I-Week 2018

Course in InSIS – 4EK611, classroom – NB 459

Chris Brunsdon is Professor of Geocomputation and Director of the National Centre for Geocomputation, at the National University of Ireland, Maynooth. He spetialised in spatial data analysis and visualisation techniques, particularly applied to social topics, such as crime patterns , house prices and health. He obtained a degree in Mathematics from the University of Durham (UK) and a Master’s Degree and PhD from the University of Newcastle Upon Tyne. He is the joint author of the book ‘An Introduction to R for Spatial Analysis and Mapping (Sage, 2016).

The course covers basic use of the R statistical programming language, the use of tools in the dplyr package, and a number of mapping and visualisation tools. The principles of reproducible analysis will also be considered, as well as a practical introduction to Rmarkdown. Participants will ultimately be able to create reproducible reports as web pages (including interactive data exploration tools), as well standard documents.

Course syllabus:

• An overview of R
• Spatial Data Handling in R
• Spatial Statistical Tools in R
• Interactive Visualisation Methods in R
• An overview of Reproducibility
• Reproducibility tools in R
• Creating Reproducible Documents
• Creating Reproducible Web Dashboards

Course in InSIS – 4IT 482, classroom – NB471

Dr. Jiri Feuerlicht lectures on enterprise computing topics at the University of Technology, Sydney, Australia and at the Prague University of Economics. He has presented seminars and professional development courses in Australia, USA, Europe and Asia. Dr. Jiri Feuerlicht holds a PhD from the Imperial College, London University and is the author of over 100 publications across a range of topics in computer science.This course focuses on topic of cloud computing covering a wide range of topics providing the students with indepth knowledge of this rapidly evolving area.Course syllabus:

• Introduction: historical perspective, advantages and challenges of cloud computing, synergies with SOA, etc.
• Cloud computing conceptds, standards and techniques: deployment models: private, public and hybrid clouds, delivery models: SaaS, IaaS, PaaS
• Cloud enabling technology: virtualization, containerization, cloud storage, etc.
• Cloud application architectures: cloud architectural patterns, security models, microservices, continuous delivery , continuous deployment and continuous integration
• Cloud data management: methods and technology: Hadoop, CAP theorem, NoSQL databases and data stores: Document databases, Graph databases, Column databases, etc. Product examples: MongoDB, Cassandra, etc.
• Cloud migration: identifying opportunities for cloud, cost-benefit analysis, provider selection, etc
• Commercial cloud platforms: AWS, Azure, etc.
• Cloud computing trends

Course in InSIS – 4ES640, classroom – NB470

Mojca Bavdaž is Associate Professor at the Faculty of Economics, University of Ljubljana, Slovenia. She has been working in the field official statistics for about two decades, be it for teaching, research or consultancy. She has conducted research on data sources and data collection underlying official economic statistics as well as on dissemination, visualization and use of these data.What is the role of official economic statistics in the world of fake data and fake news? How were official economic indicators used in recent campaigns (e.g. US presidential elections, Brexit)? How can official economic indicators compete with alternative metrics? The course will equip students with fundamentals about the functioning and methodology of official statistics to critically evaluate indicators used in today’s world, judge implications for their quality and consider their power and limitations.

• Course syllabus -the course will seek answers to the following questions:
• What is the quality of official economic statistics based on?
• What data sources are used in the production of official economic statistics?
• How do methods of data collection contribute to the quality of official economic statistics?
• How does official statistics deal with modern challenges such as big data (e.g. mobile phone data, scanner data) and integration of sources (e.g. administrative tax data with a survey)?
• How does official economic statistics solve measurement challenges (e.g. definition of concepts and statistical units)?
• How are official economic statistics disseminated to reach its users? What communication channels and what visualization tools are used?

Course in InSIS – 4SA630, classroom – NB469

František Sudzina is Associate Professor in Business Economics at Aalborg University, Denmark. Previously, he worked for the Aarhus University Information Systems Research Group and the Copenhagen Business School Center for Applied ICT, where he was involved in the 3rd Generation Enterprise Resource Planning – Strategic Software for Increased Globalisation (3gERP.org) research project. His research interests include information systems, marketing, operations research and statistics. He is a member of numerous programme committees for international conferences, and a member of editorial boards for several journals.The purpose of this course is to introduce students to information systems in a broad sense of the word. The focus of the lecture series is on information systems within organizations. Information systems help with managing an organization, they are cross-sectional, i.e. they are used virtually in all processes, such as production, marketing / sales, finance / accounting, and human resources management. Besides information on the importance and ways of using information systems, the course discusses also information systems development and students will learn how to model certain aspects of information systems.Course syllabus:

• Enterprise information systems, companies, and strategy
• Foundations of Business Intelligence
• Security
• Enterprise information systems and operations
• E-commerce
• Knowledge management
• Enterprise information systems development
• Project management