Master's Degree in Computing in Istanbul in Turkey

View all Masters Programs in Computing 2017 in Istanbul in Turkey

Computing

Master-level studies involve specialized study in a field of research or an area of professional practice. Earning a master’s degree demonstrates a higher level of mastery of the subject. Earning a master’s degree can take anywhere from a year to three or four years. Before you can graduate, you usually must write and defend a thesis, a long paper that is the culmination of your specialized research.

The computing field covers a wide range of studies, including information systems, computer engineering, information technology, computer science and software engineering. Different computing disciplines may cover software and hardware system building and design, the creation of intelligent computers, information structuring and scientific research.

Universities in Turkey provide either two or four years of education for undergraduate studies, while graduate programs last a minimum of two years. There are around 820 higher education institutions in Turkey including 76 universities with a total student enrollment of over 1 million. The quality of education at the Turkish universities varies greatly, some providing education and facilities on par with internationally renowned schools.

Istanbul is one of the largest urban agglomerations in Europe with around 14 million citizens. Many of the universities in Turkey are located there or at least have campuses there. It’s also known for private higher education sector and award-winning institutes, especially for biomedicine.

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Professional Master's Degree in Data Analytics

Sabanci University
Campus Full time 1 year October 2017 Turkey İstanbul

Big data is paving the way to empower businesses to make better decisions: With the amount of digital data increasing at an enormous rate, rigorous research is carried out in an effort to extract value from the massive data sets, to turn them into smarter decisions for improving business results. The emerging field of Data Analytics holds the key to unleashing that potential. [+]

Masters in Computing in Istanbul in Turkey. Big data is paving the way to empower businesses to make better decisions: With the amount of digital data increasing at an enormous rate, rigorous research is carried out in an effort to extract value from the massive data sets, to turn them into smarter decisions for improving business results. The emerging field of Data Analytics holds the key to unleashing that potential. Data Analytics is considered to be a relatively new field which integrates state-of-the-art computational and statistical techniques to extract business value from a rapidly expanding volume of data. Many consulting firms claim that Data Analytics will be one of the key skills of the 21st century. Most critical issue, however, is the shortage of analytical talent that could turn the high-volume data into useful information that will be used for better decision making. In a business world in which the gap between winners and losers is narrowing down, companies are increasingly turning to data analytics to gain a competitive advantage in productivity, profitability and sustainable manufacturing processes for better products and better services. To be able to do that, companies need trained workforce skilled in Data Analytics, who are equipped to manage, understand and model the data, interpret the outcome and communicate the results for business use. Professionals holding a degree in Data Analytics will be well positioned to help their organizations gain a competitive advantage in a data-driven world. This program is designed to help our participants develop the skill set needed for creating and maintaining the added competitive edge that innovative companies are trying to establish. Our curriculum will help you develop skills required for data-driven decision-making with a wide variety of courses such as: Programming, Data management and data processing, Data mining, Machine learning, Statistical models for data analysis, Optimization, Decision modeling, Exploratory data analysis and visualization, Social network analysis, Data privacy, security and forensic discovery, Information security law, Business communication, Project management, a capstone project and more. Admission Requirements Applications for non-thesis master’s programs are evaluated by the assigned Admission Jury. Suitable candidates are invited to a personal interview. Admissions are finalized by the approval of the related Graduate School Board upon the recommendation of the Jury and are announced to the applicants. Application periods can be found in the Academic Calendar of Sabanci University. Your registration will be completed upon the approval of Turkish Higher Education Council regarding the equivalence of the last graduated higher instution and the course of study. Program Structure Professional Master's Degree in Data Analytics is a 30-credit program that can be completed in one academic year. The courses are distributed across three consecutive semesters (Fall-Spring-Summer), each of which lasts 14 weeks. Students take 10 courses (excluding the Term Project) in total from various areas. The Term Project is a non-credit course. Who should apply Professional Master’s Degree in Data Analytics is designed for working professionals who are looking into developing their analytical skills with no interruption on participants’ careers. The expected participant profile: Graduates of disciplines with a solid quantitative background (e.g. computer science, engineering, mathematics, physics, statistics, economics and other fields with a quantitative focus), or All professionals who have ample work experience in a data-analytics-related area and are seeking in-depth training in Big Data Analysis. Skills Acquired Diagnose, understand, measure and evaluate data to enable better decision making within the organization. Define and apply appropriate methodologies for complex business problems. Interpret findings, present and communicate the results. Graduates can find work as data analysts, data managers, data modelers and data scientists in the financial institutions, healthcare industry, insurance industry, telecommunications industry, marketing and media firms, retail industry and government agencies. [-]