Typical admitted student: A bachelor's degree in mathematics, computer science, engineering, or a related quantitative field with a minimum GPA of 3.0 is required, along with calculus, linear algebra, and programming prerequisites. Relevant work or research experience in AI/ML is preferred.

About This Program

This graduate program provides a rigorous mathematical foundation combined with advanced training in machine learning and computational techniques.

Career Outcomes

Lead as Data Scientist in Cross-Industry AI with mathematical modeling expertise

1. Machine Learning Engineer
2. Data Scientist
3. AI Research Scientist
4. Computational Mathematician

What You'll Learn

Develop and optimize machine learning models using computational mathematics.
Apply numerical methods and linear algebra to AI algorithms.
Analyze probabilistic models for predictive analytics and inference.
Implement scalable AI solutions for real-world data problems.

Curriculum Highlights

The curriculum features coursework in applied statistics, numerical analysis, data mining, and a specialized track in machine learning applications.

Top Employers

Top employers include tech giants like Google, Amazon, Microsoft, and research institutions such as national labs and AI firms.

Admissions

A bachelor's degree in mathematics, computer science, engineering, or a related quantitative field with a minimum GPA of 3.0 is required, along with calculus, linear algebra, and programming prerequisites. Relevant work or research experience in AI/ML is preferred.

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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