M.S. in Accounting
The University of Massachusetts Dartmouth is home to a distinguished M.S. in Accou...
M.S. in Data Science
Dartmouth, Massachusetts
INTAKE: Jan & Sept
Program Overview
The University of Massachusetts Dartmouth offers an esteemed M.S. (Master of Science) program in Data Science, catering to students who aspire to excel in the dynamic and rapidly growing field of data analytics. This program stands out with its STEM (Science, Technology, Engineering, and Mathematics) designation, signifying a curriculum that not only imparts technical knowledge but also fosters critical thinking, problem-solving, and quantitative skills essential for success in the data-driven industry landscape.The M.S. in Data Science program at the University of Massachusetts Dartmouth offers a comprehensive education that goes beyond technical skills to cultivate critical thinking and problem-solving abilities. With its STEM designation, interdisciplinary curriculum, and focus on practical experience, this program positions graduates to excel in the fast-paced world of data analytics. As organizations increasingly rely on data to make informed decisions, data scientists with the expertise and proficiency developed in this program are in high demand across various industries, including finance, healthcare, e-commerce, and more. Graduates emerge prepared to tackle complex data challenges, uncover insights, and drive innovation in an era defined by data. This program not only equips students with the knowledge and skills they need for successful careers but also empowers them to shape the future of data science and analytics.
Curriculum:
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Interdisciplinary Curriculum: The M.S. in Data Science program features an interdisciplinary curriculum that integrates mathematics, statistics, computer science, and domain-specific knowledge. Students gain a holistic understanding of data analytics principles.
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STEM Designation: This program proudly carries the STEM designation, which attests to its emphasis on scientific rigor and quantitative proficiency. STEM programs are highly regarded for their focus on equipping students with the skills sought after by today's job market.
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Cutting-Edge Technology: Students have access to cutting-edge tools and technologies used in the field of data science, including data visualization tools, machine learning libraries, and big data platforms.
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Practical Experience: Practical training is a key component of the program. Students engage in hands-on projects, case studies, and real-world data analysis, preparing them for the challenges they will face in their careers.
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Data Ethics and Privacy: Ethical considerations surrounding data collection, usage, and privacy are woven into the curriculum. Graduates are equipped to handle data responsibly and ethically.
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Research Opportunities: The program offers opportunities for research collaboration with faculty members and industry partners. This research can lead to contributions to the field and valuable experience.
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Customization: Students can tailor their studies by selecting elective courses that align with their interests and career goals. Specializations may include machine learning, business analytics, or healthcare analytics.
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Capstone Project: The program often culminates in a capstone project, where students apply their knowledge to solve real-world data science challenges, providing them with practical experience and a portfolio piece.
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Career Development: UMass Dartmouth has strong industry connections, facilitating networking, internships, and job placements for students. Career development services assist students in securing roles in the field.
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Collaboration: Students have the opportunity to collaborate with peers, faculty, and industry professionals on projects, hackathons, and research initiatives, fostering a supportive and collaborative learning environment.
Location
Dartmouth, Massachusetts
Score
IELTS: 6.5
Tuition Fee
USD 26084
Entry Requirements for Postgraduate Programs
Application Fees : US$ 60
1. Academic Requirements:
- Applicants should have completed a bachelor's degree or its equivalent from a recognized institution. The minimum academic requirement is a bachelor's degree with a GPA equivalent to 60% or above.
2. English Language Proficiency:
- IELTS (International English Language Testing System):
- Overall Score: 6.5 or higher.
- No individual band score should be less than 6.0.
- TOEFL iBT (Test of English as a Foreign Language, Internet-Based Test):
- Overall Score: 80 or higher.
- DET (Duolingo English Test):
- Score: 110 or higher.
- PTE (Pearson Test of English):
- Score: 53 or higher.
Scholarships for International Students at the University of Massachusetts Dartmouth
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Merit-Based Scholarships: UMass Dartmouth offers various merit-based scholarships for international students based on academic achievement and qualifications. These scholarships may cover a portion of tuition costs and are awarded to students with exceptional academic records.
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International Student Scholarships: The university provides specific scholarships exclusively for international students. These scholarships are designed to attract and support outstanding international talent. The eligibility criteria and award amounts may vary, and students should check with the admissions office for details.
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Graduate Assistantships: Graduate students pursuing master's or doctoral degrees may have opportunities to work as graduate teaching or research assistants. These assistantships often include a stipend and a tuition waiver, which significantly reduce the cost of education.
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Global UGRAD Program: UMass Dartmouth participates in exchange programs such as the Global Undergraduate Exchange Program (Global UGRAD). This program provides scholarships to international undergraduate students, allowing them to study in the United States for a semester or academic year.
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External Scholarships and Sponsorships: International students can explore external scholarship opportunities provided by governments, foundations, and organizations in their home countries. Some countries offer scholarships to support their citizens studying abroad.
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Fulbright Program: UMass Dartmouth is a participant in the Fulbright Program, which offers scholarships for international students to pursue graduate studies, conduct research, or teach in the United States. Eligible students can apply for Fulbright scholarships through the U.S. Department of State.
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Financial Aid Guidance: The university's financial aid office assists international students in navigating the scholarship and financial aid application process. They provide guidance on finding scholarships, completing applications, and meeting deadlines.
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Need-Based Aid: While need-based financial aid options may be limited for international students, UMass Dartmouth encourages students to complete the Free Application for Federal Student Aid (FAFSA) if eligible. FAFSA results may be considered for certain financial aid opportunities.
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Assistantships and Research Grants: Graduate students in science, engineering, and technology fields may have access to research assistantships and grants funded by faculty research projects.
The University of Massachusetts Dartmouth offers a highly reputable M.S. (Master of Science) program in Data Science, equipping students with the knowledge and skills to thrive in the rapidly evolving field of data analytics. This program opens doors to diverse and promising career opportunities where data scientists play a pivotal role in extracting meaningful insights from vast data sets, aiding decision-making processes across various sectors.
1. Data Scientist: Graduates can step into the role of a data scientist, employing advanced analytical techniques to extract actionable insights from complex data sets. They design models, implement algorithms, and interpret data for various purposes.
2. Data Analyst: Data analysts work on transforming data into understandable formats and reports, aiding companies in making informed decisions. They focus on data cleansing, visualization, and interpretation.
3. Machine Learning Engineer: Graduates can work as machine learning engineers, developing and optimizing machine learning models and algorithms for predictive analysis and pattern recognition.
4. Business Intelligence Analyst: Business intelligence analysts use data to drive business strategies and make informed decisions. They create dashboards and reports to assist organizations in understanding trends and performance.
5. Quantitative Analyst: Quantitative analysts, often in finance and investment firms, use data to create models for pricing assets, risk management, and portfolio optimization.
6. Big Data Engineer: Graduates can work as big data engineers, managing, processing, and analyzing large volumes of data using specialized tools and technologies.
7. Database Administrator: Database administrators design and manage databases, ensuring data availability, security, and accessibility.
8. Predictive Modeler: Predictive modelers use statistical techniques to forecast trends, enabling organizations to plan and strategize effectively.
9. Statistician: Data science graduates can pursue a career as statisticians, specializing in designing experiments and analyzing data to solve real-world problems.
10. Data Engineer: Data engineers build and manage the systems and architecture that allow large volumes of data to be processed efficiently.
11. Research Scientist: Graduates can contribute to the advancement of data science through research, working in academia or research institutions.
12. Fraud Analyst: In finance and e-commerce, data science graduates can work as fraud analysts, identifying and preventing fraudulent activities using data analysis.
13. Health Data Analyst: In the healthcare sector, graduates can work as health data analysts, analyzing health data to improve patient care, reduce costs, and enhance healthcare systems.
14. Consulting Analyst: Data science professionals can work in consulting, helping various clients across industries to optimize their data management and analysis processes.
15. AI Ethicist: As AI becomes more prevalent, graduates can work as AI ethicists, ensuring that AI technologies are developed and used responsibly and ethically.
