One must accomplish two things when earning a PhD. First one must understand a particular subject thoroughly. Secondly, one must extensively in knowledge about that subject.
Businesses rely on the use of data, but today data is available at such a capacity that it is difficult to pull value from it. The study of data science is a combination of social science, computer science, statistics, and information. Students may focus on computational machine learning or data warehousing.
Request Information Part time Doctoral Programs in Data Science 2018
Our Ph.D. program is traditional and innovative - applied and theoretical, a Ph.D. for the 21st century. Real-world application, with real-world data, drives our student's learning process. Take a glimpse at some of the exciting findings our students have uncovered as they apply their learning. [+]
Kennesaw State University's Ph.D. in Analytics and Data Science is an advanced degree which has been developed to meet the market demand for Data Scientists.
This degree will train individuals to translate large, structured and unstructured, complex data sets into information to improve decision making. This curriculum includes a heavy emphasis on programming, data mining, statistical modeling, and the mathematical foundations to support these concepts. Importantly, the program also emphasizes communication skills - both oral and written - as well as application and tying results to business and research problems.
Because this degree is a Ph.D., it creates flexibility. Graduates can either pursue a position in the private or public sector as a "practicing" Data Scientist - where continued demand is expected to greatly outpace the supply - or pursue a position within academia, where they would be uniquely qualified to teach these skills to the next generation.... [-]
The IDIC offers a fully funded four-year PhD programme in either the area of digital economy or energy technologies. [+]
The Horizon Centre for Doctoral Training offers 10-20 places on the four-year research programme, My Life in Data, which focuses on researching personal data and the traces we leave behind. This data is now a major business and societal asset and can reveal a wealth of information about our habits, behaviours, preferences, relationships and emotions.Programme overview
The PhD programme accepts applicants from a wide range of backgrounds including computer science, engineering, mathematics, human factors, psychology, sociology, business, geography, social science and the arts.
The course consists of taught modules, annual summer schools, retreats and a three month internship taken with one of the CDT’s partner organisations.... [-]
The Big Data Institute (BDI), Shenzhen University was found in 2013, which is a core part of collaborative innovation center between Guangdong province and Hong Kong. Currently, BDI has over twenty academic staff including 1 IEEE fellow, 6 full professors, 4 associate professors and 2 post-doctoral fellows. [+]
Shenzhen is a renowned special economic zone in China, adjacent to the two international metropolises – Hongkong and Macao. It is one of the cities with the most developed economy and it plays a leading role in the cause of modernization and internationalization.
Shenzhen University, as one of the most popular universities in China with fast growth, distinctive characteristics and huge potential, is now accelerating its pace toward the top-ranking university with high level research, excellent knowledge and innovation.
The Big Data Institute (BDI), Shenzhen University was found in 2013, which is a core part of collaborative innovation center between Guangdong province and Hong Kong. Currently, BDI has over twenty academic staff including 1 IEEE fellow, 6 full professors, 4 associate professors and 2 post-doctoral fellows.... [-]
Research in multidimensional complex analysis at Siberian Federal University is about several topics. The overarching theme is the interaction between complex analysis and other areas of mathematics and physics. [+]
Research in multidimensional complex analysis at Siberian Federal University is about several topics. The overarching theme is the interaction between complex analysis and other areas of mathematics and physics. For example, methods and techniques of functional analysis are applied to the study of PDEs in domains of complex space. Algebraic geometry plays an important role in the study of distribution of complex algebraic and analytic sets and its applications in physics. Alternatively, analytic methods are used in the theory of algebraic and hypergeometric functions, in the description of the structure of discriminantal sets. Other examples include the study of multidimensional difference equations, analytic continuation of functions and sets.... [-]