Master's in Data Science in United States

Business Analytics and Data Science, M.S.

Data Analysis Workshop II

This workshop is designed for students who have a solid foundation in biostatistical concepts relevant to public health sciences and wish to enhance their data analysis skills. The course focuses on understanding and applying various analytical techniques to public health datasets. Through a computer lab setting, students will utilize Stata statistical software to master advanced data analysis methods. Key topics include analysis of variance, analysis of covariance, non-parametric methods for group comparisons, multiple linear regression, logistic regression, log-linear regression, and survival analysis.

Data Science MS

The Master of Science in Data Science program at NYU's Center for Data Science (CDS) is a highly selective program designed for individuals with a strong background in mathematics, computer science, and applied statistics. This intensive 36-credit program is structured for completion within two years of full-time study. It aims to equip students with advanced knowledge and skills to tackle complex data challenges across various fields. The curriculum emphasizes an interdisciplinary approach, fostering collaboration and innovation in the rapidly evolving domain of data science. Graduates are prepared for leadership roles in a field that is central to technological advancement and innovation.

Data Science, MS

The Master of Science (MS) in Data Science is a collaborative program offered by the Departments of Statistics and Computer Sciences, administered by the Statistics Department. This program equips students with essential computational and statistical thinking skills. These abilities, when combined with domain-specific knowledge, enable graduates to tackle complex data-rich problems across various industries and fields. Graduates will develop the critical thinking, data management, processing, modeling, and analytical skills necessary to derive meaning and knowledge from data, while also learning to use data in responsible and ethical ways. The curriculum focuses on the rapidly evolving areas of applied statistical and computing research and practice. Graduates are prepared for roles as data analysts and data scientists, or to pursue further advanced studies in data science, statistics, computer science, or related quantitative fields.

Datamining the City I

Datamining the City I is a course offered within the Master of Architecture and M.S. Advanced Architectural Design programs. This course focuses on exploring urban environments through data analysis. It is typically offered in the Spring semester and runs for the full semester, granting 3 points. The course utilizes a combination of lectures and potentially studio work to investigate how data can be extracted, analyzed, and visualized to understand complex urban systems. Students will likely engage with methods of datamining to gain new perspectives on the built environment.

Master of Applied Statistics and Data Science (MASDS)

The Master of Applied Statistics and Data Science (MASDS) program at UCLA is designed for students seeking to develop strong quantitative and analytical skills. While a bachelor's degree is required, your undergraduate major does not need to be in statistics. The program values applicants with a solid foundation in quantitative subjects such as linear algebra, multivariate calculus, probability, statistics, and programming. While proficiency in R and Python is beneficial, it will be developed during the coursework. The MASDS program also places significant value on practical work experience, particularly in applying quantitative methods in research, business, or professional settings.

Master of Data Science (MDS)

Rice University offers a professional, non-thesis Master of Data Science (MDS) degree designed to equip interdisciplinary professionals with the skills to tackle real-world problems using data. The program emphasizes a blend of computational and statistical foundations, core data science methods, and specialized knowledge. Graduates will be prepared to collect, evaluate, interpret, and communicate data effectively for decision-making across various industries. The MDS program is taught by world-class faculty and provides both on-campus and online learning options, ensuring students receive the same high-quality education regardless of their chosen format. The curriculum is structured to provide a comprehensive understanding of data science, including core courses, specialization options, electives, and a capstone project. Students can choose to specialize in areas like business analytics, machine learning, or image processing (the latter currently only for on-campus students). Elective choices allow for further customization, with options in ethics, cybersecurity, and security/privacy. The program's learning outcomes focus on developing proficiency in the computational and statistical underpinnings of data science, applying core methods, solving complex problems with data, and communicating findings to diverse audiences. This interdisciplinary program is ideal for professionals seeking to enhance their data science expertise and apply it to their fields. The flexibility of online and on-campus delivery caters to different learning preferences and professional commitments. Graduates are prepared for in-demand roles in sectors ranging from science and healthcare to energy and manufacturing, where data-driven insights are increasingly critical.

Master of Science in Accounting with Data Analytics

UMass Boston's Master of Science in Accounting with Data Analytics (MSA) program is designed to advance your accounting career in today's data-driven world. You will gain advanced accounting knowledge and develop essential analytical skills to navigate complex financial landscapes influenced by AI and Big Data. Taught by experienced faculty, the program emphasizes practical application through internships and real-world case studies. This STEM-designated program prepares you for diverse roles in public, corporate, and government accounting, equipping you with the expertise to analyze accounting and financial data effectively. The MSA program is accessible through online, in-person, and hybrid formats, and international students benefit from potential eligibility for up to three years of Optional Practical Training (OPT), providing extended opportunities for job searching and career development.

Master of Science in Applied Data Science

The Master of Science in Applied Data Science program at the University of Southern California (USC) Viterbi School of Engineering is designed to equip students from diverse academic backgrounds with the essential skills for a career in data science. This program is available both on-campus and online, allowing flexibility for students. It caters to those with undergraduate degrees in computer science, other engineering or scientific fields, and even social sciences, provided they demonstrate a strong aptitude for math and science. Graduates will be proficient in data science techniques, programming (specifically Python), database management, big data infrastructure, machine learning, data mining, and applying these skills to solve real-world challenges.

Master of Science in Applied Sports Science Analytics

The Master of Science in Applied Sports Science Analytics program equips students with the skills to enhance athlete health, performance, and well-being through data-driven interventions. This interdisciplinary program combines expertise in exercise science, statistics, and data science, enabling graduates to analyze complex datasets and develop innovative applications for sports and human performance. The curriculum focuses on practical application, preparing students to work effectively with athletes, coaches, sports medicine professionals, and athletic organizations.

Master of Science in Biomedical Data Science and AI

The Master of Science in Biomedical Data Science and AI (MDSAI) program at Icahn School of Medicine at Mount Sinai addresses the growing need for skilled professionals who can analyze the vast amounts of biomedical data generated in healthcare. This program equips students with strong quantitative backgrounds to become leaders in precision medicine. You will learn to transform complex data into actionable insights, enabling advancements in customized treatments, biomedical image analysis, and the overall quality of healthcare delivery. The curriculum utilizes cutting-edge technology and access to large, electronic medical record-linked biomedical datasets.

Master of Science in Biomedical Data Science and AI Online (MDSAIO)

The Master of Science in Biomedical Data Science and AI Online (MDSAIO) program at the Icahn School of Medicine at Mount Sinai equips students with the skills to become leaders in biomedical data science. This 30-credit program leverages cutting-edge technology and extensive biomedical data resources to drive improvements in human health. Taught by Icahn School faculty, the curriculum emphasizes quantitative and computational skills, preparing students to tackle complex health challenges through the application of data science and artificial intelligence. The fully online program mirrors the rigor and academic standards of the on-campus offerings, allowing graduates to earn the same Master of Science degree. Students engage in live, instructor-paced sessions conducted in the Eastern Time Zone, fostering direct interaction with faculty and peers. The program is designed to enhance computational, mathematical, and statistical thinking, enabling students to analyze large datasets and derive insights from biomedical problems.

Master of Science in Business Analytics

The Master of Science in Business Analytics (MSBA) program at UC Davis addresses the growing demand for professionals skilled in leveraging large datasets and computational power to drive business insights and decisions. Graduates are prepared to fill the significant gap between the need for data-savvy professionals and the available talent pool. The program is designed as an investment in your future, with UC Davis providing financial assistance options to help manage program costs.

Master of Science in Business Analytics

The University of Washington Foster School of Business offers a Master of Science in Business Analytics (MSBA) program. This program is designed to equip students with the analytical and technical skills needed to leverage data for business decision-making. It focuses on applying cutting-edge research and technology within the industry, without requiring a thesis or research component. The curriculum is taught by nationally recognized faculty who are experts in their fields, ensuring a high-quality educational experience. The program aims to prepare graduates for impactful roles in the data-driven business landscape.

Master of Science in Business Analytics (MSBA)

The Master of Science in Business Analytics (MSBA) program at the University of Washington's Foster School of Business is a full-time, one-year program designed to equip students with the skills to succeed in the field of business analytics. Classes are held in the evenings and on weekends, making it accessible for those balancing other commitments. The program starts once a year in June and is delivered entirely in person on the Seattle campus. This program is ideal for individuals who have a strong quantitative aptitude, a bachelor's degree, and a desire to leverage data for business decision-making. The curriculum focuses on developing both analytical and communication skills, preparing graduates for a variety of roles in the data-driven business world. The program emphasizes a practical, hands-on approach to learning.

Master of Science in Business Analytics (MSBA)

The Master of Science in Business Analytics (MSBA) program at Carnegie Mellon University's Tepper School of Business is designed to equip students with the skills to drive data-informed decision-making in today's complex business landscape. This full-time, one-year program focuses on leveraging data to uncover insights, solve business challenges, and create future value. The curriculum emphasizes a blend of analytical techniques, technological tools, and business acumen, preparing graduates for impactful roles in various industries. The program considers all aspects of an applicant's background, including goals, professional experience, and academic achievements, in its holistic review process.

Master of Science in Business Analytics (MSBA)

The Master of Science in Business Analytics (MSBA) program at California Baptist University is designed to equip students with the skills to become data-driven business leaders. This STEM-designated degree merges advanced analytical techniques with essential business strategy, preparing graduates to transform complex data into actionable insights across various fields including marketing, finance, economics, logistics, and operations. The program emphasizes ethical reasoning and responsible leadership, grounded in a Christian worldview, ensuring graduates lead with integrity.

Master of Science in Business Analytics (MSBA)

The UCLA Anderson Master of Science in Business Analytics (MSBA) is a 15-month, on-campus program designed for individuals driven to apply data modeling, mathematics, and coding skills to solve complex business problems. This STEM-certified program equips you with the tools to extract insights from data, tell compelling data stories, and drive strategic business decisions. Graduates become invaluable assets to organizations seeking to leverage data for actionable strategies. The curriculum is taught by faculty who are leading researchers and practitioners in their fields, ensuring students are prepared for the evolving demands of the analytics industry. The program emphasizes ethical outcomes, reflecting the UCLA Anderson standard.

Master of Science in Business: Analytics

The Master of Science in Business: Analytics (MSBA) program at the University of Wisconsin–Madison equips students with the skills to leverage data for critical business decision-making. This accelerated, STEM-designated degree focuses on turning data into actionable insights, preparing graduates for the demands of today's fast-paced world. The program fosters a collaborative learning environment within the highly ranked School of Business, known for its entrepreneurial spirit and world-renowned faculty.

Master of Science in Data Analytics

Master of Science in Data Analytics for Science

The Master of Science in Data Analytics for Science (MS-DAS) program at Carnegie Mellon University is designed for students with a background in scientific fields such as biology, physics, math, or chemistry who want to develop expertise in data analytics. This one-year program builds upon your existing scientific knowledge, equipping you with advanced skills in machine learning, computational modeling, and data visualization. The program is a collaboration between Carnegie Mellon's Mellon College of Science, Department of Statistics, and the Pittsburgh Supercomputing Center (PSC), offering a unique blend of academic rigor and access to cutting-edge high-performance computing resources. Unlike programs geared towards computer science graduates, MS-DAS focuses on applying data analytics techniques to solve complex problems within scientific domains. You will learn modern programming languages like Python, SQL, and R, and gain hands-on experience through a semester-long capstone project. This project allows you to work with industry partners on real-world data analysis challenges, fostering professional development and networking opportunities. Graduates are prepared for impactful careers in research and development across various sectors.

Master of Science in Data Science

The Master of Science (MS) in Data Science program at the Halıcıoğlu Data Science Institute (HDSI) aims to equip students with the knowledge and skills necessary for data-driven tasks and to foster future researchers who can advance the field of Data Science. The program consists of formal courses and a choice between a thesis or comprehensive examinations for degree completion. Students will complete a total of twelve 4-unit courses, divided into Foundational (Group A), Core (Group B), and Elective (Group C) requirements. These ensure exposure to fundamental concepts, advanced topics, and current research or applications in Data Science. Foundational courses cover programming, data organization, linear algebra, probability, statistics, and optimization. Core courses build upon these fundamentals, with specific required courses and a selection of others. Electives allow for specialization within data science or in related fields, subject to advisor approval. Upon completion of coursework, students can pursue either a Thesis (Plan I) or a Comprehensive Examination (Plan II). The Thesis option involves 8-12 units of Thesis Research (DSC 299) under faculty guidance. The Comprehensive Examination option assesses a student's ability to apply data science knowledge across Machine Learning/Computing, Math/Statistics, and Systems/Algorithms, typically evaluated through specific course assignments or exams.

Master of Science in Data Science

Brown University offers a one or two-year Master of Science (Sc.M.) in Data Science program designed to equip students with both theoretical knowledge and practical experience in a rapidly evolving, data-driven world. The program prepares graduates for careers in data science, integrating foundational concepts from computer science, mathematics, and statistics with specialized domain knowledge. Students will gain expertise in essential areas such as machine learning, data mining, visualization, and data management. The curriculum emphasizes addressing key data science challenges, exploring ethical and societal implications, and applying knowledge to real-world problems through experiential learning opportunities.

Master of Science in Data Science

Master of Science in Data Science

The Master of Science (MS) in Data Science program at NYU's Center for Data Science (CDS) is a rigorous 36-credit program designed for students with a strong background in mathematics, computer science, and applied statistics. This program can be completed in two years of full-time study and offers specialized tracks, including an Industry Concentration and a Data Science Track with focuses on Big Data, Mathematics and Data, and Natural Language Processing. There is also a Biomedical Informatics Track. The interdisciplinary approach to data science education, combined with world-class faculty and cutting-edge research opportunities, prepares graduates for dynamic careers. Located in New York City, a global center for technology and innovation, CDS boasts strong industry connections and internship opportunities. This provides students with valuable real-world experience and networking possibilities. The program aims to equip students with the skills needed to tackle complex data challenges and contribute to the evolving field of data science.

Master of Science in Data Science (MSDS)

The Master of Science in Data Science (MSDS) at Texas A&M University is an interdisciplinary program designed to prepare students for rewarding careers in the rapidly growing field of data science. Offered through a collaboration between the Departments of Computer Science and Engineering, Electrical and Computer Engineering, Mathematics, and Statistics, the program is housed within the Colleges of Engineering and Arts & Sciences. It provides a strong foundation in core areas such as mathematics, statistics, computer science, and machine learning, followed by customizable elective options. The MSDS program can be completed in three semesters, requiring 30 credit hours, making it suitable for both professionals seeking to upskill and students aiming for data-intensive research and projects.

Master of Science in Data Science in Biomedicine

The Master of Science (MS) in Data Science in Biomedicine program at UCLA provides advanced training in data science techniques specifically applied to the field of biomedicine. This program equips students with the skills to analyze complex biological and health-related data, fostering innovation in research and clinical practice. It is designed for individuals seeking to leverage data-driven approaches in biomedical discovery, diagnostics, and therapeutics.

Master of Science in Engineering in Data Science (MSE-DS) Online

The Master of Science in Engineering in Data Science (MSE-DS) Online is an advanced degree program offered by the University of Pennsylvania's School of Engineering and Applied Science. This program is designed for professionals seeking to deepen their expertise in data science, machine learning, and related fields. It offers a rigorous curriculum delivered entirely online, allowing students to balance their studies with professional and personal commitments. The program aims to equip graduates with the theoretical knowledge and practical skills necessary to tackle complex data challenges and drive innovation in various industries.

Master of Science in Health Data Science

The Master of Science in Health Data Science is a program designed to equip students with advanced skills in analyzing complex health data. Offered by the Department of Biostatistics, this program provides a strong foundation in statistical theory, computational methods, and the application of data science techniques to public health challenges. It is ideal for individuals seeking to leverage data for improved health outcomes and to advance research in the field.

Master’s in Applied Data Science

The Master’s in Applied Data Science program at New College of Florida is a rigorous, in-person program focused on providing students with the essential concepts and methods in databases, computing, data visualization, statistics, machine learning, and artificial intelligence. The program emphasizes building collaborative and communication skills, preparing graduates for in-demand roles in various industries. With a small, cohort-based structure, students benefit from close interaction with faculty, many of whom have industry experience. The curriculum is designed to blend interdisciplinary theory with practical application, ensuring graduates possess the technical skills and real-world experience sought by employers.

Master's in Data Science

Brown University's Master's in Data Science program is an intensive, full-time, on-campus program designed to equip students with the theoretical knowledge and practical skills to excel in the rapidly growing field of data science. The program focuses on developing a strong foundation in statistical modeling, machine learning, data mining, and computational methods, preparing graduates for impactful careers in various industries. Students will learn to analyze complex datasets, build predictive models, and communicate data-driven insights effectively. The curriculum is structured to provide a comprehensive understanding of data science principles, with an emphasis on hands-on application. Students will engage with programming languages like Python and R, essential tools for data manipulation, analysis, and visualization. The program encourages a collaborative learning environment, fostering interaction among students and with faculty who are active researchers in the field. This program is recognized as a STEM program, offering international students potential benefits for post-graduation work opportunities (OPT extension). While the program is designed for completion within two years, students can take it over a longer period by enrolling in fewer credits per semester, though this may not be compatible with full-time work due to course schedules.

Master's in Data Science for MIT MicroMasters Credential Holders

This online Master's in Data Science program is designed for individuals who have successfully completed the MITx MicroMasters in Statistics and Data Science. It offers a condensed, nine-course pathway to Northwestern University's rigorous MS in Data Science, allowing you to leverage your existing foundational knowledge. The curriculum focuses on building advanced analytical and leadership skills essential for data-intensive careers. You will learn to transform data into actionable insights, develop statistically sound solutions, and make trustworthy predictions using modern statistical and machine learning methods. The program allows for customization through a general data science track or one of four specializations: Analytics and Modeling, Artificial Intelligence, Data Engineering, or Analytics Management, enabling you to align your studies with your professional goals. You can further tailor your learning with a variety of elective courses.

Master's Program in Social Data Analytics

The Master's Program in Social Data Analytics (Sc.M.) at Brown University is a STEM-designated program focused on training students in advanced methods for collecting, processing, analyzing, and interpreting large-scale data related to human behavior and social systems. This program equips graduates with skills relevant to a variety of careers, including market research, program evaluation, policy analysis, financial analysis, and further academic study in the social sciences. The curriculum emphasizes both quantitative and qualitative research methods, with specific cores in spatial analysis and market research. Students receive instruction from internationally recognized researchers and engage in hands-on data analytic research, either through a faculty-directed project or an off-campus internship. The program is designed for early-career students with a foundation in basic statistics and social science research who seek specialized training to become highly competitive in the job market.

MS & PhD in Data Science

The Halıcıoğlu Data Science Institute (HDSI) at UC San Diego offers Master of Science (MS) and Doctor of Philosophy (PhD) programs designed to train the next generation of data scientists. These programs focus on interdisciplinary approaches to data science, welcoming students from diverse academic and professional backgrounds. The curriculum emphasizes a strong foundation in areas critical to data science, including numerical linear algebra, probability, statistics, and programming languages. Graduates are prepared for leadership roles in academia, industry, and government.

MS in Applied Data Analytics

The Master of Science (MS) in Applied Data Analytics program equips students with a strong foundation in data analytics principles and practical skills. It emphasizes current industry tools and methodologies within a rigorous academic setting. The curriculum covers organizing, cleaning, analyzing, and visualizing large datasets, introducing students to various database systems, data-mining tools, visualization packages (Python, R), and cloud services. Graduates will be prepared to critically analyze real-world problems using data analytics tools and understand the capabilities and limitations of these applications.

MS in Bioinformatics with Information Sciences Concentration

The Master of Science (MS) in Bioinformatics with an Information Sciences (IS) Concentration prepares you for a career in managing the vast amounts of health, medical, and biological data being generated. This interdisciplinary program allows you to take courses across various campus units, equipping you to work as an analyst or researcher in fields like molecular biology, environmental biology, and biomedicine. You will gain expertise in using technology to organize information, build and evaluate information systems, and develop skills in data stewardship, analytics, and policy.

MS in Business Analytics

The Master of Science (MS) in Business Analytics at The University of Texas at Austin's McCombs School of Business offers a specialized, full-time, 10-month program designed to equip students with the skills to excel in the evolving field of data analysis and artificial intelligence. This STEM-designated program focuses on the end-to-end analytics lifecycle, preparing graduates to leverage AI for enterprise decision-making, manage data-driven initiatives, and provide strategic insights in various business contexts. The curriculum emphasizes durable skills applicable across roles and industries, ensuring graduates are adaptable to future career landscapes and can effectively collaborate with both AI systems and diverse stakeholders. Graduates are prepared for roles that bridge the gap between complex data, advanced analytics, and actionable business strategies.

MSE in Data Science Online Dual Degree

The MSE in Data Science Online Dual Degree program at the University of Pennsylvania's Engineering School offers a unique opportunity for high-achieving graduate students to earn two degrees. This program allows current Penn Engineering graduate students, or recent alumni (within 5 years of graduation), to build upon their existing master's degree by pursuing an MSE in Data Science. The dual degree is designed for those with a strong interest in data science, enabling them to gain specialized knowledge and skills in this rapidly growing field.

Part-Time Master of Science in Business Analytics (MSBA)

The Part-Time Master of Science in Business Analytics (MSBA) program at Carnegie Mellon University is an online program designed to provide the same high-quality education as the full-time MSBA, but with added flexibility. It is ideal for individuals seeking to advance their careers in business analytics without compromising on academic rigor. The program does not require an application fee and offers a streamlined, two-phase application process to accommodate busy professionals.

Sport Analytics

The Analytics Edge

The Analytics Edge is a graduate-level course offered at the MIT Sloan School of Management, focusing on the practical application of analytical techniques in business and mathematics. It covers essential topics in management, operations management, and probability and statistics, equipping students with the skills to leverage data for informed decision-making. The course is designed to provide a foundational understanding of how to analyze data and derive actionable insights.