M.A. in Counseling in Educational Setting
The M.A. in Counseling in Educational Settings at Rowan University is a comprehensive p...
M.S. in Data Science
Glassboro
INTAKE: Jan & Aug
Program Overview
The STEM-designated M.S. in Data Science at Rowan University offers a comprehensive and interdisciplinary program meticulously designed to equip students with the advanced statistical, computational, and domain-specific knowledge essential for extracting meaningful insights and driving data-informed decisions. The curriculum integrates principles from statistics, computer science, and various application domains, providing a strong foundation in data mining, machine learning, data visualization, and big data technologies. Students benefit from hands-on learning experiences, research opportunities with faculty, and access to high-performance computing resources. The program emphasizes the development of critical thinking, problem-solving, and effective communication skills necessary to excel in the rapidly growing field of data science across diverse industries.
STEM Designated: The M.S. in Data Science's STEM designation underscores its strong emphasis on science, technology, engineering, and mathematics, ensuring a curriculum grounded in rigorous statistical methodologies, computational algorithms, and the application of mathematical principles to analyze and interpret complex datasets.
Curriculum: The M.S. in Data Science program requires the completion of 30 semester hours, offering both thesis and non-thesis options. The curriculum includes core courses in areas such as statistical inference, machine learning, data mining, data visualization, and big data technologies. Students can then tailor their studies through elective courses in specialized areas like natural language processing, deep learning, bioinformatics, or business analytics. The program emphasizes hands-on learning through projects using industry-standard tools and programming languages such as Python and R. The thesis option involves in-depth research culminating in a written thesis, while the non-thesis option typically includes additional coursework or a capstone project.
Research Focus: The program fosters a vibrant research environment, encouraging students to engage in cutting-edge research projects under the guidance of experienced faculty members whose research interests span diverse areas of data science. Research opportunities may include topics such as developing novel machine learning algorithms, applying data mining techniques to real-world problems, creating interactive data visualizations, and working with large-scale datasets. The research focus aims to develop students' abilities in problem formulation, data analysis, model building, and the communication of findings.
Industry Engagement: Rowan University's M.S. in Data Science program maintains strong connections with industry through collaborations, guest lectures from data science professionals, career workshops, and potential internship opportunities. The program's emphasis on practical skills and exposure to real-world data science challenges ensures that graduates are well-prepared to meet the demands of the workforce in various data-driven sectors.
Global Perspective: The field of data science is inherently global, with data being generated and analyzed across international borders and collaborations. The M.S. in Data Science program at Rowan University addresses global perspectives through the study of diverse datasets from around the world, the exploration of cross-cultural data analysis considerations, and the discussion of the global impact of data science applications in areas such as healthcare, finance, and social sciences. The diverse backgrounds of faculty and students further contribute to a global learning environment.
Location
Glassboro
Score
IELTS 6.5
Tuition Fee
USD 19150
Postgraduate Entry Requirements
Application Fee: $65
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 65% 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 70 or higher.
- PTE: Overall score of 50 or higher.
- DET (Duolingo English Test): Minimum score of 110.
Rowan University offers a variety of scholarships and financial aid opportunities specifically aimed at supporting international students in their academic pursuits. Understanding that studying abroad can be a significant financial investment, Rowan provides merit-based scholarships, awards, and grants to help ease the financial burden and reward academic excellence and leadership potential.
Merit-Based Scholarships: International students at Rowan University may be eligible for merit scholarships based on their academic achievements, standardized test scores, and other criteria. These scholarships can range from partial to substantial tuition awards and are typically renewable for multiple years, provided students maintain satisfactory academic progress.
Global Academic Excellence Scholarship: One of the key awards available to incoming international undergraduate students is the Global Academic Excellence Scholarship, which recognizes outstanding academic records and exceptional leadership qualities. This scholarship helps reduce tuition costs and encourages high-performing students to join Rowan’s diverse community.
Departmental Scholarships and Awards: Many of Rowan’s individual colleges and departments offer specialized scholarships for international students pursuing degrees in specific fields such as business, engineering, communication, or health sciences. These awards are often competitive and based on academic merit, portfolio submissions, or departmental recommendations.
Graduate Assistantships and Fellowships: For international graduate students, Rowan provides assistantships and fellowships that offer tuition remission along with a stipend in exchange for teaching or research support. These positions not only help finance graduate education but also provide valuable professional experience and academic networking opportunities.
Graduates of the M.S. in Data Science program at Rowan University possess a highly valued and versatile skillset, opening doors to a multitude of exciting and rewarding career opportunities within technology companies, financial institutions, healthcare organizations, marketing firms, government agencies, and various other data-intensive sectors.
Data Scientist: Developing and implementing advanced statistical and machine learning models to analyze complex datasets, generate insights, and solve business problems.
Machine Learning Engineer: Designing, building, and deploying machine learning systems and algorithms for various applications, such as predictive modeling and natural language processing.
Data Analyst: Collecting, cleaning, analyzing, and interpreting large datasets to identify trends, patterns, and insights that can inform business decisions.
Business Intelligence Analyst: Utilizing data analysis tools and techniques to understand business performance, identify areas for improvement, and create insightful reports and dashboards.
Big Data Engineer: Designing, building, and managing large-scale data processing systems and infrastructure, enabling efficient storage and analysis of big data.
Data Engineer: Developing and maintaining data pipelines and ETL (extract, transform, load) processes to ensure data quality and accessibility for analysis.
Quantitative Analyst (Quant): Developing and implementing mathematical and statistical models for financial analysis, risk management, and algorithmic trading.
Marketing Data Analyst: Analyzing marketing data to understand customer behavior, optimize marketing campaigns, and improve customer engagement.
Healthcare Data Analyst: Applying data science techniques to analyze healthcare data, improve patient outcomes, and optimize healthcare operations.
Data Visualization Specialist: Creating compelling and informative visualizations of complex data to communicate insights effectively to both technical and non-technical audiences.
