MBA in Business Analytics
Robert Morris University (RMU) offers a comprehensive MBA program with a concentration ...
M.S. Data Analytics
Moon Township, Pennsylvania
INTAKE: Fall, Spring, Summer
Program Overview
The M.S. in Data Analytics at Robert Morris University is a cutting-edge program designed for students who wish to harness the power of data to make informed business decisions. This program provides a strong foundation in data collection, analysis, and interpretation, preparing students to work with large datasets, extract valuable insights, and apply advanced analytical techniques to solve complex business challenges. Graduates are equipped to enter high-demand roles across various sectors such as finance, healthcare, marketing, and technology.
STEM-designated: The M.S. in Data Analytics at Robert Morris University is a STEM-designated program, highlighting its focus on scientific, technological, engineering, and mathematical principles in data analysis. This designation ensures that students gain the skills needed to handle sophisticated data tools and techniques. For international students, the STEM designation also allows for an extended Optional Practical Training (OPT) period in the U.S., enabling them to gain additional work experience after completing their studies.
Curriculum: The curriculum for the M.S. in Data Analytics is carefully structured to provide students with a comprehensive understanding of key data analytics techniques, tools, and technologies. Core courses include data mining, statistical modeling, machine learning, and big data analytics, along with elective options in areas such as business intelligence, predictive analytics, and data visualization. Students also complete a capstone project where they apply their learning to real-world data challenges, ensuring practical experience that can be directly applied in the workplace.
Research Focus: Robert Morris University’s M.S. in Data Analytics program places a strong emphasis on research that advances the field of data science and analytics. Students and faculty engage in research exploring new methods of data interpretation, machine learning algorithms, and innovative applications of data analytics in various industries. The research focus is designed to equip students with the critical thinking and problem-solving skills needed to tackle contemporary data challenges in business, healthcare, and other sectors.
Industry Engagement: The M.S. in Data Analytics at Robert Morris University incorporates significant industry engagement, allowing students to connect with professionals and gain real-world experience. Through internships, collaborative projects, and partnerships with industry leaders, students have the opportunity to work on actual business problems and apply their knowledge in practical settings. These experiences not only enhance learning but also provide valuable networking opportunities that can help students secure employment upon graduation.
Global Perspective: The M.S. in Data Analytics program at Robert Morris University is designed with a global perspective, incorporating case studies, tools, and strategies used by organizations worldwide. The program prepares students to understand the global implications of data analysis, including the ethical considerations, privacy issues, and regulations that vary by region. By learning how to analyze and interpret data in a global context, students are better equipped to work in international markets and understand the diverse challenges faced by organizations around the world.
Location
Moon Township, Pennsylvania
Score
IELTS 6.5
Tuition Fee
USD 31800
Postgraduate Entry Requirements
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 70% or above in their bachelor's degree.
English Language Proficiency:
- IELTS: Overall band score of 6.5 or 7.0 with a minimum of 6.0 in each component.
- TOEFL: Overall score of 79 or higher.
- PTE: Overall score of 53 or higher.
- DET (Duolingo English Test): Minimum score of 120.
Standardized Test Requirements:
- GMAT (Graduate Management Admission Test): Minimum score of 470 required.
Robert Morris University provides a range of scholarship opportunities for international students to help make higher education more accessible and affordable.
Merit-Based Scholarships: Robert Morris University offers merit-based scholarships to international students based on academic achievement and potential. These scholarships are awarded to students with strong academic records, high standardized test scores, and notable achievements. The merit-based scholarships help reduce the cost of tuition and are typically renewable based on maintaining academic performance.
Institutional Scholarships: RMU provides several institutional scholarships specifically for international students, designed to support their educational expenses. These scholarships may be awarded based on various criteria, including academic excellence, leadership skills, and extracurricular involvement. Students are encouraged to apply for these scholarships as part of their admissions process.
External Scholarships: In addition to university-specific scholarships, international students are encouraged to explore external scholarship opportunities. These may include scholarships offered by private organizations, government programs, and international agencies. The university’s financial aid office can assist students in identifying and applying for relevant external scholarships.
Graduates of the M.S. in Data Analytics program at Robert Morris University are well-equipped for a variety of high-demand roles in the growing field of data science and analytics. The comprehensive skill set developed throughout the program—ranging from statistical analysis to machine learning and big data technologies prepares graduates for leadership roles in industries such as healthcare, finance, technology, and marketing.
Data Analyst: Analyzing and interpreting complex data sets to provide actionable insights that support business decisions.
Data Scientist: Using advanced algorithms and statistical techniques to extract insights and build predictive models from large datasets.
Business Intelligence Analyst: Creating and managing data visualizations and dashboards to support strategic decision-making.
Data Engineer: Developing, constructing, and managing large-scale data processing systems to ensure data is accessible, clean, and ready for analysis.
Quantitative Analyst: Applying statistical and mathematical techniques to analyze financial data and make predictions regarding investment opportunities.
Machine Learning Engineer: Designing and implementing machine learning models to automate decision-making and predictive analytics.
Operations Analyst: Using data to optimize operational processes, improve efficiency, and support business growth strategies.
Marketing Analyst: Leveraging data to analyze consumer behavior and market trends to inform marketing strategies and campaigns.
