Big Data Analytics (Non-Thesis) MEF University

Overview

Programme Learning Outcomes

•  Building on the skills acquired during the undergraduate degree, an improved and deepened level of expertise in the field of big data analytics related to machine learning.

• Applied in-depth theoretical and practical knowledge in the fields of statistics, computation and computer science related to machine learning.

• Extensive knowledge about the analysis and modeling methods used in machine learning and their limitations.

• Ability to design and perform exploratory research based on analytics, modeling and experimentation; to generate solutions to complex situations encountered in this process and to interpret the results.

• Ability to describe the analytics process and its results both verbally and in writing on national and international platforms within or outside of the field of machine learning.

• Awareness of social, scientific and ethical values regarding the machine learning, processing, usage, interpretation and dissemination stages and in all related professional activities.

• Professional awareness new and emerging applications in the machine learning field and an ability to demonstrate their uses.

• Competence to act as a leader in multi-disciplinary teams, to develop big data-driven solutions to complex situations; to take responsibility.

• Ability to communicate in English both verbally and in writing at European Language Portfolio General Level B2.

• Understanding of social and environmental aspects of machine learning applications.

Graduate Profile

Graduates of this Big Data Analytics (Non-Thesis) programme at MEF University will have a wide range of job opportunities in the IT and technology sectors. The comprehensive knowledge and skills provided by the programme allow graduates to be employed in the following areas:

• Data Scientist: They can work on data-driven projects by specializing in big data analysis, artificial intelligence and machine learning.

• Project Manager: They can assume responsibilities such as project management and strategic planning in technology projects.

• IT Consultant: They can provide consultancy services to improve and optimize companies' information technology infrastructures.

• Smart Systems and Artificial Intelligence Engineer: They can work on artificial intelligence, smart systems and robotic applications.

• E-commerce and Digital Marketing Specialist: They can produce e-commerce strategies and digital marketing solutions on digital platforms.