A MS in Data Science is an interdisciplinary degree program designed to provide studies in scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.
Earning a MS in data science can help you gain a broad skill set that can be applied to a vast number of tech-related careers, such as data engineering, data architecture, or computer programming.
As a student in this advanced degree program, you can expect to dive into essential concepts in the following areas:
- Applied Statistics
- Database Systems and Data Preparation
- Practical Machine Learning
You will also learn how to use programming languages like Python, R, and SQL.
To succeed as a data scientist, you need skills from several disciplines, including mathematics, statistics, and computer science. From retrieving statistical data to gaining insights across workflows data science has always been vital for any business.
A MS in Data Science is considered to be an interdisciplinary degree program that is designed to provide studies in scientific methods, processes, and systems to extract knowledge or valuable insights from data in varied forms, either structured or unstructured.
It is a highly selective program for students having a strong background in mathematics, applied statistics, and computer science. The degree usually focuses on the development of new methods for data science.
Universities which provide MS in Data science in the USA
The program offers strong preparation in statistical modelling, machine learning, optimization, management and analysis of massive data sets, and data acquisition. The program focuses on topics such as reproducible data analysis, collaborative problem solving, visualization and communication, and security and ethical issues that arise in data science. Students with bachelor’s degrees in the natural sciences, mathematics, computer science, or engineering are invited to apply for admission.
- The Yale University offers a Master of Arts in Statistics and Data Science duration of 2 years. This course is offered on a full-time basis. This program is provided on-campus and off-campus. In this course, the department offers a broad training program of the main areas of statistical theory, probability theory, stochastic processes, asymptotic, information theory, machine learning, data analysis, statistical computing, and graphical methods.
The 27-unit, online program is designed for the working professional’s schedule and can be completed on one of three paths: accelerated, standard, or decelerated. The multidisciplinary online data science master’s curriculum draws upon computer science, social sciences, statistics, management, and law. Students use the latest tools and analytical methods to work with data at scale, derive insights from complex and unstructured data, and solve real-world problems.
The curriculum for the MS in Data Science (MSDS) in NYU degree is 36 credits. One of the key features of the MS in Data Science curriculum is a capstone project that makes the theoretical knowledge you gain in the program operational in realistic settings. During the project, you will go through the entire process of solving a real-world problem: from collecting and processing real-world data, to designing the best method to solve the problem, and finally, to implementing a solution.
Students typically finish the degree program in 5 or 6 quarters (since summer quarter enrolment is not required, it is not figured into the 5-6 quarters). The M.S. in Statistics and Data Science are terminal degree programs that are designed to prepare individuals for career placement following degree completion. Being located in Silicon Valley (Palo Alto, California), students are ideally placed to pursue work experience and internships with the many tech-giants.
Apart from this list Columbia University, University of Southern California, University of Pennsylvania, University of Virginia are also some of the reputed names when it comes to pursuing MS in data science.
Many students find employment in data science, research analytics, software engineering, program management within the technology sector (operations research), or the finance industry (asset management, acquisitions/mergers, business analytics) as well as various governmental services.
It is a very broad skill and can be applied in different career paths and possibilities. The tech industry is growing at a fast pace, it requires skilled candidates to perform their best for the growth of the company and nation in general.
Many students go for MS after graduation to hone their skills and upgrade their resume to work in a reputed organization that pays well.
Prerequisites for MS in Data Science
- The candidate must score at least a B grade or better in his/her Bachelors Degree from any reputed institution.
- Letters of Recommendation will be required to get admission.
- College work, research, transcripts and other essentials should be kept handy.
- The student must be referred by someone who knows about his/her academic performance.
- Must have a course completed on probability and statistics, programming or calculus.
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