning algorithms for predictive modeling
- Apply deep learning techniques to image and language data
- Design probabilistic models for uncertainty quantification
- Implement reinforcement learning systems for decision-making
- Evaluate and optimize ML models for real-world deployment
Curriculum Highlights
The curriculum requires core courses in machine learning and statistics, specialized electives, and a summer research or industry practicum.
Top Employers
Top employers include Google, Meta, Amazon, Microsoft, and research institutions like OpenAI.
Admissions
Applicants must hold a bachelor's degree with a strong background in computer science, including programming skills, and mathematics such as probability, statistics, matrix algebra, and multivariate calculus. GRE scores are optional, with TOEFL/IELTS required for international students.
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+)
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