Data Science, or data science, plays an extremely important role in
today's world, transforming the way we make decisions,
conduct business and solve problems. In an era of tremendous growth in the amount of
data generated daily by a variety of sources, from social media
to information systems, the skillful use of this data is becoming a key
success factor. Data Science combines statistical techniques,
data analysis, machine learning and big data processing to uncover
hidden patterns, relationships and information that can lead to more accurate
conclusions and better business decisions. Companies using Data Science can
optimize their processes, improve efficiency, better understand
customers' needs and predict market trends. In addition, Data Science plays
a key role in the development of new technologies such as artificial intelligence,
process automation and the Internet of Things (IoT). With the growing importance of
data as a strategic resource, Data Science skills are becoming
increasingly sought after on the job market, highlighting the central role of this
field in today's world.

The use of deep learning methods, advanced statistical analysis and
machine learning classifiers in Data Science opens the door to a revolution in
data analysis and decision-making. Deep learning methods, based on
multilayer neural networks, make it possible to automatically detect
complex patterns and relationships in data to create accurate
predictive and classification models. Advanced statistical analysis,
including techniques such as cluster analysis, principal component analysis or
feature space analysis, enables the identification of significant relationships between
variables and the reduction of data dimensionality, leading to more
transparent and interpretable results. Machine learning classifiers,
including models based on decision trees, SVM (Support Vector
Machines) algorithms, or k-nearest neighbor algorithms, allow efficient
data classification and the creation of recommendation systems. Combined, these
techniques create powerful data analysis tools that find application in
various fields, from business to medicine, enabling a better understanding of
data, predicting trends and making more accurate decisions.
Modern Data Science relies on the synergy of these methods, leading to
innovative solutions and driving advances in data analysis.

Career prospects for graduates of the
Data Science specialty are promising and booming in view of the growing
importance of data in the modern world. Graduates with
advanced knowledge in data analysis, machine learning, statistics
and programming are becoming highly sought-after professionals on the job market.
Employment opportunities for them are extremely broad, covering sectors such as
finance, medicine, retail, marketing, industry, and research. In
data analytics, they can work as data analysts, data scientists or

data engineers, engaged in collecting, processing and analyzing
data to generate business insights and make strategic decisions.
In the area of artificial intelligence and machine learning, they can serve as
researchers, creating and refining algorithms and predictive models. Companies
technology companies, corporations, government agencies and academic institutions are looking
for qualified professionals to develop and implement innovative
data-driven solutions. Additionally, there is no shortage of opportunities to work as consultants or
freelancers, providing data analysis services to various clients. With
increasing demand for data experts, career prospects for
Data Science graduates are promising and offer many
opportunities for professional and personal growth.

This silhouette has a particularly broad area thematic focus, so four subject areas have been identified within it:

- Area - Databases
- Area - Software Engineering
- Area - Business Application Programming
- Area - Project Management

A graduate educated according to this silhouette is a specialist prepared to work in larger software development teams and business process analysis and support teams. With knowledge in the areas of requirements engineering, databases, data warehousing and data mining, business process modeling and team communication, and business decision-making processes, he or she is prepared to mediate communication between software development teams and business teams.

A good knowledge of technology, databases, systems architecture, and analysis and design methods enables him or her to grow professionally in a variety of occupations and roles from business analyst, systems analyst, requirements engineer, programmer, website designer, database designer and administrator, data warehouse designer and analyst, software engineer to managers of IT development, support and project teams.

Potential places of employment for such a prepared candidate include companies that develop and implement software, especially business systems, organizations that own and process large data sets (including banks, insurance companies, telephone operators), companies that provide business intelligence services, development and support departments and analytical departments of large enterprises.

Elective subjects related to silhouette

For those choosing this area , please refer to the recommendations of elective subjects for your preferred subject area.

Candidate Profile

A candidate interested in an education aimed at this silhouette should be characterized by analytical thinking skills, proficiency in a selected general-purpose programming language and knowledge of the basics of database systems, as well as an aptitude for communication and the ability to work in a team. Familiarity with object-oriented analysis and design methods, including the UML language, is desirable.

Occupations in which a graduate pursuing this silhouette may find employment include network and computer systems administrator, data center designer and administrator, mobile application developer, wireless communication systems designer and administrator, ICT systems security specialist, cloud services designer, DevOps engineer, or streaming services designer and administrator. Potential employers include telecom operators, mobile system and application manufacturers, and cloud-based service providers.

The term interactive multimedia covers issues of user interaction with information systems, usually online. A special role is played here by interaction, i.e. two-way communication of a person with the system or with other users through the system (e.g. in games and other activities requiring interaction). Such interaction is enabled by multimedia interfaces.

Interactive media integrates computer, data, television, phone and mobile devices, interfaces, and other information technologies. Interactive media refers to conceptual interaction design, graphical user interface, new media, digital culture, and enriched and virtual reality. Among the most popular interactive multimedia applications are games, educational and training programs, electronic encyclopedias and travel guides. The user of an interactive multimedia application becomes an active participant in two-way, wide-ranging communication.