Executive Masters Of Business Administration
The Executive Masters of Business Administration (EMBA) at RIT is desi...
M.S. in Data Science
Rochester
INTAKE: August
Program Overview
The M.S. in Data Science at Rochester Institute of Technology (RIT) is designed to provide students with a comprehensive understanding of data analysis, computational methods, and statistical modeling. The program prepares graduates for careers in data science, focusing on skills that are essential to managing, analyzing, and interpreting large datasets to make data-driven decisions. It is highly interdisciplinary, combining computer science, statistics, and domain-specific knowledge to equip students with the tools necessary to solve real-world problems in various industries, including healthcare, finance, and technology.
STEM-Designated: The M.S. in Data Science is a STEM-designated program, which means it is recognized for its emphasis on science, technology, engineering, and mathematics. This designation offers international students the potential for a longer period of Optional Practical Training (OPT) in the U.S., making it an attractive option for those looking to gain practical experience in the data science field after completing their degree.
Curriculum: The curriculum of RIT’s M.S. in Data Science is structured to provide students with a solid foundation in both theoretical and applied aspects of data science. Core courses cover topics such as data analysis, machine learning, data visualization, programming in Python and R, and statistical inference. Students also have the opportunity to specialize in areas like big data, deep learning, or artificial intelligence through elective courses. The program emphasizes hands-on learning, ensuring that students acquire practical experience working with real-world datasets and tools commonly used in the industry.
Research Focus: The research focus of the M.S. in Data Science program at RIT includes areas such as machine learning, artificial intelligence, data mining, data visualization, and the ethical implications of data use. Faculty and students are engaged in cutting-edge research projects that explore the ways data science can be applied to solve problems in various domains, from healthcare to environmental science. The program encourages students to participate in research projects, providing them with the opportunity to contribute to advancements in the field and gain valuable experience for their future careers.
Industry Engagement: RIT has strong ties to the industry, and the M.S. in Data Science program leverages these connections to provide students with real-world experience. Through internships, cooperative education opportunities, and collaborative projects with industry partners, students gain hands-on experience in data science and develop a deeper understanding of how their academic knowledge can be applied in a professional setting. These engagements also provide students with networking opportunities and a direct pathway to potential employment after graduation.
Global Perspective: The M.S. in Data Science program at RIT prepares students to work in a global, interconnected world where data-driven decision-making is critical. The program attracts students from diverse backgrounds, promoting a global perspective on the challenges and opportunities in data science. Additionally, students can engage in global research collaborations and have access to international internships and study-abroad opportunities, allowing them to broaden their understanding of how data science is applied across different industries and regions. This international outlook enhances their ability to work in global teams and navigate the complexities of data science in diverse cultural and business contexts.
Location
Rochester
Score
IELTS 6.5
Tuition Fee
USD 54176
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 88 or higher.
- PTE: Overall score of 60 or higher.
Standardized Test Requirements:
- GRE Graduate Record Examinations: Overall score of 280 or higher is required.
- GMAT Graduate Management Admission Test: Overall score of 400 or higher is required.
WES Evaluation is required
Rochester Institute of Technology (RIT) is supporting international students through a variety of scholarship opportunities designed to ease the financial burden of studying abroad. These scholarships are available for undergraduate and graduate students and can be awarded based on academic merit, need, and specific program requirements.
Merit-Based Scholarships: RIT offers several merit-based scholarships for international students that are awarded based on academic achievement. These scholarships are intended to recognize the hard work and dedication of students who have demonstrated exceptional academic performance in their previous studies. These scholarships can significantly reduce tuition fees, making education at RIT more affordable for international students. Applicants are automatically considered for merit-based scholarships during the admissions process, and no additional application is required.
International Student Scholarships: In addition to merit-based scholarships, RIT offers specific scholarships tailored to international students. These scholarships are designed to make education accessible to students from around the world and help them pursue their studies at a world-class institution. The scholarships vary in amount and eligibility criteria, and they are awarded based on factors such as academic performance, leadership potential, and extracurricular involvement.
Program-Specific Scholarships: Certain academic programs at RIT offer program-specific scholarships for international students. These scholarships are designed to support students in specific fields of study, such as engineering, business, computer science, and the arts. Each program may have its own criteria for eligibility, and students are encouraged to check with their respective departments for details about available scholarships. Program-specific scholarships often offer additional opportunities for networking, research, and professional development.
Graduate Scholarships and Assistantships: RIT offers graduate scholarships and assistantships to international students pursuing master’s and doctoral degrees. These scholarships are awarded based on academic excellence, research potential, and professional achievements. Graduate students may also be eligible for teaching or research assistantships, which provide a stipend and valuable academic experience. Assistantships allow students to work alongside faculty on research projects and gain teaching experience, which can enhance their academic and professional profiles.
Graduates of the M.S. in Data Science program at Rochester Institute of Technology (RIT) are well-equipped to pursue a wide range of careers in the rapidly growing field of data science. Career opportunities for data science graduates span various industries such as healthcare, finance, technology, business, government, and more.
Data Scientist: Data scientists analyze complex datasets to derive actionable insights, develop predictive models, and apply machine learning techniques to solve real-world problems.
Data Analyst: Data analysts focus on interpreting large datasets, creating reports, and helping organizations make data-driven decisions by providing insights based on statistical analysis.
Machine Learning Engineer: Machine learning engineers design and implement algorithms and models to enable machines to learn from data and improve automatically over time.
Data Engineer: Data engineers build and maintain the infrastructure needed for the collection, storage, and analysis of large datasets, ensuring that data is accessible, reliable, and scalable.
Business Intelligence Analyst: Business intelligence analysts focus on leveraging data to help businesses optimize operations, improve strategies, and make informed decisions through reports and dashboards.
Quantitative Analyst: Quantitative analysts work in finance to develop mathematical models and algorithms to inform investment strategies, risk management, and trading decisions.
AI Specialist: AI specialists use data science techniques to develop artificial intelligence systems, enabling machines to perform tasks that traditionally require human intelligence.
