Typical admitted student: A bachelor's degree in a quantitative field such as computer science, mathematics, statistics, or engineering is required, along with a minimum GPA of 3.0 and prerequisite coursework in calculus, linear algebra, programming, and statistics.

About This Program

A professional master’s degree that combines mathematical and engineering foundations with business intelligence to produce data-driven industry leaders.

Career Outcomes

Lead as Data Scientist in Cross-Industry AI with deep learning expertise

1. Machine Learning Engineer
2. Data Scientist
3. AI Research Scientist
4. Data Analytics Manager

What You'll Learn

Develop and deploy machine learning models for predictive analytics.
Process and manage large-scale datasets using big data tools.
Apply statistical methods and probability for data inference.
Create visualizations to communicate data insights effectively.
Build AI solutions integrating data engineering and modeling.

Curriculum Highlights

The curriculum integrates statistics, deep learning, optimization, and communication through a mix of technical coursework and professional internships.

Top Employers

Top employers include Google, Amazon, Microsoft, IBM, and consulting firms like McKinsey and Deloitte.

Admissions

A bachelor's degree in a quantitative field such as computer science, mathematics, statistics, or engineering is required, along with a minimum GPA of 3.0 and prerequisite coursework in calculus, linear algebra, programming, and statistics.

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: Not Required
TOEFL/IELTS: Required for international students (TOEFL 80+ / IELTS 6.5+)

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