Find Masters Programs in Data Science in North America 2019
In order to successfully obtain a Masters qualification, you will need to obtain a number of credits by passing individual modules. Most taught Masters will have a number of core modules which you must take and pass in order to obtain the qualification. The assessment of research Masters is almost always entirely by a single dissertation module or project.
View all Master Programs in Data Science in North America 2019
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A flexible and affordable degree from one of the top Computer Science programs in the world focused on one of the hottest fields of the new millennium.
This MicroMasters program in Statistics and Data Science is comprised of four online courses and a virtually proctored exam that will provide you with the foundational knowledge essential to understanding the methods and tools used in data science, and hands-on training in data analysis and machine learning. You will dive into the fundamentals of probability and statistics, as well as learn, implement, and experiment with data analysis techniques and machine learning algorithms. This program will prepare you to become an informed and effective practitioner of data scientist who adds value to an organization. The credential can be applied, for admitted students, towards a Ph.D. in Social and Engineering Systems (SES) through the MIT Institute for Data, Systems, and Society (IDSS) or may accelerate your path towards a Master’s degree at other universities around the world.
Master algorithmic programming techniques necessary for top software engineering professions.
Gain the critical skills needed to become a data scientist, rated one of the best jobs in America and in demand globally.
The Master of Data Science is a master’s degree in data science, an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured, similar to data mining.
Learn the theoretical knowledge and practical skills necessary to analyze big data for functional application in business and technology.
As data accumulates across broad sectors of industry and academia we see a need for data scientists equipped with skills to assist with data-based decision making. For example, businesses are using data to determine insurance coverage, to make marketing decisions, to offer recommendations to customers, and to provide more effective health care. A famous example from academia is the determination of the Higgs Boson from simulated data with machine learning methods.