A masters is the first level of graduate coursework and can be obtained after you receive a bachelor’s degree. Earning a masters usually requires two years of full-time study, which amounts to 36 to 54 semester credits.
Spanning 23 countries, North America is continent filled with educational opportunity. Students have the opportunity to learn multiple languages and develop an understanding of vastly different cultures.
View all Master Programs in Data Science in North America 2018
Master algorithmic programming techniques necessary for top software engineering professions. [+]
This MicroMasters program is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems through implementing over one hundred algorithmic coding problems in a programming language of your choice.
No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we have invested thousands of hours designing challenges as an alternative to multiple choice questions that you usually find in MOOCs. We believe in learning through application, especially when it comes to learning algorithms.
For each algorithm you develop and implement, we have designed multiple tests to check its correctness and running time — you will have to debug your programs without even knowing what these tests are! It may sound difficult, but we believe it is the only way to truly understand how the algorithms work and to master the art of programming.... [-]
The Master of Science in Data Science for Public Policy (MS-DSPP) is a joint degree offered by Georgetown’s McCourt School of Public Policy and Georgetown’s Graduate Analytics program combining the historic strengths of McCourt’s public policy analysis curriculum with the cutting-edge computational, mathematical, statistical methods training of Georgetown’s Analytics program. [+]
From our smartphones and our credit cards; to our tweets and our cars - data are everywhere and in everything. Even in power lines, airports and the roads we drive on, data exist in places that we wouldn’t even think of.
The smart and intentional application of these data could allow us to make better public policy decisions, find patterns, and more effectively deliver critical services like healthcare, education and national security. In governments around the world and in the nonprofit and private sectors, the demand for data analysts, scientists, and data-savvy managers is increasing quickly.... [-]
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.[+]
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.
Enroll in the Master of Computer Science in Data Science (MCS-DS) and gain access to the computational and statistical knowledge needed to turn big data into meaningful insights. Build expertise in four core areas of computer science—data visualization, machine learning, data mining, and cloud computing—while learning key skills in statistics and information science. This completely online degree is an affordable gateway to one of the most lucrative and fastest growing careers of the new millennium.
The MCS-DS is offered by CS @ ILLINOIS, a U.S. News & World Report top five CS graduate program, in collaboration with the University’s Statistics Department and top-ranked iSchool. Join our alumni network of entrepreneurs, educators, and technical visionaries, who have revolutionized the way people communicate, shop, conduct business, and are entertained. From the ILLIAC to Blue Waters, OpenMP to MPI, Mosaic to YouTube, and the first vectorizing compilers to LLVM, CS @ ILLINOIS has long been at the forefront of excellence in computing and education.... [-]
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. [+]
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.
We offer a Masters in Data Science degree that covers basic and advanced essentials in statistical inference, machine learning, data visualization, data mining, and big data methods, all of which are key for a trained data scientist. In order to be selected for our program, we require a basic background in calculus, linear algebra, probability, computer programming, data structures, and algorithms. Our program is spread across 30 credits and contains projects involving big datasets, classification methods, variable selection, and deep learning to name a few.... [-]