Artificial Intelligence and Distributed Computing

cu predare în limba engleză

Planurile de învățământ aferente specializării de master

An universitar 2026–2027

Plan de învățământ – anul I

Promoția 2026–2028

Plan de învățământ – anul II

Promoția 2025–2027

2 ani

Durata programului

120 ECTS

Credite de studiu

Engleză

Limba de predare

Cu frecvență

Forma de învățământ

Alege promoția. Anul I și anul II indică anul de studiu în 2026–2027; fiecare opțiune afișează planul complet al promoției.

Plan complet · Promoția 2026–2028

Planul de învățământ pentru toate cele 4 semestre ale programului · 120 ECTS.

Misiunea programului de studii

Misiunea principală a programului de studii universitare de masterat Artificial Intelligence and Distributed Computing este de a asigura obținerea unor competențe specifice desfășurării de activități de cercetare fundamentală și aplicativă în domeniul Informaticii, orientată cu precădere înspre domenii de actualitate cum sunt inteligența artificială, calculul distribuit și de înaltă performanță, precum și progrese din domeniul teoriei calculului. Competențele dobândite vor permite absolvenților programului de studii universitare de masterat să urmeze ciclul de studii universitare de doctorat sau să își desfășoare activitate în institute de cercetare și departamente de cercetare-dezvoltare în domeniul IT.

Durată: 2 ani   |   Credite: 120 ECTS
Limba de predare: engleză   |   Forma de învățământ: cu frecvență
Tipul programului: master de cercetare

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Competențe-cheie · 3
  • CC1. mathematical competence and competence in science, technology and engineering
  • CC2. digital competence
  • CC3. personal, social and learning to learn competence
Competențe profesionale · 43
  • CP1. analyse business requirements – Study clients' needs and expectations for a product or service in order to identify and resolve inconsistencies and possible disagreements of involved stakeholders.
  • CP2. apply for research funding – Identify key relevant funding sources and prepare research grant application in order to obtain funds and grants. Write research proposals.
  • CP3. apply ICT systems theory – Implement principles of ICT systems theory in order to explain and document system characteristics that can be applied universally to other systems
  • CP4. apply research ethics and scientific integrity principles in research activities – Apply fundamental ethical principles and legislation to scientific research, including issues of research integrity. Perform, review, or report research avoiding misconducts such as fabrication, falsification, and plagiarism.
  • CP5. apply reverse engineering – Use techniques to extract information or disassemble an ICT component, software or system in order to analyse, correct and reassemble or reproduce it.
  • CP6. apply statistical analysis techniques – 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.
  • CP7. communicate with a non-scientific audience – Communicate about scientific findings to a non-scientific audience, including the general public. Tailor the communication of scientific concepts, debates, findings to the audience, using a variety of methods for different target groups, including visual presentations.
  • CP8. conduct literature research – Conduct a comprehensive and systematic research of information and publications on a specific literature topic. Present a comparative evaluative literature summary.
  • CP9. conduct quantitative research – Execute a systematic empirical investigation of observable phenomena via statistical, mathematical or computational techniques.
  • CP10. conduct research across disciplines – Work and use research findings and data across disciplinary and/or functional boundaries.
  • CP11. conduct research interview – Use professional researching and interviewing methods and techniques to gather relevant data, facts or information, to gain new insights and to fully comprehend the message of the interviewee.
  • CP12. conduct scholarly research – Plan scholarly research by formulating the research question and conducting empirical or literature research in order to investigate the truth of the research question.
  • CP13. consult with business clients – Communicate with clients of a business or business project in order to introduce new ideas, obtain feedback, and find solutions to problems.
  • CP14. create data sets – 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.
  • CP15. create prototype of user experience solutions – Design and prepare mock-ups, prototypes and flows in order to test User Experience (UX) solutions or to collect feedback from users, customers, partners or stakeholders.
  • CP16. creatively use digital technologies – 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.
  • CP17. define technical requirements – 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.
  • CP18. deliver visual presentation of data – Create visual representations of data such as charts or diagrams for easier understanding.
  • CP19. demonstrate disciplinary expertise – Demonstrate deep knowledge and complex understanding of a specific research area, including responsible research, research ethics and scientific integrity principles, privacy and GDPR requirements, related to research activities within a specific discipline.
  • CP20. design process – Identify the workflow and resource requirements for a particular process, using a variety of tools such as process simulation software, flowcharting and scale models.
  • CP21. develop professional network with researchers and scientists – Develop alliances, contacts or partnerships, and exchange information with others. Foster integrated and open collaborations where different stakeholders co-create shared value research and innovations. Develop your personal profile or brand and make yourself visible and available in face-to-face and online networking environments.
  • CP22. develop software prototype – Create a first incomplete or preliminary version of a piece of software application to simulate some specific aspects of the final product.
  • CP23. develop statistical software – Participate in the various development stages of computer programs for econometric and statistical analysis, such as research, new product development, prototyping, and maintenance.
  • CP24. disseminate results to the scientific community – Publicly disclose scientific results by any appropriate means, including conferences, workshops, colloquia and scientific publications.
  • CP25. draft scientific or academic papers and technical documentation – Draft and edit scientific, academic or technical texts on different subjects.
  • CP26. evaluate research activities – Review proposals, progress, impact and outcomes of peer researchers, including through open peer review.
  • CP27. integrate gender dimension in research – Take into account in the whole research process the biological characteristics and the evolving social and cultural features of women and men (gender).
  • CP28. interact professionally in research and professional environments – Show consideration to others as well as collegiality. Listen, give and receive feedback and respond perceptively to others, also involving staff supervision and leadership in a professional setting.
  • CP29. manage findable accessible interoperable and reusable data – Produce, describe, store, preserve and (re) use scientific data based on FAIR (Findable, Accessible, Interoperable, and Reusable) principles, making data as open as possible, and as closed as necessary.
  • CP30. manage open publications – Be familiar with Open Publication strategies, with the use of information technology to support research, and with the development and management of CRIS (current research information systems) and institutional repositories. Provide licensing and copyright advice, use bibliometric indicators, and measure and report research impact.
  • CP31. manage research data – Produce and analyse scientific data originating from qualitative and quantitative research methods. Store and maintain the data in research databases. Support the re-use of scientific data and be familiar with open data management principles.
  • CP32. mentor individuals – Mentor individuals by providing emotional support, sharing experiences and giving advice to the individual to help them in their personal development, as well as adapting the support to the specific needs of the individual and heeding their requests and expectations.
  • CP33. operate open source software – Operate Open Source software, knowing the main Open Source models, licensing schemes, and the coding practices commonly adopted in the production of Open Source software.
  • CP34. perform scientific research – Gain, correct or improve knowledge about phenomena by using scientific methods and techniques, based on empirical or measurable observations.
  • CP35. plan research process – Outline the research methodologies and schedule in order to ensure that the research can be thoroughly and efficiently executed and that the objectives can be met in a timely manner.
  • CP36. promote open innovation in research – Apply techniques, models, methods and strategies which contribute to the promotion of steps towards innovation through collaboration with people and organizations outside the organisation.
  • CP37. promote the transfer of knowledge – Deploy broad awareness of processes of knowledge valorisation aimed to maximise the two–way flow of technology, intellectual property, expertise and capability between the research base and industry or the public sector.
  • CP38. provide user documentation – Develop and organise the distribution of structured documents to assist people using a particular product or system, such as written or visual information about an application system and how to use it.
  • CP39. publish academic research – Conduct academic research, in universities and research institutions, or on a personal account, publish it in books or academic journals with the aim of contributing to a field of expertise and achieving personal academic accreditation.
  • CP40. speak different languages – Master foreign languages to be able to communicate in one or more foreign languages.
  • CP41. think abstractly – Demonstrate the ability to use concepts in order to make and understand generalisations, and relate or connect them to other items, events, or experiences.
  • CP42. use methodologies for user-centered design – Use design methodologies in which the needs, wishes and limitations of end users of a product, service or process are given extensive attention at each stage of the design process.
  • CP43. write scientific publications – Present the hypothesis, findings, and conclusions of your scientific research in your field of expertise in a professional publication.
Competențe transversale · 14
  • CT1. analyse big data – Collect and evaluate numerical data in large quantities, especially for the purpose of identifying patterns between the data.
  • CT2. conduct qualitative research – Gather relevant information by applying systematic methods, such as interviews, focus groups, text analysis, observations and case studies.
  • CT3. develop creative ideas – Developing new artistic concepts and creative ideas.
  • CT4. execute analytical mathematical calculations – Apply mathematical methods and make use of calculation technologies in order to perform analyses and devise solutions to specific problems.
  • CT5. innovate in ICT – Create and describe new original research and innovation ideas within the field of information and communication technologies, compare to the emerging technologies and trends and plan the development of new ideas.
  • CT6. interact with users to gather requirements – Communicate with users to identify their requirements and collect them. Define all relevant user requirements and document them in an understandable and logical way for further analysis and specification.
  • CT7. manage personal professional development – Take responsibility for lifelong learning and continuous professional development. Engage in learning to support and update professional competence. Identify priority areas for professional development based on reflection about own practice and through contact with peers and stakeholders. Pursue a cycle of self-improvement and develop credible career plans.
  • CT8. synthesise information – Critically read, interpret, and summarise new and complex information from diverse sources.
  • CT9. use data processing techniques – Gather, process and analyse relevant data and information, properly store and update data and represent figures and data using charts and statistical diagrams.
  • CT10. execute ICT user research activities – Perform research tasks such as recruitment of participants, scheduling of tasks, collecting of empirical data, data analysis and production of materials in order to assess the interaction of users with an ICT system, program or application.
  • CT11. increase the impact of science on policy and society – Influence evidence-informed policy and decision making by providing scientific input to and maintaining professional relationships with policymakers and other stakeholders.
  • CT12. perform project management – Manage and plan various resources, such as human resources, budget, deadline, results, and quality necessary for a specific project, and monitor the project's progress in order to achieve a specific goal within a set time and budget.
  • CT13. manage intellectual property rights – Deal with the private legal rights that protect the products of the intellect from unlawful infringement.
  • CT14. promote the participation of citizens in scientific and research activities – Engage citizens in scientific and research activities and promote their contribution in terms of knowledge, time or resources invested.

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Cunoștințe · 63
  • C1. Identify stakeholder requirements conflicts in business briefs.
  • C2. Identify ICT system components and their functional relationships.
  • C3. Classify ICT system characteristics by functional purpose.
  • C4. Compare data distributions against expected model assumptions.
  • C5. Interpret correlation results for variable relationships.
  • C6. Select relevant scholarly sources for an AI research topic.
  • C7. Compare findings across scientific publications on an AI topic.
  • C8. Evaluate digital workflows against task constraints.
  • C9. Translate stakeholder needs into measurable technical specifications.
  • C10. Label chart elements for clear data interpretation.
  • C11. Identify workflow steps for a process scenario.
  • C12. Map resource needs for a process model.
  • C13. Select core features for a software prototype scope.
  • C14. Classify statistical analysis requirements by project priority.
  • C15. Evaluate statistical software results against expected outputs.
  • C16. Select an appropriate empirical method for a software investigation.
  • C17. Identify relevant variables in large data sets for pattern analysis.
  • C18. Interpret summary statistics for trend assessment.
  • C19. Evaluate concept originality against project goals.
  • C20. Calculate matrix operations for model training verification.
  • C21. Derive numerical estimates for optimization parameters.
  • C22. Record user requirements in a clear specification note.
  • C23. Classify datasets by relevance to project objectives.
  • C24. Identify relevant research funding opportunities for project proposals.
  • C25. Identify research misconduct in project documentation.
  • C26. Identify code patterns that reveal system structure from compiled software.
  • C27. Evaluate scientific messages for audience comprehension.
  • C28. Design quantitative research questions for software usage studies.
  • C29. Identify relevant research methods for a project question.
  • C30. Formulate interview questions for research objectives.
  • C31. Formulate a research question from a scholarly problem statement.
  • C32. Identify client business needs for project discussions.
  • C33. Evaluate research methods against disciplinary ethics requirements.
  • C34. Assess privacy risks in research activity plans.
  • C35. Build a professional profile for research networking.
  • C36. Format citations according to a publication style.
  • C37. Identify gender-related stakeholder needs in research planning.
  • C38. Classify datasets by access restrictions and sharing conditions.
  • C39. Evaluate publication venues for open access suitability.
  • C40. Assess copyright constraints for repository deposits.
  • C41. Classify research datasets by method, source, and sensitivity.
  • C42. Interpret open source license obligations for software distribution.
  • C43. Draft a research methodology for an ICT project.
  • C44. Evaluate collaboration proposals against innovation objectives.
  • C45. Identify transferable research assets for industry collaboration.
  • C46. Document intellectual property transfer conditions for a project.
  • C47. Evaluate manuscript quality against journal submission criteria.
  • C48. Classify technical concepts by shared properties and relationships.
  • C49. Translate user feedback into design requirements.
  • C50. Formulate a research question for a scientific publication.
  • C51. Evaluate evidence against the research hypothesis.
  • C52. Code interview transcripts into thematic categories.
  • C53. Evaluate observation notes for recurring research patterns.
  • C54. Identify emerging ICT trends relevant to research opportunities.
  • C55. Assess feedback to identify development priorities.
  • C56. Evaluate source credibility for technical information.
  • C57. Identify key claims in scientific articles.
  • C58. Analyze ICT user research data for interaction issues.
  • C59. Map policy stakeholders by influence and information needs.
  • C60. Assess evidence quality for policy recommendations.
  • C61. Evaluate project deliverables against quality requirements.
  • C62. Assess patent relevance for AI model components.
  • C63. Identify potential citizen contributions for research project participation.
Abilități · 119
  • A1. Prioritize stakeholder requirements by project constraints.
  • A2. Document stakeholder requirements in a structured specification.
  • A3. Explain ICT system boundaries using system interaction evidence.
  • A4. Calculate descriptive statistics for structured datasets.
  • A5. Assess publication credibility for an AI research topic.
  • A6. Compile datasets from distributed source files into one structured collection.
  • A7. Merge related records into a unified dataset schema.
  • A8. Organize data elements into a coherent training dataset.
  • A9. Assemble labeled samples into a single evaluation dataset.
  • A10. Select digital tools for solving project-specific conceptual problems.
  • A11. Prototype digital solutions for process improvement tasks.
  • A12. Prioritize technical requirements against project constraints.
  • A13. Validate technical requirements against stakeholder needs.
  • A14. Select appropriate chart types for dataset characteristics.
  • A15. Format visual hierarchy for presentation slides.
  • A16. Select a suitable process simulation tool.
  • A17. Construct a flowchart for a process scenario.
  • A18. Build a software prototype from defined functional requirements.
  • A19. Implement interface elements in a software prototype.
  • A20. Design a statistical model for a defined analysis goal.
  • A21. Prototype a statistical algorithm in working code.
  • A22. Plan a research question from an observable software problem.
  • A23. Collect data from a defined software study sample.
  • A24. Clean numerical data before statistical evaluation.
  • A25. Compare data distributions across large samples for anomalies.
  • A26. Generate original concept variants for AI solution features.
  • A27. Combine diverse source ideas into novel visual concepts.
  • A28. Refine concept sketches into implementable design directions.
  • A29. Compute statistical measures for experiment results.
  • A30. Elicit stakeholder requirements through structured user interviews.
  • A31. Classify user requirements by functional scope.
  • A32. Validate data quality against project requirements.
  • A33. Present statistical results in appropriate charts.
  • A34. Match grant criteria to project research objectives.
  • A35. Draft research proposal sections for funding submission.
  • A36. Evaluate research procedures against ethics requirements.
  • A37. Apply citation rules in research reports.
  • A38. Trace control flow in disassembled program sections.
  • A39. Compare binary outputs against original source behavior.
  • A40. Tailor technical explanations to lay audience needs.
  • A41. Translate scientific findings into plain language summaries.
  • A42. Select communication formats for public outreach messages.
  • A43. Select statistical methods for empirical software data analysis.
  • A44. Interpret computational results from quantitative experiments.
  • A45. Compare findings from different disciplines for consistency.
  • A46. Synthesize findings into a research summary.
  • A47. Conduct structured interviews with selected participants.
  • A48. Probe interview responses for missing details.
  • A49. Select an empirical method for a research question.
  • A50. Locate relevant literature for a research question.
  • A51. Formulate questions for client feedback sessions.
  • A52. Present solution options to business clients.
  • A53. Sketch user interface layouts for prototype testing sessions.
  • A54. Construct interactive wireframes for stakeholder review.
  • A55. Design user flow diagrams for task validation.
  • A56. Apply GDPR requirements to research data handling decisions.
  • A57. Identify relevant researchers for project collaboration.
  • A58. Evaluate collaboration opportunities against project goals.
  • A59. Prepare conference abstracts for scientific presentation.
  • A60. Draft journal manuscripts from research findings.
  • A61. Present research results to specialist audiences.
  • A62. Structure technical arguments for a scientific manuscript.
  • A63. Synthesize sources into a literature review section.
  • A64. Edit technical prose for clarity and precision.
  • A65. Evaluate research proposals against methodological rigor and feasibility.
  • A66. Assess research progress against agreed milestones and deliverables.
  • A67. Judge research outcomes against intended objectives and evidence quality.
  • A68. Review open peer feedback for relevance and methodological validity.
  • A69. Assess gender bias in research data collection methods.
  • A70. Integrate gender variables into research analysis frameworks.
  • A71. Give constructive feedback during technical review meetings.
  • A72. Adapt communication to interdisciplinary project stakeholders.
  • A73. Resolve workplace disagreements through professional dialogue.
  • A74. Describe datasets using standard metadata elements.
  • A75. Store datasets in structured repositories.
  • A76. Assign licensing terms to research publications.
  • A77. Report research impact using bibliometric indicators.
  • A78. Validate research data entries against collection records.
  • A79. Store research data in a database schema.
  • A80. Assess individual support needs in mentoring conversations.
  • A81. Select open source components for project integration.
  • A82. Evaluate source code contributions against open source project practices.
  • A83. Sequence research activities within project constraints.
  • A84. Evaluate research methods against project objectives.
  • A85. Identify external research partners for innovation projects.
  • A86. Document collaboration outcomes for innovation review.
  • A87. Assess knowledge exchange opportunities against stakeholder needs.
  • A88. Draft structured product manuals for end users.
  • A89. Organize documentation sets by user task.
  • A90. Review user guides against product functionality.
  • A91. Formulate a research question from a field gap.
  • A92. Analyze empirical findings against existing literature.
  • A93. Draft an academic abstract for publication submission.
  • A94. Translate technical documentation for project stakeholders.
  • A95. Interpret meeting remarks in a foreign language.
  • A96. Compose professional emails in a foreign language.
  • A97. Present project updates in a foreign language.
  • A98. Generalize patterns from software cases to broader design principles.
  • A99. Map system behaviours to abstract models.
  • A100. Elicit user needs through structured interviews.
  • A101. Observe user interactions in task-based sessions.
  • A102. Structure a scientific article for journal submission.
  • A103. Select interview questions aligned with a research objective.
  • A104. Conduct participant interviews for qualitative data collection.
  • A105. Compare candidate innovation ideas against current ICT technologies.
  • A106. Formulate original ICT research hypotheses from emerging needs.
  • A107. Review progress against a career development plan.
  • A108. Compare findings across technical documents.
  • A109. Summarize research results in concise briefs.
  • A110. Collect empirical data from ICT user research sessions.
  • A111. Translate research findings into policy briefs.
  • A112. Prioritize project tasks against deadline and budget constraints.
  • A113. Allocate project resources to scheduled work packages.
  • A114. Monitor project milestones against the approved schedule.
  • A115. Classify copyright status for software deliverables.
  • A116. Document ownership claims for project artifacts.
  • A117. Select suitable participation channels for citizen research involvement.
  • A118. Evaluate citizen input against research project objectives.
  • A119. Evaluate individual mentoring needs through structured conversation notes.
Responsabilitate și autonomie · 46
  • R1. Resolve stakeholder requirement disagreements through evidence-based comparison.
  • R2. Document ICT system behavior using operational observations.
  • R3. Assess machine learning outputs against validation data.
  • R4. Compose a structured literature summary for an AI topic.
  • R5. Adapt digital methods to resolve technical ambiguities.
  • R6. Document technical requirements in a structured specification.
  • R7. Evaluate chart clarity against presentation goals.
  • R8. Assess prototype behavior against intended use cases.
  • R9. Interpret results from a software experiment against the hypothesis.
  • R10. Validate calculation outputs against problem constraints.
  • R11. Verify requirement statements against user feedback.
  • R12. Store datasets using approved organisational procedures.
  • R13. Evaluate grant application completeness against submission requirements.
  • R14. Document research decisions with integrity records.
  • R15. Reconstruct software modules from interface evidence.
  • R16. Evaluate dataset quality for quantitative software research.
  • R17. Evaluate research evidence against project constraints.
  • R18. Evaluate interview notes against research questions.
  • R19. Evaluate evidence against a research question.
  • R20. Evaluate client feedback against project constraints.
  • R21. Refine prototype interactions after user feedback.
  • R22. Justify research decisions using scientific integrity principles.
  • R23. Exchange project information with research partners.
  • R24. Respond to peer review comments on manuscripts.
  • R25. Justify gender-sensitive research choices in project documentation.
  • R26. Supervise junior staff during routine technical tasks.
  • R27. Evaluate dataset formats for interoperability.
  • R28. Apply open data principles to research dataset publication.
  • R29. Adapt mentoring approach to individual expectations.
  • R30. Maintain professional boundaries during mentoring support.
  • R31. Document open source usage for software compliance records.
  • R32. Allocate time for research tasks across the schedule.
  • R33. Coordinate innovation exchanges with external organizations.
  • R34. Negotiate collaboration terms for technology transfer arrangements.
  • R35. Distribute approved documentation to users.
  • R36. Evaluate analogies between technical solutions and problem contexts.
  • R37. Evaluate prototypes against user task goals.
  • R38. Draw conclusions from empirical research findings.
  • R39. Prioritize innovation concepts against project feasibility constraints.
  • R40. Set personal development goals from practice reflection.
  • R41. Plan learning activities for a professional growth cycle.
  • R42. Recruit participants for ICT user research sessions.
  • R43. Schedule ICT user research tasks with participants.
  • R44. Maintain professional relationships with policymakers.
  • R45. Evaluate license obligations for third-party code.
  • R46. Document citizen contributions in a research activity record.

Ocupații prevăzute în planul de învățământ

  • Artificial intelligence engineer — ESCO 2511.11
  • ICT research consultant — ESCO 2511.12

Plan complet · 4 semestre · 120 ECTS. Alege anul de studiu pentru a vedea cele două semestre ale sale.

Se alege câte o disciplină din fiecare pachet opțional; facultativele aduc credite suplimentare celor 30 ECTS/semestru.

C1: DF — fundamentală; DS — de specializare; DC — complementară.
C2: DOB — obligatorie; DOP — opțională; DFA — facultativă. P1, P2 și P3 identifică pachetele în cadrul semestrului.

Semestrul 1 · 30 ECTS

18 ECTS obligatorii + 12 ECTS opționale. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1Distributed SystemsDFDOB—INFOM1016
2Fundamentals of Artificial IntelligenceDFDOB—INFOM1026
3Methodology of Research ActivityDFDOB—INFOM1044
4Research EthicsDCDOB—INFOM1032
5Advanced Logic and Functional ProgrammingDSDOPP1INFOM1056
6Data Analysis and Programming in RDSDOPP1INFOM1086
7Introduction to Cybersecurity. Prevention, Detection and Mitigation TechniquesDSDOPP1INFOM1116
8Operations Research and OptimizationDSDOPP1INFOM1076
9Architectures for Parallel ComputingDSDOPP2INFOM1066
10Cryptography and Information SecurityDSDOPP2INFOM1166
11Distributed Methods and Technologies based on XMLDSDOPP2INFOM1096
12Dynamical Systems in Machine LearningDSDOPP2INFOM1106
13Operating Systems IDFDFA—INFOL3025
14Programming IDFDFA—INFOL1026
15Volunteering IDCDFA—INFOM1002

Semestrul 2 · 30 ECTS

12 ECTS obligatorii + 18 ECTS opționale. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1Academic and Technical WritingDFDOB—INFOM2016
2Research StageDSDOB—INFOM2026
3DevSecOpsDSDOPP1INFOM2216
4Multi-agent SystemsDSDOPP1INFOM2036
5Term RewritingDSDOPP1INFOM2056
6Automated Theorem ProvingDSDOPP2INFOM2086
7Cloud SecurityDSDOPP2INFOM2186
8Data MiningDSDOPP2INFOM2066
9Parallel ComputingDSDOPP2INFOM2076
10Big Data TechnologiesDSDOPP3INFOM2106
11Modeling and Verifying Algorithms in CoqDSDOPP3INFOM2116
12Special Topics in Artificial IntelligenceDSDOPP3INFOM2096
13Logical and Functional ProgrammingDSDFA—INFOL6014
14Programming IIDSDFA—INFOL2046
15Volunteering IIDCDFA—INFOM2002

Semestrul 3 · 30 ECTS

16 ECTS obligatorii + 14 ECTS opționale. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1Machine LearningDSDOB—INFOM3028
2Techniques for Scientific WorkDSDOB—INFOM3018
3Advanced NeuroscienceDSDOPP1INFOM3057
4Computer VirologyDSDOPP1INFOM3197
5Computer VisionDSDOPP1INFOM3037
6Metaheuristic AlgorithmsDSDOPP1INFOM3067
7Resource Management in Distributed and Parallel SystemsDSDOPP1INFOM3047
8Algorithm Synthesis and Mathematical Theory ExplorationDSDOPP2INFOM3157
9Computational Game TheoryDSDOPP2INFOM3097
10Introduction to Quantum ComputingDSDOPP2INFOM3087
11Penetration TestingDSDOPP2INFOM3227
12Text MiningDSDOPP2INFOM3077
13Volunteering IIIDCDFA—INFOM3002

Semestrul 4 · 30 ECTS

30 ECTS obligatorii. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1MSc Thesis PreparationDSDOB—INFOM40215
2Research PracticeDSDOB—INFOM4018
3Scientific SeminarDSDOB—INFOM4037
4Volunteering IVDCDFA—INFOM4002

Arhiva fișelor disciplinelor · Semestrele 1–4. Verifică anul universitar indicat în fiecare fișă.

Plan complet · Promoția 2025–2027

Planul de învățământ pentru toate cele 4 semestre ale programului · 120 ECTS.

Misiunea programului de studii

Misiunea principală a programului de studii universitare de masterat Artificial Intelligence and Distributed Computing este de a asigura obținerea unor competențe specifice desfășurării de activități de cercetare fundamentală și aplicativă în domeniul Informaticii, orientată cu precădere înspre domenii de actualitate cum sunt inteligența artificială, calculul distribuit și de înaltă performanță, precum și progrese din domeniul teoriei calculului. Competențele dobândite vor permite absolvenților programului de studii universitare de masterat să urmeze ciclul de studii universitare de doctorat sau să își desfășoare activitate în institute de cercetare și departamente de cercetare-dezvoltare în domeniul IT.

Durată: 2 ani   |   Credite: 120 ECTS
Limba de predare: engleză   |   Forma de învățământ: cu frecvență
Tipul programului: master de cercetare

Deschide categoria care te interesează. Informația completă este păstrată, cu liste pe două coloane când spațiul permite.

Competențe-cheie

Competențe-cheie:

  • CC1. Competențe multilingvistice;
  • CC2. Competențe în domeniul științei, tehnologiei, ingineriei și matematicii;
  • CC3. Competențe digitale;
  • CC4. Competențe personale, sociale și de a învăța să înveți;
  • CC5. Competențe civice;
  • CC6. Competențe antreprenoriale.
Competențe profesionale

Competențe profesionale:

  • CP1. Capacitatea de a înțelege/utiliza/adapta concepte specifice Inteligenței artificiale și calculului distribuit în diferite contexte teoretice și practice;
  • CP2. Capacitatea de a modela/proiecta/implementa sisteme inteligente cu aplicații în diverse domenii științifice și tehnice;
  • CP3. Capacitatea de a utiliza tehnologii recente din calculul de înaltă performanță și calculul distribuit;
  • CP4. Capacitatea de a analiza cerințele utilizatorilor, de a identifica soluții, de a compara și selecta instrumente teoretice și software adecvate;
  • CP5. Capacitatea de a propune/analiza/demonstra/dezvolta concepte și teorii inovatoare;
  • CP6. Capacitatea de a analiza critic rezultate ale cercetării comunității și de a elabora rapoarte științifice;
  • CP7. Competențe antreprenoriale în domeniul IT.
Competențe transversale

Competențe transversale:

  • CT1. Capacitate de procesare a unor informații complexe și de integrare a cunoștințelor specifice unor domenii variate;
  • CT2. Capacitate de planificare și organizare eficientă a muncii cu respectarea termenelor;
  • CT3. Respectarea normelor de etică specifice domeniului de activitate.
  • CT4. Capacitatea de a comunica/transfera cunoștințe și de a instrui în domeniul informaticii, cu precădere în cadrul colaborărilor interdisciplinare.
  • CT5. Capacitatea de a se implica în activități destinate unor grupuri sociale diverse și utilizarea expertizei profesionale pentru a iniția/derula proiecte și activități care să susțină procesul de digitalizare și educație pentru o societate digitalizată;
  • CT6. Preocupare față de protejarea mediului înconjurător în contextul utilizării și dezvoltării unor tehnologii de calcul inovatoare.

Deschide categoria care te interesează. Informația completă este păstrată, cu liste pe două coloane când spațiul permite.

Cunoștințe

Cunoștințe – Conform Cadrului European al Calificărilor (European Qualifications Framework – EQF), rezultatele învățării aferente nivelului 7 de calificare, corespunzător studiilor universitare de masterat, presupun cunoștințe foarte specializate și conștientizarea critică a acestora, unele dintre ele situându-se în avangarda nivelului de cunoștințe dintr-un domeniu de muncă sau de studiu, ca bază a unei gândiri și/sau cercetări originale:

  • Cunoștințe avansate în domeniul logicii și raționamentului automat;
  • Metode de distribuire a calculului;
  • Concepte specifice calculului de înaltă performanță;
  • Metode de reprezentare a cunoștințelor și de extragere a acestora din date;
  • Modele probabiliste în reprezentarea și procesarea cunoștințelor;
  • Modele și metode în învățarea automată;
  • Algoritmi avansați de căutare în spațiul soluțiilor și algoritmi de planificare; 
  • Principii ale proiectării și implementării aplicațiilor distribuite;
  • Cunoștințe avansate în modelare computațională și analiza algoritmilor;
  • Concepte din metodologia cercetării științifice.
Abilități
 
Abilități – Conform Cadrului European al Calificărilor (European Qualifications Framework – EQF), rezultatele învățării aferente nivelului 7 de calificare, corespunzător studiilor universitare de masterat, presupun abilități de specialitate pentru rezolvarea problemelor în materie de cercetare și/sau inovare, pentru dezvoltarea de noi cunoștințe și proceduri și pentru integrarea cunoștințelor din diferite domenii:
  • Proiectarea și implementarea unor sisteme inteligente, sisteme multi-agent, sisteme expert, sisteme de recomandare;
  • Implementarea unor modele de învățare automată adaptate diferitelor domenii aplicative; 
  • Utilizarea tehnologiilor orientate spre servicii (cloud/edge/fog computing);
  • Utilizarea unor instrumente de modelare și simulare;
  • Abilitatea de a desfășura activitatea de cercetare în domeniul Informaticii și domenii înrudite;
  • Abilități de analiză calitativă și cantitativă a datelor;
Responsabilitate și autonomie
 
Responsabilitate și autonomie – Conform Cadrului European al Calificărilor (European Qualifications Framework – EQF), rezultatele învățării aferente nivelului 7 de calificare, corespunzător studiilor universitare de masterat, presupun gestionarea și transformarea situațiilor de muncă sau de studiu care sunt complexe, imprevizibile și necesită noi abordări strategice, prin asumarea responsabilității pentru a contribui la cunoștințele și practicile profesionale și/sau pentru revizuirea performanței strategice a echipelor:
  • Respectarea confidențialității și protejarea proprietății intelectuale în relațiile cu colaboratorii;
  • Reprezentarea corectă a nivelului de competență și acceptarea de sarcini în limitele acestuia;
  • Responsabilitatea de a respecta cele mai înalte standarde profesionale în dezvoltarea de produse software și în activitatea de cercetare;
  • Păstrarea autonomiei, integrității și independenței în opiniile profesionale;
  • Promovarea integrității și reputației profesiei, în concordanță cu interesul public;
  • Perfecționarea continuă în domeniul de activitate;
  • Comportament etic, cinstit și colegial în practicarea profesiei.

Ocupații prevăzute în planul de învățământ

Proiectant sisteme informatice — COR 251101

Plan complet · 4 semestre · 120 ECTS. Alege anul de studiu pentru a vedea cele două semestre ale sale.

Se alege câte o disciplină din fiecare pachet opțional; facultativele aduc credite suplimentare celor 30 ECTS/semestru.

C1: DF — fundamentală; DS — de specializare; DC — complementară.
C2: DOB — obligatorie; DOP — opțională; DFA — facultativă. P1, P2 și P3 identifică pachetele în cadrul semestrului.

Semestrul 1 · 30 ECTS

18 ECTS obligatorii + 12 ECTS opționale. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1Distributed SystemsDFDOB—INFOM1016
2Fundamentals of Artificial IntelligenceDFDOB—INFOM1026
3Research EthicsDCDOB—INFOM1032
4Methodology of Research ActivityDFDOB—INFOM1044
5Advanced Logic and Functional ProgrammingDSDOPP1INFOM1056
6Architectures for Parallel ComputingDSDOPP1INFOM1066
7Introduction to Cybersecurity. Prevention, Detection and Mitigation TechniquesDSDOPP1INFOM1116
8Operations Research and OptimizationDSDOPP1INFOM1076
9Data Analysis and Programming in RDSDOPP2INFOM1086
10Distributed Methods and Technologies based on XMLDSDOPP2INFOM1096
11Dynamical Systems in Machine LearningDSDOPP2INFOM1106
12Cryptography and Information SecurityDSDOPP2INFOM1166
13Programming IDFDFA—INFOL1026
14Operating Systems IDFDFA—INFOL3025
15Volunteering IDCDFA—INFOM1002

Semestrul 2 · 30 ECTS

12 ECTS obligatorii + 18 ECTS opționale. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1Academic and Technical WritingDFDOB—INFOM2016
2Research StageDSDOB—INFOM2026
3Multi-agent SystemsDSDOPP1INFOM2036
4DevSecOpsDSDOPP1INFOM2216
5Term RewritingDSDOPP1INFOM2056
6Cloud SecurityDSDOPP2INFOM2186
7Data MiningDSDOPP2INFOM2066
8Parallel ComputingDSDOPP2INFOM2076
9Automated Theorem ProvingDSDOPP2INFOM2086
10Special Topics in Artificial IntelligenceDSDOPP3INFOM2096
11Modeling and Verifying Algorithms in CoqDSDOPP3INFOM2116
12Big Data TechnologiesDSDOPP3INFOM2106
13Logical and Functional ProgrammingDSDFA—INFOL6014
14Programming IIDFDFA—INFOL2045
15Volunteering IIDCDFA—INFOM2002

Semestrul 3 · 30 ECTS

16 ECTS obligatorii + 14 ECTS opționale. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1Techniques for Scientific WorkDSDOB—INFOM3018
2Machine LearningDSDOB—INFOM3028
3Computer VisionDSDOPP1INFOM3037
4Resource Management in Distributed and Parallel SystemsDSDOPP1INFOM3047
5Neuroscience – Brain Computing InterfacesDSDOPP1INFOM3057
6Computer VirologyDSDOPP1INFOM3197
7Metaheuristic AlgorithmsDSDOPP1INFOM3067
8Text MiningDSDOPP2INFOM3077
9Introduction to Quantum ComputingDSDOPP2INFOM3087
10Penetration TestingDSDOPP2INFOM3227
11Computational Game TheoryDSDOPP2INFOM3097
12Algorithm Synthesis and Mathematical Theory ExplorationDSDOPP2INFOM3157
13Volunteering IIIDCDFA—INFOM3002

Semestrul 4 · 30 ECTS

30 ECTS obligatorii. Facultativele aduc credite suplimentare.

Nr.DisciplinăC1C2PachetCod disciplinăECTS
1Research PracticeDSDOB—INFOM4018
2MSc Thesis PreparationDSDOB—INFOM40215
3Scientific SeminarDSDOB—INFOM4037
4Volunteering IVDCDFA—INFOM4002

Arhiva fișelor disciplinelor · Semestrele 1–4. Verifică anul universitar indicat în fiecare fișă.