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Data Science

People specializing in data analysis and conversion (data scientists) are the most sought-after experts in the companies such as Microsoft, Nordeus and Seven Bridges Genomics, which has made this profession the most promising one of the 21st century, with an estimated average salary of $ 116,840. Data science brings in the most popular and cutting-edge programming languages such as Python, R, MongoDB, Spark and Hadoop.

The Data Science study program is a unique master’s degree program in Serbia, on a par with the best quality programs in Europe and the world. This program is thought in the Serbian and English Language. The program instructs candidates to design intelligent mobile and web applications, based on extremely large data sets (Big Data). Lecturers whose expertise and publications place them among the most promising young scientists in the region, use their immense enthusiasm to help candidates achieve the highest academic goals and adopt hands-on required by the highest paying jobs in the country and abroad.

hatUpon successfully completing the studies, students acquire the title MASTER SOFTWARE ENGINEER..

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I semestar

The course aims to familiarize students with the basic data processing principles. The focus will be on the following areas: linear regression, classification basics, recommendations systems. It will also provide an overview of clustering algorithms. Furthermore, the most common types of processed data will be demonstrated. During the course, data representing time series, an audio record, an image, a multidimensional string or a text are processed and analyzed.

The course aims to familiarize students with the basic programming languages that are currently the most popular in industry and companies. Depending on the problem being solved, students will acquire knowledge that will help them choose an appropriate programming language.

The advent of the Internet has resulted in a large amount of available data in the form of text documents, images and / or videos. This trend creates the need to efficiently process such data, wherefore special programming languages as well as hardware solutions on computer clusters need to be used.

The course provides basic theoretical knowledge pertaining to the principles, elements and working modules of contemporary non-relational databases. These databases have emerged as there was a need to store distributed large amounts of data that can be structured, missing or unstructured.

  • The candidate takes six exams. The first project assignment integrates three courses from the first semester, whereas the second one integrates three courses from the second semester.
  • During the semester, the candidate defines the topic for his/her master’s thesis. The project assignments from the first and second semester can be integrated into the master’s thesis.

II semestar

Students are acquainted with visual data processing. Through practical examples, students will learn about the process of extracting essential information from the image and abilities to develop intelligent services based on it.

Students are acquainted with textual data processing. Through practical examples, students will learn about the process of extracting essential information from the text and abilities to develop intelligent services based on it.

A student is able to identify the problem / problems that requires / require research prior to developing a medium complexity software system in a specific domain of application and selecting and applying an adequate research methodology / tools.

This subject is oriented towards the practical aspects of the synthesis and evaluation of DS systems, following the basic paradigm of the synthesis cycle: collecting data, researching trends and characteristics, developing a model that makes decisions based on data, measuring and evaluating the model’s accuracy, efficiently visualizing the solutions achieved.

The student is familiar with the requirements that they need to fulfill to quickly and efficiently join in the work processes of the organizations that develop and produce software and / or are engaged in the sale or provision of advisory services in the IT domain. The student has the basic knowledge and skills necessary for quick and efficient inclusion in the work processes of these organizations.

The student is competent to identify the problem, perform an analysis and specify a medium complexity Data Science system, using methodological approaches and machine learning technologies. Subsequently, he is able to implement it using trending technologies and software engineering tools, and finally critically evaluate the results achieved and propose further course of action.

  • The candidate takes six exams. The first project assignment integrates three courses from the first semester, whereas the second one integrates three courses from the second semester.
  • During the semester, the candidate defines the topic for his/her master’s thesis. The project assignments from the first and second semester can be integrated into the master’s thesis.