The Postgraduate Study Programs MSc in Data Analytics and Financial Technology is a joint Inter-university Degree Study Programs between the Department of Administrative Science and Technology and Department of Accounting and Finance of the Hellenic Mediterranean University (GR) and the Department of Accounting and Finance and Department of Computer Science of Neapolis University Pafos. It leads to a joint Master’s Degree of Studies of the two Higher Education Institutions without requiring a recognition process by D.O.A.T.A.P. The Programs is aimed primarily at graduates of Finance, Accounting, Economics, Business Administration and Computer Science.

Our Data Analytics programme is designed to equip you with the advanced analytical skills and critical thinking needed to thrive in today’s data-driven world. This program combines cutting-edge techniques in data management, statistical analysis, and machine learning.

Specialize in harnessing analytics, data science, and machine learning to enhance health care outcomes. You’ll take classes that delve into advanced statistics, mining health care data, health data integration, and other analytics concepts.

Develop advanced data science skills, including machine learning and data analysis that are essential for careers in many data-driven sectors through a flexible, online MSc. Develop core skills in data science essential to successful careers in many data-driven sectors.

The Master of Science in Data Analytics program provides students with the critical skills necessary to become Data Analysts or Data Scientists working in a variety of fields across all industries. The integration of Data Analytics and Informatics has created a demand for professionals who can make data-driven decisions that propel their organizations forward.

The MSc Data Analytics is designed to accommodate a broad audience of learners whose particular pursuits in data analytics might be either technical or business-focused. The programme makes use of academic research, industry-defined practical problems, and case studies, to offer an approach that will genuinely foster a deeper knowledge of the subject area.

The Master of Science (MS) in Data Science and Analytics prepares students to transform data into information so that insight is gained for addressing real-world problems.

DSTI Applied MSc in Data Analytics master’s level programme propels you far beyond the conventional analytics training offered by typical business schools. This unique MSc programme delivers an unparalleled blend of advanced mathematics, computational science, and cutting-edge IT practices—all taught in English. By fully integrating deep technical skills into a profound business perspective, we empower you to move from mere insight generation to hands-on implementation and automation of analytics solutions within modern information systems.

Big data analytics comprises advanced analytics involving intricate applications of statistical, mathematical concepts in conjunction with advanced algorithms. This upbeat and hands-on style to reach business decisions is transformative because it empowers decision-makers with the power to make informed decisions to approach real-time business objectives. The MSc program in Big Data Analytics would allow students to gain an understanding of the various data sources and enable them to study, understand and analyze the data incurred across sources. This program in big data analytics follows a multi-disciplinary approach at its center, focusing on the prevalent as well as evolving Big Data tools like Hadoop and Cloud Architecture. This program is everything one would need to make an effective career shift and delve into the world of big data analytics.

Learn to use big data to help companies make better and faster decisions and operate more efficiently. The data analytics master’s degree at Canisius University offers real-world learning opportunities, strong industry connections, and flexible course delivery options to fit your schedule. When you graduate, you’ll be prepared to work as a data specialist across a range of industries and organizations.

As we move towards greener technologies, mastering data is key to optimizing the development and integration of renewable energy solutions. Our Impact MSc in Data Analytics for Renewable Energy program empowers you with the practical skills and in-depth knowledge needed to drive the transition to clean energy using data analytics.

Get to grips with data technology, data applications, data strategies and data-driven decision making, and combine these with actionable business insights through the online master’s in Data & Business Analytics.

The Master of Science in Data Science program qualifies for STEM OPT/CPT benefits, allowing international students up to 36 months of practical training, and offers a rigorous and comprehensive curriculum that equips students with advanced skills in statistical methods, data analytics, artificial intelligence, and ethical technology management. The program combines core courses such as Statistical Methods, Quantitative Methods, and Data Analytics with specialized classes in Big Data Analytics for IoT, Applied AI, and Advanced AI for Business Insights while enabling international students to access 12 months of CPT during the program, 12 months of initial OPT, and an additional 24-month STEM OPT extension with qualifying employers.

Our part-time MSc Data and Decision Analytics, studied over 24 months, prepares students not only to be able to analyse and digest data but also to translate this into effective decision-making in the age of Big Data. Delivered through a mixture of live online sessions and asynchronous activities, this course combines theoretical foundations with practical hands-on experience.

The EDHEC Online MSc in Data Management and Business Analytics is designed to train experts and professionals to master the process of data management, from the collection of data to the use of tools and techniques and the creation of models, allowing them to become immediately operational in their respective fields.