Villanova University United States

Master of Science in Applied Statistics and Data Science - STEM designated

Integrated Masters with deeper specialization and research focus
Taught in English
Duration 2 Years
Mode On Campus
Level Postgraduate
Degree Masters Degree
Closing soon January 2027

Course Overview

The Master of Science in Applied Statistics and Data Science at Villanova University is designed for ambitious individuals seeking to master the quantitative and computational skills essential for today's data-driven world. As industries increasingly rely on robust statistical analysis and predictive modeling, this STEM-designated program equips you with the expertise to tackle complex challenges in areas like regression methods, data mining, and statistical programming. You will develop a deep understanding of statistical theory and its practical application, preparing you for impactful roles in a field experiencing significant growth and innovation.

This full-time, on-campus Master of Science degree is structured over two years, providing a comprehensive curriculum that includes core statistical methods, programming, and theory, alongside specialized tracks in Applied Statistics, Biostatistics, or Data Science. You will engage with advanced topics such as linear models, multivariate methods, and machine learning, often through hands-on projects and case studies. By completing this program, you will graduate with a strong portfolio and the analytical acumen to pursue advanced careers in data science, statistical consulting, or research across various sectors.

Course Curriculum & Details

Detailed information for serious evaluators

Program Overview

The Master of Science in Applied Statistics and Data Science program provides a robust foundation in statistical methods and data analysis. Core coursework covers statistical programming, theory, and regression techniques, with advanced topics available through various tracks and electives. Students can specialize in areas such as data mining, predictive analytics, and machine learning, or explore diverse fields like Bayesian statistics, time series analysis, and experimental design. The program also allows for interdisciplinary study with approved electives from related departments.

1 Required Courses (All Tracks)

Statistical methods
Statistical programming
Statistical theory I
Regression methods

2 Additional Required Courses (by Track)

Statistical theory II
Linear models

3 Data Science Track

Data mining & predictive analytics
Statistical theory II
Linear models

4 Elective Courses

Statistical theory II
Multivariate methods
Bayesian statistics
Linear models
Categorical data analysis
Design of experiments
Time series and forecasting
Survival data analysis
Clinical trials
Longitudinal data analysis
Nonparametric statistics
Sampling methods
Stochastic modeling
Statistical genetics
Data mining & predictive analytics
Deep learning
Selected topics I
Selected topics II
Independent study

5 Approved Electives from Other Programs (with permission)

Operations research
Database systems
Machine learning

Cost & Affordability

A clear picture of what this course will cost you

Program Costs

First Year Fee Tuition fee
USD 28,710.00
Second Year Fee Tuition fee
USD 28,710.00
Total Program Cost Estimated total tuition
USD 57,420.00

Currency note: Program costs shown in USD based on the available tuition breakdown.

Living Costs

Food & Groceries USD 3,600.00 - USD 5,400.00
Transport USD 840.00 - USD 1,440.00
Utilities & Bills USD 1,200.00 - USD 2,040.00
Estimated Total USD 5,640.00 - USD 8,880.00

Living cost estimates are based on Montgomery Campus.

Outcomes & Employability

What happens after you graduate

94%
Graduate Employment Rate Within 6 to 12 months of graduation

Common Graduate Roles

Airport Infrastructure & Aviation SecurityBanking & Financial ServicesBrokerage & Trading & SecuritiesFinancial Technology (Fintech)Industry 4.0 & Digital ManufacturingProduct Management & UXRegulatory & Government AffairsRoad Transport & LogisticsSoftware Development & EngineeringSupply Chain & Procurement

Top Employers Hiring for this course

Amazon Web Services

Boeing

Booz Allen Hamilton

IBM

Lockheed Martin

Merck

Microsoft

Vanguard

Why Study Master of Science in Applied Statistics and Data Science - STEM designated at Villanova University

What makes this program stand out

January 2027 Closing soon

Next intake is in January 2027

Very Fast Application response time

Villanova University typically responds to applications within 1 - 2 days, giving you clarity on your options quickly.

Life at Villanova University in United States

What daily life looks like for international students

Language

English

Primary language everywhere

Climate

Mild & Rainy

10-20°C average, pack layers

Safety (Numbeo Safety Index)

Very Safe

Exeter is one of UK's safest cities

Frequently Asked Questions

Common questions about Master of Science in Applied Statistics and Data Science - STEM designated at Villanova University

Can I work while studying?

International students can work up to 20 hours per week during terms and full-time during breaks without needing a separate work permit. Approval is required for off-campus work after the first year.

What English language score do I need for this course?

To apply, you need to meet specific English language requirements. Acceptable tests include Duolingo, TOEFL, and IELTS, with minimum scores outlined for each.

What jobs can I get after studying this course?

Graduates can pursue careers as Data Analysts, Statistical Consultants, Data Scientists, Business Analysts, and Actuaries.

What will I actually study in this course?

The program equips students with essential skills for data-driven careers and highlights the significance of data-driven decision making in various sectors. Key subjects include applied statistics and data science methodologies.

When can I start — what are the intake months?

You can start the Master of Science in Applied Statistics and Data Science program in January, May, or August. Make sure to check application deadlines for each intake.
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