Study Plan

Competences

The competence framework states the academic capabilities this programme is designed to build. Each entry keeps its linked learning outcomes visible so the structure can be followed without leaving the page.

Key competences

4 entries

CC1

mathematical competence and competence in science, technology and engineering

See details

Linked learning outcomes

(no linked learning outcomes)

CC2

digital competence

See details

Linked learning outcomes

(no linked learning outcomes)

CC3

personal, social and learning to learn competence

See details

Linked learning outcomes

(no linked learning outcomes)

CC4

entrepreneurship competence

See details

Linked learning outcomes

(no linked learning outcomes)

Professional competences

28 entries

CP1

ARACIS Informatică CPS 1.1

See details

Uses data structures, algorithms and programming paradigms

Linked learning outcomes

C1 A56 R20

CP2

ARACIS Informatică CPS 1.2

See details

Uses the mathematical foundations applied in computer science, including formal logic, algebra, probability, and statistics.

Linked learning outcomes

C2 A57 R21

CP3

ARACIS Informatică CPS 1.3

See details

Manages computer networks and operating systems.

Linked learning outcomes

C3 A58 A59 R22

CP4

ARACIS Informatică CPS 1.4

See details

Designs databases.

Linked learning outcomes

C4 A60 R23

CP5

ARACIS Informatică CPS 1.5

See details

Uses modern programming paradigms, including functional, object-oriented, and parallel programming.

Linked learning outcomes

C5 A61 R24

CP6

ARACIS Informatică CPS 1.6

See details

Uses advanced concepts and techniques from the fields of artificial intelligence, machine learning, and natural language processing.

Linked learning outcomes

C6 A62 R25

CP7

ARACIS Informatică CPS 1.7

See details

Protects computer systems using computer security techniques, both software and hardware.

Linked learning outcomes

C7 A63 R26

CP8

ARACIS Informatică CPS 1.8

See details

Designs and manages the development of complex IT projects, using modern strategies.

Linked learning outcomes

C8 A64 A65 R27 R28

CP9

analyse business requirements

See details

Study clients' needs and expectations for a product or service in order to identify and resolve inconsistencies and possible disagreements of involved stakeholders.

Linked learning outcomes

C9 A1 A2 R1

CP10

apply ICT systems theory

See details

Implement principles of ICT systems theory in order to explain and document system characteristics that can be applied universally to other systems

Linked learning outcomes

C16 C17 A14 R5

CP11

create data sets

See details

Generate a collection of new or existing related data sets that are made up out of separate elements but can be manipulated as one unit.

Linked learning outcomes

A15 A16 A17 A18

CP12

creatively use digital technologies

See details

Use digital tools and technologies to create knowledge and to innovate processes and products. Engage individually and collectively in cognitive processing to understand and resolve conceptual problems and problem situations in digital environments.

Linked learning outcomes

C18 A19 A20 R6

CP13

define technical requirements

See details

Specify technical properties of goods, materials, methods, processes, services, systems, software and functionalities by identifying and responding to the particular needs that are to be satisfied according to customer requirements.

Linked learning outcomes

C10 A3 A4 R2

CP14

deliver visual presentation of data

See details

Create visual representations of data such as charts or diagrams for easier understanding.

Linked learning outcomes

C19 A21 A22 R7

CP15

design process

See details

Identify the workflow and resource requirements for a particular process, using a variety of tools such as process simulation software, flowcharting and scale models.

Linked learning outcomes

C11 C12 A5 A6

CP16

develop computer vision system

See details

Apply and combine different computer vision tools and methods such as image acquisition, image processing, image segmentation and classification, detection, etc. in one system to allow computers to extract information from digital images such as photographs or video.

Linked learning outcomes

C20 C21 A23 R8

CP17

develop software prototype

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Create a first incomplete or preliminary version of a piece of software application to simulate some specific aspects of the final product.

Linked learning outcomes

C13 A7 A8 R3

CP18

develop statistical software

See details

Participate in the various development stages of computer programs for econometric and statistical analysis, such as research, new product development, prototyping, and maintenance.

Linked learning outcomes

C22 C23 A24 A25

CP19

establish data processes

See details

Use ICT tools to apply mathematical, algorithmic or other data manipulation processes in order to create information.

Linked learning outcomes

C24 A26 A27 R9

CP20

handle data samples

See details

Collect and select a set of data from a population by a statistical or other defined procedure.

Linked learning outcomes

C25 A28 A29 A30

CP21

implement data quality processes

See details

Apply quality analysis, validation and verification techniques on data to check data quality integrity.

Linked learning outcomes

C26 A31 A32 A33

CP22

normalise data

See details

Reduce data to their accurate core form (normal forms) in order to achieve such results as minimisation of dependency, elimination of redundancy, increase of consistency.

Linked learning outcomes

C27 A34 A35 R10

CP23

perform data cleansing

See details

Detect and correct corrupt records from data sets, ensure that the data become and remain structured according to guidelines.

Linked learning outcomes

C28 A36 A37 R11

CP24

perform dimensionality reduction

See details

Reduce the number of variables or features for a dataset in machine learning algorithms through methods such as principal component analysis, matrix factorization, autoencoder methods, and others.

Linked learning outcomes

C29 A38 A39 R12

CP25

use software libraries

See details

Utilise collections of codes and software packages which capture frequently used routines to help programmers simplify their work.

Linked learning outcomes

C14 A9 A10 A11

CP26

utilise computer-aided software engineering tools

See details

Use software tools (CASE) to support the development lifecycle, design and implementation of software and applications of high-quality that can be easily maintained.

Linked learning outcomes

C15 A12 A13 R4

CP27

conduct literature research

See details

Conduct a comprehensive and systematic research of information and publications on a specific literature topic. Present a comparative evaluative literature summary.

Linked learning outcomes

C30 C31 A40 R13

CP28

develop data processing applications

See details

Create a customised software for processing data by selecting and using the appropriate computer programming language in order for an ICT system to produce demanded output based on expected input.

Linked learning outcomes

C32 C33 A41 R14

Transversal personal competences

7 entries

CT1

analyse big data

See details

Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.

Linked learning outcomes

C34 C35 A42 A43

CT2

apply statistical analysis techniques

See details

Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.

Linked learning outcomes

C36 C37 A44 R15

CT3

develop creative ideas

See details

Developing new artistic concepts and creative ideas.

Linked learning outcomes

C38 A45 A46 A47

CT4

execute analytical mathematical calculations

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Apply mathematical methods and make use of calculation technologies in order to perform analyses and devise solutions to specific problems.

Linked learning outcomes

C39 C40 A48 R16

CT5

interpret current data

See details

Analyse data gathered from sources such as market data, scientific papers, customer requirements and questionnaires which are current and up-to-date in order to assess development and innovation in areas of expertise.

Linked learning outcomes

C41 A49 A50 R17

CT6

manage data collection systems

See details

Develop and manage methods and strategies used to maximise data quality and statistical efficiency in the collection of data, in order to ensure the gathered data are optimised for further processing.

Linked learning outcomes

C42 C43 A51 R18

CT7

use data processing techniques

See details

Gather, process and analyse relevant data and information, properly store and update data and represent figures and data using charts and statistical diagrams.

Linked learning outcomes

C44 A52 A53 R19

Transversal interpersonal competences

1 entries

CT8

report analysis results

See details

Produce research documents or give presentations to report the results of a conducted research and analysis project, indicating the analysis procedures and methods which led to the results, as well as potential interpretations of the results.

Linked learning outcomes

C45 C46 A54 A55

Transversal global citizenship competences

1 entries

CT9

identify processes for re-engineering

See details

Identify potential to restructure a company or part of its operations, e.g. by exploiting information technology.

Linked learning outcomes

C47 C48 A66 R29

Learning outcomes

Learning outcomes translate the competence framework into observable academic results. Each entry keeps its connected competences and subject anchors visible so the curriculum can be followed in both directions.

Knowledge

48 entries

identifies, explains, and justifies fundamental concepts of data structures, algorithms, and programming paradigms, as well as computer architecture.

1 competences | 4 subjects

evaluate · 6/6

See details

Linked competences

CP1

Linked subjects

Algorithms and Data Structures 1 Programming 1 Logic For Computer Science Computer Architecture

selects, explains, and specifies the mathematical foundations applied in computer science, including formal logic, algebra, probability, and statistics.

1 competences | 8 subjects

understand · 2/6

See details

Linked competences

CP2

Linked subjects

Logic For Computer Science Fundamentals Of Mathematics Probability Theory and Statistics Calculus Formal Languages and Automata Theory Graph Theory and Combinatorics Numerical Methods Data Compression Algorithms

describes, identifies, and explains the operation and administration of computer networks and operating systems.

1 competences | 2 subjects

understand · 2/6

See details

Linked competences

CP3

Linked subjects

Computer Networks Operating Systems 1

identifies, selects, and justifies principles and design models of databases.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CP4

Linked subjects

Databases Software Engineering

selects, describes, analyzes, and explains modern programming paradigms, including functional, object-oriented, and parallel programming, using current languages and frameworks.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP5

Linked subjects

Software Engineering Graphics and User Interfaces

identifies, compares, recognizes, and describes advanced concepts and techniques in the fields of artificial intelligence, machine learning, and natural language processing.

1 competences | 3 subjects

analyze · 4/6

See details

Linked competences

CP6

Linked subjects

Artificial Intelligence Natural Language Processing Deep Learning

names, recognizes, and justifies information security techniques, both software and hardware.

1 competences | 3 subjects

Taxonomy not set

See details

Linked competences

CP7

Linked subjects

Computer Networks Operating Systems 1 Security and Cryptography

names, provides examples, concludes, specifies, recognizes, and critically justifies methods for designing and managing complex IT projects, using modern strategies.

1 competences | 4 subjects

Taxonomy not set

See details

Linked competences

CP8

Linked subjects

Algorithms and Data Structures 1 Software Engineering Ai Project Programming Project

Identify stakeholder requirements conflicts in business briefs.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CP9

Linked subjects

Methods and Practices In Informatics

C10

Translate stakeholder needs into measurable technical specifications.

1 competences | 1 subjects

create · 5/6

See details

Linked competences

CP13

Linked subjects

Methods and Practices In Informatics

C11

Identify workflow steps for a process scenario.

1 competences | 3 subjects

understand · 2/6

See details

Linked competences

CP15

Linked subjects

Programming 1 Robotic Process Automation Planning Techniques For Robotics

C12

Map resource needs for a process model.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP15

Linked subjects

Programming 1 Robotic Process Automation

C13

Select core features for a software prototype scope.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP17

Linked subjects

Programming 1

C14

Evaluate library output against expected program behavior.

1 competences | 0 subjects

evaluate · 6/6

See details

Linked competences

CP25

Linked subjects

(no linked subjects)

C15

Select suitable CASE tools for a software project.

1 competences | 0 subjects

apply · 3/6

See details

Linked competences

CP26

Linked subjects

(no linked subjects)

C16

Identify ICT system components and their functional relationships.

1 competences | 3 subjects

analyze · 4/6

See details

Linked competences

CP10

Linked subjects

Computer Architecture Computer Networks Operating Systems 1

C17

Classify ICT system characteristics by functional purpose.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP10

Linked subjects

Computer Architecture Computer Networks

C18

Evaluate digital workflows against task constraints.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP12

Linked subjects

Robotic Process Automation

C19

Label chart elements for clear data interpretation.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP14

Linked subjects

Data Visualization and Analysis Web Design

C20

Select suitable image acquisition methods for a vision task.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CP16

Linked subjects

Deep Learning Image Processing Computer Vision

C21

Evaluate segmentation results against task criteria.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CP16

Linked subjects

Image Processing Computer Vision

C22

Classify statistical analysis requirements by project priority.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP18

Linked subjects

Probability Theory and Statistics Numerical Methods

C23

Evaluate statistical software results against expected outputs.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CP18

Linked subjects

Probability Theory and Statistics Python Tools For Machine Learning

C24

Classify data types for algorithmic processing.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP19

Linked subjects

Python Tools For Machine Learning Machine Learning

C25

Document sample selection procedures for data datasets.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP20

Linked subjects

Probability Theory and Statistics Machine Learning

C26

Document data quality defects in validation reports.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CP21

Linked subjects

Databases

C27

Identify functional dependencies in a table schema.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CP22

Linked subjects

Databases

C28

Identify corrupt records within structured datasets.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CP23

Linked subjects

Deep Learning

C29

Interpret reduced feature representations.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CP24

Linked subjects

Probability Theory and Statistics

C30

Select relevant scholarly sources for an AI research topic.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP27

Linked subjects

Methodology For Writing The Bsc Thesis Bsc Thesis Preparation

C31

Compare findings across scientific publications on an AI topic.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP27

Linked subjects

Methodology For Writing The Bsc Thesis Academic Writing

C32

Classify input data requirements for processing workflows.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CP28

Linked subjects

Programming 1

C33

Select a programming language for a data processing task.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CP28

Linked subjects

Programming 1

C34

Identify relevant variables in large data sets for pattern analysis.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CT1

Linked subjects

Probability Theory and Statistics Data Visualization and Analysis

C35

Interpret summary statistics for trend assessment.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CT1

Linked subjects

Data Visualization and Analysis

C36

Compare data distributions against expected model assumptions.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CT2

Linked subjects

Data Visualization and Analysis

C37

Interpret correlation results for variable relationships.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CT2

Linked subjects

Numerical Methods

C38

Evaluate concept originality against project goals.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CT3

Linked subjects

Artificial Intelligence

C39

Calculate matrix operations for model training verification.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CT4

Linked subjects

Linear Algebra and Differential Equation

C40

Derive numerical estimates for optimization parameters.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CT4

Linked subjects

Numerical Methods Linear Algebra and Differential Equation

C41

Classify current sources by relevance to project decisions.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CT5

Linked subjects

Artificial Intelligence Methods and Practices In Informatics

C42

Design data collection workflows for balanced sample acquisition.

1 competences | 2 subjects

create · 5/6

See details

Linked competences

CT6

Linked subjects

Ai Project Methods and Practices In Informatics

C43

Evaluate data collection outputs against quality criteria.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CT6

Linked subjects

Ai Project

C44

Classify datasets by relevance to project objectives.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CT7

Linked subjects

Data Visualization and Analysis

C45

Structure research findings into a concise technical report.

1 competences | 2 subjects

create · 5/6

See details

Linked competences

CT8

Linked subjects

Methodology For Writing The Bsc Thesis Academic Writing

C46

Explain analysis methods used in a research project.

1 competences | 2 subjects

understand · 2/6

See details

Linked competences

CT8

Linked subjects

Methodology For Writing The Bsc Thesis Academic Writing

C47

Assess operational workflows for restructuring opportunities.

1 competences | 0 subjects

analyze · 4/6

See details

Linked competences

CT9

Linked subjects

(no linked subjects)

C48

Identify process dependencies in operational workflows.

1 competences | 0 subjects

analyze · 4/6

See details

Linked competences

CT9

Linked subjects

(no linked subjects)

Skills

66 entries

Prioritize stakeholder requirements by project constraints.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP9

Linked subjects

Software Engineering

Document stakeholder requirements in a structured specification.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CP9

Linked subjects

Software Engineering

Prioritize technical requirements against project constraints.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP13

Linked subjects

Methods and Practices In Informatics

Validate technical requirements against stakeholder needs.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP13

Linked subjects

Methods and Practices In Informatics

Select a suitable process simulation tool.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP15

Linked subjects

Robotic Process Automation

Construct a flowchart for a process scenario.

1 competences | 2 subjects

create · 5/6

See details

Linked competences

CP15

Linked subjects

Methods and Practices In Informatics Planning Techniques For Robotics

Build a software prototype from defined functional requirements.

1 competences | 1 subjects

create · 5/6

See details

Linked competences

CP17

Linked subjects

Programming 1

Implement interface elements in a software prototype.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CP17

Linked subjects

Visual Programming

Select suitable library functions for a given programming task.

1 competences | 0 subjects

apply · 3/6

See details

Linked competences

CP25

Linked subjects

(no linked subjects)

A10

Integrate a library into an application build configuration.

1 competences | 0 subjects

apply · 3/6

See details

Linked competences

CP25

Linked subjects

(no linked subjects)

A11

Invoke library methods with correct parameters.

1 competences | 0 subjects

apply · 3/6

See details

Linked competences

CP25

Linked subjects

(no linked subjects)

A12

Configure CASE tool settings for project workflows.

1 competences | 0 subjects

apply · 3/6

See details

Linked competences

CP26

Linked subjects

(no linked subjects)

A13

Model software structure with CASE diagrams.

1 competences | 0 subjects

apply · 3/6

See details

Linked competences

CP26

Linked subjects

(no linked subjects)

A14

Explain ICT system boundaries using system interaction evidence.

1 competences | 3 subjects

understand · 2/6

See details

Linked competences

CP10

Linked subjects

Computer Architecture Computer Networks Operating Systems 1

A15

Compile datasets from distributed source files into one structured collection.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CP11

Linked subjects

Databases Python Tools For Machine Learning Machine Learning

A16

Merge related records into a unified dataset schema.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CP11

Linked subjects

Databases Python Tools For Machine Learning Machine Learning

A17

Organize data elements into a coherent training dataset.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CP11

Linked subjects

Databases Python Tools For Machine Learning Machine Learning

A18

Assemble labeled samples into a single evaluation dataset.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP11

Linked subjects

Python Tools For Machine Learning Machine Learning

A19

Select digital tools for solving project-specific conceptual problems.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP12

Linked subjects

Methods and Practices In Informatics Robotic Process Automation

A20

Prototype digital solutions for process improvement tasks.

1 competences | 2 subjects

create · 5/6

See details

Linked competences

CP12

Linked subjects

Ai Project Robotic Process Automation

A21

Select appropriate chart types for dataset characteristics.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP14

Linked subjects

Probability Theory and Statistics Data Visualization and Analysis

A22

Format visual hierarchy for presentation slides.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CP14

Linked subjects

Data Visualization and Analysis

A23

Preprocess image data for downstream vision models.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CP16

Linked subjects

Deep Learning Image Processing Computer Vision

A24

Design a statistical model for a defined analysis goal.

1 competences | 2 subjects

create · 5/6

See details

Linked competences

CP18

Linked subjects

Probability Theory and Statistics Numerical Methods

A25

Prototype a statistical algorithm in working code.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP18

Linked subjects

Probability Theory and Statistics Python Tools For Machine Learning

A26

Prepare datasets for machine learning workflows.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP19

Linked subjects

Python Tools For Machine Learning Machine Learning

A27

Transform raw data into structured features.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP19

Linked subjects

Python Tools For Machine Learning Machine Learning

A28

Select representative data samples for training datasets.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CP20

Linked subjects

Probability Theory and Statistics Python Tools For Machine Learning Machine Learning

A29

Evaluate sample quality against dataset criteria.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP20

Linked subjects

Probability Theory and Statistics Machine Learning

A30

Verify sample representativeness against population characteristics.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP20

Linked subjects

Probability Theory and Statistics Machine Learning

A31

Validate dataset records against predefined quality rules.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CP21

Linked subjects

Databases

A32

Detect missing values in structured datasets.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CP21

Linked subjects

Databases Python Tools For Machine Learning

A33

Assess dataset consistency across related fields.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CP21

Linked subjects

Databases

A34

Normalize relational tables to third normal form.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP22

Linked subjects

Databases Algorithms and Data Structures 2

A35

Detect redundancy in relational data structures.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CP22

Linked subjects

Databases

A36

Validate record structure against dataset guidelines.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP23

Linked subjects

Programming 1 Artificial Intelligence

A37

Correct invalid fields in dataset records.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP23

Linked subjects

Programming 1 Software Engineering

A38

Select the reduction method for a dataset.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP24

Linked subjects

Numerical Methods Python Tools For Machine Learning

A39

Prepare features for dimensionality reduction.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CP24

Linked subjects

Artificial Intelligence Deep Learning Neural Computing

A40

Assess publication credibility for an AI research topic.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CP27

Linked subjects

Methodology For Writing The Bsc Thesis Bsc Thesis Preparation

A41

Implement a data transformation routine from specified input.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CP28

Linked subjects

Programming 1

A42

Clean numerical data before statistical evaluation.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CT1

Linked subjects

Data Visualization and Analysis

A43

Compare data distributions across large samples for anomalies.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CT1

Linked subjects

Data Visualization and Analysis

A44

Calculate descriptive statistics for structured datasets.

1 competences | 3 subjects

apply · 3/6

See details

Linked competences

CT2

Linked subjects

Calculus Numerical Methods Linear Algebra and Differential Equation

A45

Generate original concept variants for AI solution features.

1 competences | 1 subjects

create · 5/6

See details

Linked competences

CT3

Linked subjects

Artificial Intelligence

A46

Combine diverse source ideas into novel visual concepts.

1 competences | 1 subjects

create · 5/6

See details

Linked competences

CT3

Linked subjects

Graphics and User Interfaces

A47

Refine concept sketches into implementable design directions.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CT3

Linked subjects

Graphics and User Interfaces Artificial Intelligence

A48

Compute statistical measures for experiment results.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CT4

Linked subjects

Numerical Methods

A49

Extract decision signals from current research findings.

1 competences | 2 subjects

analyze · 4/6

See details

Linked competences

CT5

Linked subjects

Artificial Intelligence Methods and Practices In Informatics

A50

Prioritize current evidence by project relevance.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CT5

Linked subjects

Artificial Intelligence Methods and Practices In Informatics

A51

Configure collection settings to reduce missing data.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CT6

Linked subjects

Ai Project Methods and Practices In Informatics

A52

Validate data quality against project requirements.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CT7

Linked subjects

Data Visualization and Analysis

A53

Present statistical results in appropriate charts.

1 competences | 1 subjects

create · 5/6

See details

Linked competences

CT7

Linked subjects

Data Visualization and Analysis

A54

Present analysis results to a technical audience.

1 competences | 2 subjects

responding · 2/5

See details

Linked competences

CT8

Linked subjects

Methodology For Writing The Bsc Thesis Academic Writing

A55

Interpret research results against project hypotheses.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CT8

Linked subjects

Methodology For Writing The Bsc Thesis Academic Writing

A56

develops, designs, and demonstrates complex software solutions using efficient algorithms and diverse programming paradigms.

1 competences | 5 subjects

Taxonomy not set

See details

Linked competences

CP1

Linked subjects

Algorithms and Data Structures 1 Visual Programming Algorithms and Data Structures 2 Game Programming and Virtual Reality Cognitive Robotics

A57

applies, evaluates, and proposes mathematical methods for modeling, simulating, and solving computing problems.

1 competences | 4 subjects

evaluate · 6/6

See details

Linked competences

CP2

Linked subjects

Calculus Numerical Methods Linear Algebra and Differential Equation Computational Geometry

A58

proposes, designs, and justifies the configuration, security, and optimization of IT infrastructures.

1 competences | 1 subjects

evaluate · 6/6

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Linked competences

CP3

Linked subjects

Security and Cryptography

A59

designs, implements, operates, and develops relational databases.

1 competences | 1 subjects

create · 5/6

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Linked competences

CP3

Linked subjects

Databases

A60

designs, builds, and develops databases and database systems.

1 competences | 1 subjects

create · 5/6

See details

Linked competences

CP4

Linked subjects

Databases

A61

designs, plans, builds, and develops scalable software applications and efficiently uses hardware and software resources.

1 competences | 0 subjects

create · 5/6

See details

Linked competences

CP5

Linked subjects

(no linked subjects)

A62

designs, implements, experiments with predictive models, and develops applications based on machine learning algorithms.

1 competences | 7 subjects

create · 5/6

See details

Linked competences

CP6

Linked subjects

Deep Learning Image Processing Computer Vision Cognitive Robotics Introduction To Neurotehnologies Human-ai Interaction Intelligent Systems

A63

estimates information security risks, proposes, solves, and tests IT security solutions.

1 competences | 1 subjects

Taxonomy not set

See details

Linked competences

CP7

Linked subjects

Security and Cryptography

A64

initiates, prepares, carries out, and proposes methods for developing complex IT projects.

1 competences | 2 subjects

Taxonomy not set

See details

Linked competences

CP8

Linked subjects

Practice Stage In Ai (112 H)Individual Project

A65

creates specific professional reports.

1 competences | 1 subjects

Taxonomy not set

See details

Linked competences

CP8

Linked subjects

Methodology For Writing The Bsc Thesis

A66

Evaluate process bottlenecks against technology capabilities.

1 competences | 0 subjects

evaluate · 6/6

See details

Linked competences

CT9

Linked subjects

(no linked subjects)

Responsibility

29 entries

Resolve stakeholder requirement disagreements through evidence-based comparison.

1 competences | 1 subjects

responding · 2/5

See details

Linked competences

CP9

Linked subjects

Software Engineering

Document technical requirements in a structured specification.

1 competences | 1 subjects

create · 5/6

See details

Linked competences

CP13

Linked subjects

Academic Writing

Assess prototype behavior against intended use cases.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP17

Linked subjects

Individual Project

Evaluate CASE outputs for maintenance quality.

1 competences | 0 subjects

evaluate · 6/6

See details

Linked competences

CP26

Linked subjects

(no linked subjects)

Document ICT system behavior using operational observations.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP10

Linked subjects

Computer Architecture Operating Systems 1

Adapt digital methods to resolve technical ambiguities.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP12

Linked subjects

Methods and Practices In Informatics Robotic Process Automation

Evaluate chart clarity against presentation goals.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CP14

Linked subjects

Data Visualization and Analysis Academic Writing

Configure detection parameters for image analysis tasks.

1 competences | 2 subjects

apply · 3/6

See details

Linked competences

CP16

Linked subjects

Image Processing Computer Vision

Evaluate data quality against processing requirements.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP19

Linked subjects

Machine Learning

R10

Verify schema consistency after normalization changes.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP22

Linked subjects

Databases

R11

Verify dataset integrity after cleansing actions.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP23

Linked subjects

Deep Learning

R12

Evaluate retained information after reduction.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP24

Linked subjects

Deep Learning

R13

Compose a structured literature summary for an AI topic.

1 competences | 2 subjects

create · 5/6

See details

Linked competences

CP27

Linked subjects

Methodology For Writing The Bsc Thesis Academic Writing

R14

Evaluate program output against expected input conditions.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CP28

Linked subjects

Programming 1

R15

Assess machine learning outputs against validation data.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CT2

Linked subjects

Artificial Intelligence Deep Learning

R16

Validate calculation outputs against problem constraints.

1 competences | 1 subjects

evaluate · 6/6

See details

Linked competences

CT4

Linked subjects

Numerical Methods

R17

Compare current customer needs against available evidence.

1 competences | 2 subjects

evaluate · 6/6

See details

Linked competences

CT5

Linked subjects

Artificial Intelligence Professional Counseling and Career Guidance

R18

Monitor collection system performance for sampling bias.

1 competences | 1 subjects

analyze · 4/6

See details

Linked competences

CT6

Linked subjects

Ai Project

R19

Store datasets using approved organisational procedures.

1 competences | 1 subjects

apply · 3/6

See details

Linked competences

CT7

Linked subjects

Software Engineering

R20

coordinates technical teams for the development of software applications, making responsible decisions regarding their optimization and integration

1 competences | 1 subjects

organization · 4/5

See details

Linked competences

CP1

Linked subjects

Practice Stage In Ai (112 H)

R21

develops interdisciplinary solutions by integrating mathematics with related fields and collaborating efficiently with specialized teams.

1 competences | 1 subjects

Taxonomy not set

See details

Linked competences

CP2

Linked subjects

Linear Algebra and Differential Equation

R22

ethically and responsibly builds secure and scalable IT solutions, collaborating with specialists from related fields.

1 competences | 0 subjects

create · 5/6

See details

Linked competences

CP3

Linked subjects

(no linked subjects)

R23

designs and manages the activities required for the development of a database system.

1 competences | 0 subjects

create · 5/6

See details

Linked competences

CP4

Linked subjects

(no linked subjects)

R24

produces software and continuously adapts it to new technologies and market requirements.

1 competences | 3 subjects

Taxonomy not set

See details

Linked competences

CP5

Linked subjects

Ai Project Practice Stage In Ai (112 H)Individual Project

R25

applies an ethical framework in the use of AI, with responsibility for the social impact of the proposed solutions.

1 competences | 5 subjects

apply · 3/6

See details

Linked competences

CP6

Linked subjects

Artificial Intelligence Ai Project Cognitive Robotics Human-ai Interaction Ethics and Academic Integrity

R26

knows and implements information security requirements.

1 competences | 2 subjects

Taxonomy not set

See details

Linked competences

CP7

Linked subjects

Computer Networks Security and Cryptography

R27

develops a collaborative environment and takes responsibility for the successful and timely delivery of projects according to requirements.

1 competences | 3 subjects

Taxonomy not set

See details

Linked competences

CP8

Linked subjects

Practice Stage In Ai (112 H)Individual Project Entrepreneurship Skills

R28

organizes technical teams and manages the lifecycle of software projects.

1 competences | 3 subjects

organization · 4/5

See details

Linked competences

CP8

Linked subjects

Practice Stage In Ai (112 H)Individual Project Entrepreneurship Skills

R29

Prioritize restructuring options by business impact.

1 competences | 0 subjects

evaluate · 6/6

See details

Linked competences

CT9

Linked subjects

(no linked subjects)

Curriculum

The semester structure keeps the curriculum grouped by mandatory, elective, and optional subjects. Expand a row to inspect hours, subject type, linked learning outcomes, and any public syllabus.

Semester 1

Credits: 32 | Total hours/week: 25

Mandatory subjects

Algorithms and Data Structures 1

6 credits

Lecture 2 Seminar 2 Lab 0 Practical 0 Kind DF

C1 C8 A56

Programming 1

6 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

C1 C11 C12 C13 C32 C33 A7 A36 A37 A41 R14

Logic For Computer Science

5 credits

Lecture 2 Seminar 2 Lab 0 Practical 0 Kind DF

C1 C2

Fundamentals Of Mathematics

5 credits

Lecture 2 Seminar 2 Lab 0 Practical 0 Kind DF

Computer Architecture

5 credits

Lecture 2 Seminar 2 Lab 0 Practical 0 Kind DF

C1 C16 C17 A14 R5

Professional Counseling and Career Guidance

1 credits

Lecture 0 Seminar 1 Lab 0 Practical 0 Kind DC

R17

Ethics and Academic Integrity

1 credits

Lecture 1 Seminar 0 Lab 0 Practical 0 Kind DC

R25

Elective subjects

2 credits

Foreign Lanuage 1 - Spanish

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 1 - French

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 1 - German

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

1 credits

Physical Education 1

Lecture 0 Seminar 0 Lab 1 Practical 0 Kind DC

(no linked learning outcomes)

Optional subjects

Volunteering 1 (60h)

2 credits

Lecture 0 Seminar 0 Lab 0 Practical 4 Kind DC

(no linked learning outcomes)

Introduction To Programming

2 credits

Lecture 1 Seminar 0 Lab 2 Practical 0 Kind DS

(no linked learning outcomes)

Competitive Programming 1

2 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DS

(no linked learning outcomes)

Semester 2

Credits: 31 | Total hours/week: 26

Mandatory subjects

Algorithms and Data Structures 2

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

A34 A56

Formal Languages and Automata Theory

5 credits

Lecture 2 Seminar 2 Lab 0 Practical 0 Kind DF

Calculus

5 credits

Lecture 2 Seminar 2 Lab 0 Practical 0 Kind DF

C2 A44 A57

Python Tools For Machine Learning

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C23 C24 A15 A16 A17 A18 A25 A26 A27 A28 A32 A38

Methods and Practices In Informatics

3 credits

Lecture 2 Seminar 0 Lab 1 Practical 0 Kind DS

C9 C10 C41 C42 A3 A4 A6 A19 A49 A50 A51 R6

Academic Writing

1 credits

Lecture 0 Seminar 1 Lab 0 Practical 0 Kind DC

C31 C45 C46 A54 A55 R2 R7 R13

Elective subjects

4 credits

Web Design

Lecture 1 Seminar 0 Lab 2 Practical 0 Kind DS

C19

Visual Programming

Lecture 1 Seminar 0 Lab 2 Practical 0 Kind DS

A8 A56

2 credits

Foreign Lanuage 2 - Spanish

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 2 - French

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 2 - German

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

1 credits

Physical Education 2

Lecture 0 Seminar 0 Lab 1 Practical 0 Kind DC

(no linked learning outcomes)

Optional subjects

It Placement

4 credits

Lecture 0 Seminar 0 Lab 0 Practical 8 Kind DS

(no linked learning outcomes)

Volunteering 2 (60h)

2 credits

Lecture 0 Seminar 0 Lab 0 Practical 4 Kind DC

(no linked learning outcomes)

Competitive Programming 2

2 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DS

(no linked learning outcomes)

Programming Project

2 credits

Lecture 0 Seminar 0 Lab 1 Practical 0 Kind DS

Semester 3

Credits: 31 | Total hours/week: 26

Mandatory subjects

Graph Theory and Combinatorics

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

Operating Systems 1

4 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

C3 C7 C16 A14 R5

Databases

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

C4 C26 C27 A15 A16 A17 A31 A32 A33 A34 A35 A59 A60 R10

Probability Theory and Statistics

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

C2 C22 C23 C25 C29 C34 A21 A24 A25 A28 A29 A30

Linear Algebra and Differential Equation

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C39 C40 A44 A57 R21

Individual Project

2 credits

Lecture 0 Seminar 0 Lab 1 Practical 0 Kind DS

A64 R3 R24 R27 R28

Entrepreneurship Skills

2 credits

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

R27 R28

Elective subjects

2 credits

Foreign Lanuage 3 - Spanish

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 3 - French

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 3 - German

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

1 credits

Physical Education 3

Lecture 0 Seminar 0 Lab 1 Practical 0 Kind DC

(no linked learning outcomes)

Optional subjects

Volunteering 3 (60h)

2 credits

Lecture 0 Seminar 0 Lab 0 Practical 4 Kind DC

(no linked learning outcomes)

Competitive Programming 3

2 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DS

(no linked learning outcomes)

Semester 4

Credits: 31 | Total hours/week: 34

Mandatory subjects

Software Engineering

4 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C4 C5 C8 A1 A2 A37 R1 R19

Artificial Intelligence

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

C6 C38 C41 A36 A39 A45 A47 A49 A50 R15 R17 R25

Numerical Methods

4 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C2 C22 C37 C40 A24 A38 A44 A48 A57 R16

Ai Project

2 credits

Lecture 0 Seminar 0 Lab 1 Practical 0 Kind DS

C8 C42 C43 A20 A51 R18 R24 R25

Computational Geometry

3 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

A57

Practice Stage In Ai (112 H)

4 credits

Lecture 0 Seminar 0 Lab 0 Practical 8 Kind DS

A64 R20 R24 R27 R28

Elective subjects

4 credits

Security and Cryptography

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C7 A58 A63 R26

Graphics and User Interfaces

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C5 A46 A47

2 credits

Foreign Lanuage 4 - Spanish

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 4 - French

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

Foreign Lanuage 4 - German

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

2 credits

Optional Complementary Discipline That Forms Transversal Skills (dct) 1

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

1 credits

Physical Education 4

Lecture 0 Seminar 0 Lab 1 Practical 0 Kind DC

(no linked learning outcomes)

Optional subjects

Competitive Programming 4

2 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DS

(no linked learning outcomes)

Volunteering 4 (60h)

2 credits

Lecture 0 Seminar 0 Lab 0 Practical 4 Kind DC

(no linked learning outcomes)

Entrepreneurship Skills – Practical Applications

2 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DC

(no linked learning outcomes)

Semester 5

Credits: 30 | Total hours/week: 24

Mandatory subjects

Machine Learning

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C24 C25 A15 A16 A17 A18 A26 A27 A28 A29 A30 R9

Methodology For Writing The Bsc Thesis

4 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DS

C30 C31 C45 C46 A40 A54 A55 A65 R13

Data Visualization and Analysis

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C19 C34 C35 C36 C44 A21 A22 A42 A43 A52 A53 R7

Image Processing

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C20 C21 A23 A62 R8

Neural Computing

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

A39

Elective subjects

2 credits

Optional Complementary Discipline That Forms Transversal Skills (dct) 2

Lecture 1 Seminar 1 Lab 0 Practical 0 Kind DC

(no linked learning outcomes)

4 credits

Human-ai Interaction

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

A62 R25

Robotic Process Automation

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C11 C12 C18 A5 A19 A20 R6

Optional subjects

Volunteering 5 (60 H)

2 credits

Lecture 0 Seminar 0 Lab 0 Practical 4 Kind DC

(no linked learning outcomes)

Competitive Programming 5

2 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DS

(no linked learning outcomes)

Semester 6

Credits: 30 | Total hours/week: 28

Mandatory subjects

Computer Networks

5 credits

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DF

C3 C7 C16 C17 A14 R26

Bsc Thesis Preparation

5 credits

Lecture 0 Seminar 0 Lab 3 Practical 5 Kind DS

C30 A40

Elective subjects

5 credits

Planning Techniques For Robotics

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C11 A6

Natural Language Processing

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

5 credits

Deep Learning

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C6 C20 C28 A23 A39 A62 R11 R12 R15

Data Compression Algorithms

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

5 credits

Computer Vision

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

C20 C21 A23 A62 R8

Game Programming and Virtual Reality

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

A56

5 credits

Intelligent Systems

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

A62

Cognitive Robotics

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

A56 A62 R25

Introduction To Neurotehnologies

Lecture 2 Seminar 0 Lab 2 Practical 0 Kind DS

A62

Optional subjects

Competitive Programming

2 credits

Lecture 0 Seminar 0 Lab 2 Practical 0 Kind DS

(no linked learning outcomes)

Volunteering 6 (60 H)

2 credits

Lecture 0 Seminar 0 Lab 0 Practical 4 Kind DC

(no linked learning outcomes)