General objectives of the course:
Knowing the fundamental concepts related to databases
Deepening the knowledge about the relational data model
Competencies that are targeted:
Identifying the basic concepts for organizing data using databases
Identifying and explaining the main models for organizing and managing data in databases
Using methodologies and database design environments for specific problems
Evaluating the quality of various Database Management Systems in terms of their structure, functionality and extensibility
Developing projects involving databases
This class is taught in Romanian for the 2nd year Mathematics and Computer Science major (ro., Matematica-Informatica romana, anul 2).
Objectives of the course:
Handling (extremely) large amounts of digital data in various formats (text, video, sensor, financial, medical etc.)
Enable the use of novel algorithms, software infrastructures and methodologies for the purpose of processing (store, retrieve, analyze) large amounts of data
Provide decision support over large volumes of data
Enable the creation of applications and services for various business domains based on the results of big data analysis
Competencies that are targeted:
Use of non-traditional databases for storing and processing large amounts of data
Advanced querying over distributed information resources
Evaluation, testing and validation with real-world data
Learning to conduct incipient research in the field of Big Data
Methods and algorithms for data processing and analysis applied to Big Data
Multidisciplinary competencies spanning various application sectors (e.g., life sciences and bioinformatics, telco, media, finance, security, health, energy, etc.)
This class is taught in English for the 2nd year of the following Master programmes: High Performance Computing Master, Software Engineering Master and Data Science Master.
Objectives of the course:
Handling and analyzing large amounts of digital data in the field of Cognitive Science
Competencies targeted:
Understanding the specificity of Big Data in the context of psychological research
Knowledge of the main sources of Big Data for psychological research and the main procedures of processing Big Data
Understanding the role of Big Data analysis in cognitive sciences, social psychology, healthcare and other related fields of knowledge
Explaining specific behaviors using complex models based on Big Data analysis
Interpreting the results of Big Data analysis by integrating empirical findings with the psychological theoretical context
Use of non-traditional databases for storing and processing large amounts of data
This class is offered to the 2nd year students of the Cognitive Sciences Bachelor Programme at the Faculty of Psychology within UBB.
Course objectives:
To get acquainted with the fundamental concepts concerning concurrency control, database recovery, database security, query optimization, distributed databases
To create ADO.NET applications with data-bound controls
To handle concurrently running transactions using pessimistic and optimistic isolation levels
To optimize SQL queries
Targeted skills:
Using methodologies and database design environments for specific problems
Evaluating the quality of various Database Management Systems in terms of their structure, functionality and extensibility
Developing projects involving databases
This class is taught to 2nd year students from the Computer Science Bachelor Programme in English. I am only responsible for the practical work (i.e., the labs) within this course.