Machine Learning (supervised): Decision trees, Naïve Bayes classification, Ordinary least square regression, Logistic regression, Neural Networks, SVM (Support Vector Machine), Ensemble methods, others

Systems Engineering and Software Engineering principles, methods and models, distributed systems design and organisation

Data management and enterprise data infrastructure, private and public data storage systems and services

Machine Learning (supervised): Decision trees, Naïve Bayes classification, Ordinary least square regression, Logistic regression, Neural Networks, SVM (Support Vector Machine), Ensemble methods. Systems Engineering and Software Engineering principles, methods and models, distributed systems design and organisation. Data management and enterprise data infrastructure, private and public data storage systems and services

Machine Learning (unsupervised): clustering algorithms, Principal Components Analysis (PCA), Singular Value Decomposition (SVD), Independent Components Analysis (ICA)

Cloud Computing, cloud based services and cloud powered services design

Data storage systems, data archive services, digital libraries, and their operational models

Machine Learning (unsupervised): clustering algorithms, Principal Components Analysis (PCA), Singular Value Decomposition (SVD), Independent Components Analysis (ICA). Cloud Computing, cloud based services and cloud powered services design. Data storage systems, data archive services, digital libraries, and their operational models.

Machine Learning (reinforced): Q-Learning, TD-Learning, Genetic Algorithms)

Big Data technologies for large datasets processing: batch, parallel, streaming systems, in particular cloud based

Data governance, data governance strategy, Data Management Plan (DMP)

Machine Learning (reinforced): Q-Learning, TD-Learning, Genetic Algorithms). Big Data technologies for large datasets processing: batch, parallel, streaming systems, in particular cloud based. Data governance, data governance strategy, Data Management Plan (DMP).

Data Mining (Text mining, Anomaly detection, regression, time series, classification, feature selection, association, clustering)

Applications software requirements and design, agile development technologies, DevOps and continuous improvement cycle

Data Architecture, data types and data formats, data modeling and design, including related technologies (ETL, OLAP, OLTP, etc.)

Data Mining (Text mining, Anomaly detection, regression, time series, classification, feature selection, association, clustering). Applications software requirements and design, agile development technologies, DevOps and continuous improvement cycle. Data Architecture, data types and data formats, data modeling and design, including related technologies (ETL, OLAP, OLTP, etc.)

Text Data Mining: statistical methods, NLP, feature selection, apriori algorithm, etc.

Systems and data security, data access, including data anonymisation, federated access control systems

Data lifecycle and organisational workflow, data provenance and linked data

Text Data Mining: statistical methods, NLP, feature selection, apriori algorithm, etc. Systems and data security, data access, including data anonymisation, federated access control systems. Data lifecycle and organisational workflow, data provenance and linked data

Prescriptive Analytics

Compliance based security models, privacy and IPR protection

Data curation and data quality, data integration and interoperability

Prescriptive Analytics. Compliance based security models, privacy and IPR protection. Data curation and data quality, data integration and interoperability

Prescriptive Analytics

Relational, nonrelational databases (SQL and NoSQL), Data Warehouse solutions, ETL (Extract, Transform, Load), OLTP, OLAP processes for large datasets

Data protection, backup, privacy, IPR, ethics and responsible data use

Prescriptive Analytics. Relational, nonrelational databases (SQL and NoSQL), Data Warehouse solutions, ETL (Extract, Transform, Load), OLTP, OLAP processes for large datasets. Data protection, backup, privacy, IPR, ethics and responsible data usu

Graph Data Analytics: path analysis, connectivity analysis, community analysis, centrality analysis, subgraph isomorphism, etc.

Big Data infrastructures, high-performance networks, infrastructure and services management and operation

Metadata, PID, data registries, data factories, standards and compliance

Graph Data Analytics: path analysis, connectivity analysis, community analysis, centrality analysis, subgraph isomorphism, etc. Big Data infrastructures, high-performance networks, infrastructure and services management and operation. Metadata, PID, data registries, data factories, standards and compliance

Qualitative analytics

Modeling and simulation, theory and systems

Open Data, Open Science, research data archives/repositories, Open Access, ORCID

Qualitative analytics. Modeling and simulation, theory and systems. Open Data, Open Science, research data archives/repositories, Open Access, ORCID

Natural language processing

Information systems, collaborative systems

Data preparation and pre-processing

Natural language processing. Information systems, collaborative systems. Data preparation and pre-processing

Business Analytics (BA) and Business Intelligence (BI); methods and data analysis; cognitive technologies

Optimisation

Business Analytics (BA) and Business Intelligence (BI); methods and data analysis; cognitive technologies. Optimisation

Data Warehouses technologies, data integration and analytics

Data driven User Experience (UX) requirements and design

Data Warehouses technologies, data integration and analytics
Data driven User Experience (UX) requirements and design