Introduction to Data Mining
Data mining involves discovering patterns of large data sets which includes artificial intelligence, machine learning, statistics and database system. Data Mining is s computing process and an interdisciplinary field of computer science. The students learn the process of extraction of information from data set and in its transformation into understandable structures and its application. The aspects of data mining covers database, data management and data processing. Data mining helps to identify and solve the problems by data analysis. The advanced course in data mining prepares the students to become efficient professionals in the global arena.
Eligibility Criteria for the course
Candidates who have competed Masters degree in computer application/computer science/statistics/computer engineering from a recognized university are eligible. Students should have ground knowledge in calculus. They should have programming and modeling experience. They should possess good communication skills and strong English foundation in writing and reading capabilities.
Additional Description of data mining Ph.D course
The program is interdisciplinary and helps the students to equip with teaching skills for future generations. The course enables students to gain deep knowledge of statistics, data analysis and programming. Data mining has integrated our lives and is changing the working styles of people in the organizations. Students learn pure and applied theory to get understanding of methodologies used and to become critical thinkers. The course trains students for becoming efficient leadership positions and for entry into top most positions in the companies. Students gain access to real data sets and are exposed to work in cutting edge technologies.
The curriculum includes programming, data mining, statistical modeling, mathematical foundation, The course emphasizes on enhancing communication skills for business and research programs. The subjects of study includes data mining, segmentation, models, binary classification, social network analysis, linear models, graph theory, survey data, computational mathematics, machine learning, big data analytics, advanced data base. The data mining tools and techniques are used in many areas such as genetics, research areas, mathematical fields, cybernetics and marketing. The data mining is used to uncover the hidden patterns to business predictions to improve marketing campaigns and in sales of new products and services.
Job Prospects for Ph.D Mining
The students find jobs in public /private sectors, academia and business sectors. The job profiles includes data mining analysts, advanced analytics engineer, data scientist, software engineer, research statistician, quantitative analyst, research scientist, chief data officer, analytic manager, project manager,
Ph.D Data Mining Admissions for 2018 - 2019 Academic Year
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