AI (2026 - 2029)
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
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mathematical competence and competence in science, technology and engineering
CC2
digital competence
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digital competence
CC3
personal, social and learning to learn competence
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personal, social and learning to learn competence
CC4
entrepreneurship competence
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entrepreneurship competence
Professional competences
28 entries
CP1
ARACIS Informatică CPS 1.1
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ARACIS Informatică CPS 1.1
CP2
ARACIS Informatică CPS 1.2
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ARACIS Informatică CPS 1.2
CP3
ARACIS Informatică CPS 1.3
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ARACIS Informatică CPS 1.3
CP4
ARACIS Informatică CPS 1.4
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ARACIS Informatică CPS 1.4
CP5
ARACIS Informatică CPS 1.5
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ARACIS Informatică CPS 1.5
CP6
ARACIS Informatică CPS 1.6
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ARACIS Informatică CPS 1.6
CP7
ARACIS Informatică CPS 1.7
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ARACIS Informatică CPS 1.7
CP8
ARACIS Informatică CPS 1.8
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ARACIS Informatică CPS 1.8
CP9
analyse business requirements
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analyse business requirements
CP10
apply ICT systems theory
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apply ICT systems theory
CP11
create data sets
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create data sets
CP12
creatively use digital technologies
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creatively use digital technologies
CP13
define technical requirements
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define technical requirements
CP14
deliver visual presentation of data
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deliver visual presentation of data
CP15
design process
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design process
CP16
develop computer vision system
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develop computer vision system
CP17
develop software prototype
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develop software prototype
CP18
develop statistical software
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develop statistical software
CP19
establish data processes
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establish data processes
CP20
handle data samples
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handle data samples
CP21
implement data quality processes
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implement data quality processes
CP22
normalise data
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normalise data
CP23
perform data cleansing
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perform data cleansing
CP24
perform dimensionality reduction
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perform dimensionality reduction
CP25
use software libraries
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use software libraries
CP26
utilise computer-aided software engineering tools
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utilise computer-aided software engineering tools
CP27
conduct literature research
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conduct literature research
CP28
develop data processing applications
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develop data processing applications
Transversal personal competences
7 entries
CT1
analyse big data
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analyse big data
CT2
apply statistical analysis techniques
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apply statistical analysis techniques
CT3
develop creative ideas
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develop creative ideas
CT4
execute analytical mathematical calculations
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execute analytical mathematical calculations
CT5
interpret current data
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interpret current data
CT6
manage data collection systems
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manage data collection systems
CT7
use data processing techniques
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use data processing techniques
Transversal interpersonal competences
1 entries
CT8
report analysis results
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report analysis results
Transversal global citizenship competences
1 entries
CT9
identify processes for re-engineering
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identify processes for re-engineering
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
C1
identifies, explains, and justifies fundamental concepts of data structures, algorithms, and programming paradigms, as well as computer architecture.
evaluate · 6/6
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identifies, explains, and justifies fundamental concepts of data structures, algorithms, and programming paradigms, as well as computer architecture.
C2
selects, explains, and specifies the mathematical foundations applied in computer science, including formal logic, algebra, probability, and statistics.
understand · 2/6
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selects, explains, and specifies the mathematical foundations applied in computer science, including formal logic, algebra, probability, and statistics.
C3
describes, identifies, and explains the operation and administration of computer networks and operating systems.
understand · 2/6
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describes, identifies, and explains the operation and administration of computer networks and operating systems.
C4
identifies, selects, and justifies principles and design models of databases.
evaluate · 6/6
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identifies, selects, and justifies principles and design models of databases.
C5
selects, describes, analyzes, and explains modern programming paradigms, including functional, object-oriented, and parallel programming, using current languages and frameworks.
analyze · 4/6
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selects, describes, analyzes, and explains modern programming paradigms, including functional, object-oriented, and parallel programming, using current languages and frameworks.
C6
identifies, compares, recognizes, and describes advanced concepts and techniques in the fields of artificial intelligence, machine learning, and natural language processing.
analyze · 4/6
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identifies, compares, recognizes, and describes advanced concepts and techniques in the fields of artificial intelligence, machine learning, and natural language processing.
C7
names, recognizes, and justifies information security techniques, both software and hardware.
Taxonomy not set
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names, recognizes, and justifies information security techniques, both software and hardware.
C8
names, provides examples, concludes, specifies, recognizes, and critically justifies methods for designing and managing complex IT projects, using modern strategies.
Taxonomy not set
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names, provides examples, concludes, specifies, recognizes, and critically justifies methods for designing and managing complex IT projects, using modern strategies.
C9
Identify stakeholder requirements conflicts in business briefs.
analyze · 4/6
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Identify stakeholder requirements conflicts in business briefs.
C10
Translate stakeholder needs into measurable technical specifications.
create · 5/6
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Translate stakeholder needs into measurable technical specifications.
C11
Identify workflow steps for a process scenario.
understand · 2/6
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Identify workflow steps for a process scenario.
C12
Map resource needs for a process model.
apply · 3/6
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Map resource needs for a process model.
C13
Select core features for a software prototype scope.
evaluate · 6/6
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Select core features for a software prototype scope.
C14
Evaluate library output against expected program behavior.
evaluate · 6/6
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Evaluate library output against expected program behavior.
C15
Select suitable CASE tools for a software project.
apply · 3/6
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Select suitable CASE tools for a software project.
C16
Identify ICT system components and their functional relationships.
analyze · 4/6
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Identify ICT system components and their functional relationships.
C17
Classify ICT system characteristics by functional purpose.
analyze · 4/6
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Classify ICT system characteristics by functional purpose.
C18
Evaluate digital workflows against task constraints.
evaluate · 6/6
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Evaluate digital workflows against task constraints.
C19
Label chart elements for clear data interpretation.
apply · 3/6
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Label chart elements for clear data interpretation.
C20
Select suitable image acquisition methods for a vision task.
apply · 3/6
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Select suitable image acquisition methods for a vision task.
C21
Evaluate segmentation results against task criteria.
evaluate · 6/6
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Evaluate segmentation results against task criteria.
C22
Classify statistical analysis requirements by project priority.
analyze · 4/6
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Classify statistical analysis requirements by project priority.
C23
Evaluate statistical software results against expected outputs.
evaluate · 6/6
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Evaluate statistical software results against expected outputs.
C24
Classify data types for algorithmic processing.
apply · 3/6
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Classify data types for algorithmic processing.
C25
Document sample selection procedures for data datasets.
apply · 3/6
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Document sample selection procedures for data datasets.
C26
Document data quality defects in validation reports.
apply · 3/6
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Document data quality defects in validation reports.
C27
Identify functional dependencies in a table schema.
analyze · 4/6
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Identify functional dependencies in a table schema.
C28
Identify corrupt records within structured datasets.
analyze · 4/6
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Identify corrupt records within structured datasets.
C29
Interpret reduced feature representations.
analyze · 4/6
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Interpret reduced feature representations.
C30
Select relevant scholarly sources for an AI research topic.
apply · 3/6
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Select relevant scholarly sources for an AI research topic.
C31
Compare findings across scientific publications on an AI topic.
analyze · 4/6
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Compare findings across scientific publications on an AI topic.
C32
Classify input data requirements for processing workflows.
analyze · 4/6
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Classify input data requirements for processing workflows.
C33
Select a programming language for a data processing task.
apply · 3/6
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Select a programming language for a data processing task.
C34
Identify relevant variables in large data sets for pattern analysis.
analyze · 4/6
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Identify relevant variables in large data sets for pattern analysis.
C35
Interpret summary statistics for trend assessment.
evaluate · 6/6
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Interpret summary statistics for trend assessment.
C36
Compare data distributions against expected model assumptions.
analyze · 4/6
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Compare data distributions against expected model assumptions.
C37
Interpret correlation results for variable relationships.
analyze · 4/6
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Interpret correlation results for variable relationships.
C38
Evaluate concept originality against project goals.
evaluate · 6/6
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Evaluate concept originality against project goals.
C39
Calculate matrix operations for model training verification.
apply · 3/6
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Calculate matrix operations for model training verification.
C40
Derive numerical estimates for optimization parameters.
analyze · 4/6
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Derive numerical estimates for optimization parameters.
C41
Classify current sources by relevance to project decisions.
analyze · 4/6
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Classify current sources by relevance to project decisions.
C42
Design data collection workflows for balanced sample acquisition.
create · 5/6
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Design data collection workflows for balanced sample acquisition.
C43
Evaluate data collection outputs against quality criteria.
evaluate · 6/6
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Evaluate data collection outputs against quality criteria.
C44
Classify datasets by relevance to project objectives.
analyze · 4/6
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Classify datasets by relevance to project objectives.
C45
Structure research findings into a concise technical report.
create · 5/6
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Structure research findings into a concise technical report.
C46
Explain analysis methods used in a research project.
understand · 2/6
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Explain analysis methods used in a research project.
C47
Assess operational workflows for restructuring opportunities.
analyze · 4/6
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Assess operational workflows for restructuring opportunities.
C48
Identify process dependencies in operational workflows.
analyze · 4/6
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Identify process dependencies in operational workflows.
Skills
66 entries
A1
Prioritize stakeholder requirements by project constraints.
evaluate · 6/6
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Prioritize stakeholder requirements by project constraints.
A2
Document stakeholder requirements in a structured specification.
apply · 3/6
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Document stakeholder requirements in a structured specification.
A3
Prioritize technical requirements against project constraints.
evaluate · 6/6
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Prioritize technical requirements against project constraints.
A4
Validate technical requirements against stakeholder needs.
evaluate · 6/6
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Validate technical requirements against stakeholder needs.
A5
Select a suitable process simulation tool.
evaluate · 6/6
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Select a suitable process simulation tool.
A6
Construct a flowchart for a process scenario.
create · 5/6
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Construct a flowchart for a process scenario.
A7
Build a software prototype from defined functional requirements.
create · 5/6
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Build a software prototype from defined functional requirements.
A8
Implement interface elements in a software prototype.
apply · 3/6
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Implement interface elements in a software prototype.
A9
Select suitable library functions for a given programming task.
apply · 3/6
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Select suitable library functions for a given programming task.
A10
Integrate a library into an application build configuration.
apply · 3/6
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Integrate a library into an application build configuration.
A11
Invoke library methods with correct parameters.
apply · 3/6
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Invoke library methods with correct parameters.
A12
Configure CASE tool settings for project workflows.
apply · 3/6
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Configure CASE tool settings for project workflows.
A13
Model software structure with CASE diagrams.
apply · 3/6
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Model software structure with CASE diagrams.
A14
Explain ICT system boundaries using system interaction evidence.
understand · 2/6
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Explain ICT system boundaries using system interaction evidence.
A15
Compile datasets from distributed source files into one structured collection.
apply · 3/6
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Compile datasets from distributed source files into one structured collection.
A16
Merge related records into a unified dataset schema.
apply · 3/6
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Merge related records into a unified dataset schema.
A17
Organize data elements into a coherent training dataset.
apply · 3/6
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Organize data elements into a coherent training dataset.
A18
Assemble labeled samples into a single evaluation dataset.
apply · 3/6
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Assemble labeled samples into a single evaluation dataset.
A19
Select digital tools for solving project-specific conceptual problems.
apply · 3/6
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Select digital tools for solving project-specific conceptual problems.
A20
Prototype digital solutions for process improvement tasks.
create · 5/6
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Prototype digital solutions for process improvement tasks.
A21
Select appropriate chart types for dataset characteristics.
apply · 3/6
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Select appropriate chart types for dataset characteristics.
A22
Format visual hierarchy for presentation slides.
apply · 3/6
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Format visual hierarchy for presentation slides.
A23
Preprocess image data for downstream vision models.
apply · 3/6
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Preprocess image data for downstream vision models.
A24
Design a statistical model for a defined analysis goal.
create · 5/6
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Design a statistical model for a defined analysis goal.
A25
Prototype a statistical algorithm in working code.
apply · 3/6
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Prototype a statistical algorithm in working code.
A26
Prepare datasets for machine learning workflows.
apply · 3/6
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Prepare datasets for machine learning workflows.
A27
Transform raw data into structured features.
analyze · 4/6
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Transform raw data into structured features.
A28
Select representative data samples for training datasets.
apply · 3/6
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Select representative data samples for training datasets.
A29
Evaluate sample quality against dataset criteria.
analyze · 4/6
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Evaluate sample quality against dataset criteria.
A30
Verify sample representativeness against population characteristics.
analyze · 4/6
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Verify sample representativeness against population characteristics.
A31
Validate dataset records against predefined quality rules.
apply · 3/6
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Validate dataset records against predefined quality rules.
A32
Detect missing values in structured datasets.
analyze · 4/6
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Detect missing values in structured datasets.
A33
Assess dataset consistency across related fields.
analyze · 4/6
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Assess dataset consistency across related fields.
A34
Normalize relational tables to third normal form.
apply · 3/6
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Normalize relational tables to third normal form.
A35
Detect redundancy in relational data structures.
analyze · 4/6
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Detect redundancy in relational data structures.
A36
Validate record structure against dataset guidelines.
apply · 3/6
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Validate record structure against dataset guidelines.
A37
Correct invalid fields in dataset records.
apply · 3/6
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Correct invalid fields in dataset records.
A38
Select the reduction method for a dataset.
apply · 3/6
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Select the reduction method for a dataset.
A39
Prepare features for dimensionality reduction.
apply · 3/6
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Prepare features for dimensionality reduction.
A40
Assess publication credibility for an AI research topic.
evaluate · 6/6
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Assess publication credibility for an AI research topic.
A41
Implement a data transformation routine from specified input.
apply · 3/6
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Implement a data transformation routine from specified input.
A42
Clean numerical data before statistical evaluation.
apply · 3/6
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Clean numerical data before statistical evaluation.
A43
Compare data distributions across large samples for anomalies.
analyze · 4/6
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Compare data distributions across large samples for anomalies.
A44
Calculate descriptive statistics for structured datasets.
apply · 3/6
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Calculate descriptive statistics for structured datasets.
A45
Generate original concept variants for AI solution features.
create · 5/6
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Generate original concept variants for AI solution features.
A46
Combine diverse source ideas into novel visual concepts.
create · 5/6
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Combine diverse source ideas into novel visual concepts.
A47
Refine concept sketches into implementable design directions.
apply · 3/6
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Refine concept sketches into implementable design directions.
A48
Compute statistical measures for experiment results.
apply · 3/6
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Compute statistical measures for experiment results.
A49
Extract decision signals from current research findings.
analyze · 4/6
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Extract decision signals from current research findings.
A50
Prioritize current evidence by project relevance.
evaluate · 6/6
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Prioritize current evidence by project relevance.
A51
Configure collection settings to reduce missing data.
apply · 3/6
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Configure collection settings to reduce missing data.
A52
Validate data quality against project requirements.
evaluate · 6/6
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Validate data quality against project requirements.
A53
Present statistical results in appropriate charts.
create · 5/6
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Present statistical results in appropriate charts.
A54
Present analysis results to a technical audience.
responding · 2/5
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Present analysis results to a technical audience.
A55
Interpret research results against project hypotheses.
evaluate · 6/6
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Interpret research results against project hypotheses.
A56
develops, designs, and demonstrates complex software solutions using efficient algorithms and diverse programming paradigms.
Taxonomy not set
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develops, designs, and demonstrates complex software solutions using efficient algorithms and diverse programming paradigms.
A57
applies, evaluates, and proposes mathematical methods for modeling, simulating, and solving computing problems.
evaluate · 6/6
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applies, evaluates, and proposes mathematical methods for modeling, simulating, and solving computing problems.
A58
proposes, designs, and justifies the configuration, security, and optimization of IT infrastructures.
evaluate · 6/6
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proposes, designs, and justifies the configuration, security, and optimization of IT infrastructures.
A59
designs, implements, operates, and develops relational databases.
create · 5/6
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designs, implements, operates, and develops relational databases.
A60
designs, builds, and develops databases and database systems.
create · 5/6
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designs, builds, and develops databases and database systems.
A61
designs, plans, builds, and develops scalable software applications and efficiently uses hardware and software resources.
create · 5/6
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designs, plans, builds, and develops scalable software applications and efficiently uses hardware and software resources.
A62
designs, implements, experiments with predictive models, and develops applications based on machine learning algorithms.
create · 5/6
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designs, implements, experiments with predictive models, and develops applications based on machine learning algorithms.
A63
estimates information security risks, proposes, solves, and tests IT security solutions.
Taxonomy not set
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estimates information security risks, proposes, solves, and tests IT security solutions.
A64
initiates, prepares, carries out, and proposes methods for developing complex IT projects.
Taxonomy not set
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initiates, prepares, carries out, and proposes methods for developing complex IT projects.
A65
creates specific professional reports.
Taxonomy not set
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creates specific professional reports.
A66
Evaluate process bottlenecks against technology capabilities.
evaluate · 6/6
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Evaluate process bottlenecks against technology capabilities.
Responsibility
29 entries
R1
Resolve stakeholder requirement disagreements through evidence-based comparison.
responding · 2/5
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Resolve stakeholder requirement disagreements through evidence-based comparison.
R2
Document technical requirements in a structured specification.
create · 5/6
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Document technical requirements in a structured specification.
R3
Assess prototype behavior against intended use cases.
evaluate · 6/6
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Assess prototype behavior against intended use cases.
R4
Evaluate CASE outputs for maintenance quality.
evaluate · 6/6
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Evaluate CASE outputs for maintenance quality.
R5
Document ICT system behavior using operational observations.
apply · 3/6
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Document ICT system behavior using operational observations.
R6
Adapt digital methods to resolve technical ambiguities.
apply · 3/6
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Adapt digital methods to resolve technical ambiguities.
R7
Evaluate chart clarity against presentation goals.
evaluate · 6/6
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Evaluate chart clarity against presentation goals.
R8
Configure detection parameters for image analysis tasks.
apply · 3/6
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Configure detection parameters for image analysis tasks.
R9
Evaluate data quality against processing requirements.
evaluate · 6/6
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Evaluate data quality against processing requirements.
R10
Verify schema consistency after normalization changes.
evaluate · 6/6
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Verify schema consistency after normalization changes.
R11
Verify dataset integrity after cleansing actions.
evaluate · 6/6
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Verify dataset integrity after cleansing actions.
R12
Evaluate retained information after reduction.
evaluate · 6/6
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Evaluate retained information after reduction.
R13
Compose a structured literature summary for an AI topic.
create · 5/6
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Compose a structured literature summary for an AI topic.
R14
Evaluate program output against expected input conditions.
evaluate · 6/6
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Evaluate program output against expected input conditions.
R15
Assess machine learning outputs against validation data.
evaluate · 6/6
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Assess machine learning outputs against validation data.
R16
Validate calculation outputs against problem constraints.
evaluate · 6/6
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Validate calculation outputs against problem constraints.
R17
Compare current customer needs against available evidence.
evaluate · 6/6
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Compare current customer needs against available evidence.
R18
Monitor collection system performance for sampling bias.
analyze · 4/6
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Monitor collection system performance for sampling bias.
R19
Store datasets using approved organisational procedures.
apply · 3/6
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Store datasets using approved organisational procedures.
R20
coordinates technical teams for the development of software applications, making responsible decisions regarding their optimization and integration
organization · 4/5
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coordinates technical teams for the development of software applications, making responsible decisions regarding their optimization and integration
R21
develops interdisciplinary solutions by integrating mathematics with related fields and collaborating efficiently with specialized teams.
Taxonomy not set
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develops interdisciplinary solutions by integrating mathematics with related fields and collaborating efficiently with specialized teams.
R22
ethically and responsibly builds secure and scalable IT solutions, collaborating with specialists from related fields.
create · 5/6
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ethically and responsibly builds secure and scalable IT solutions, collaborating with specialists from related fields.
R23
designs and manages the activities required for the development of a database system.
create · 5/6
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designs and manages the activities required for the development of a database system.
R24
produces software and continuously adapts it to new technologies and market requirements.
Taxonomy not set
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produces software and continuously adapts it to new technologies and market requirements.
R25
applies an ethical framework in the use of AI, with responsibility for the social impact of the proposed solutions.
apply · 3/6
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applies an ethical framework in the use of AI, with responsibility for the social impact of the proposed solutions.
R26
knows and implements information security requirements.
Taxonomy not set
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knows and implements information security requirements.
R27
develops a collaborative environment and takes responsibility for the successful and timely delivery of projects according to requirements.
Taxonomy not set
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develops a collaborative environment and takes responsibility for the successful and timely delivery of projects according to requirements.
R28
organizes technical teams and manages the lifecycle of software projects.
organization · 4/5
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organizes technical teams and manages the lifecycle of software projects.
R29
Prioritize restructuring options by business impact.
evaluate · 6/6
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Prioritize restructuring options by business impact.
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.