Data Science and Artificial Intelligence

Cloud computing for data scientists

Integrated course, 5.00 ECTS

 

Course content

Part 1: Fundamentals of cloud computing
- Overview and definition of terms
- IT architectures and IT service management
- Service deployment models (XaaS, Edge Computing, Fog Computing, ...)
- Security management and identity management
- Overview of important cloud computing providers
Part 2: Introduction to cloud computing
- Idenity management binding and synchronization
- Setup and configuration of simple cloud services
- Monitoring and cost management
Part 3: Data storage and data processing in the cloud
- Setup, configuration and deployment of selected storage services
- Setup, configuration and deployment of clusters for the distributed storage and processing of big data
- High-performance and scalable queries

Learning outcomes

Students have basic knowledge as well as practical knowledge in the field of cloud computing. They know and understand different service deployment models and have an overview of important cloud computing providers. Students are able to independently set up, configure and monitor simple cloud services. In particular, the students have practical application knowledge in the areas of data storage and data processing.

Recommended or required reading and other learning resources / tools

Recommended literature or books:
- Briggs, B., Kassner, E. (2017). Cloud Application Architecture Guide; Microsoft Corporation. Microsoft Press, 1st edition.
- Marz, N., Warren, J. (2015). Big Data - Principles and best practices of scaleable real-time data systems. Manning Publications Co., 1st edition.
- Michael Crump and Barry Luijbregts; Microsoft Press 2018. Azure for Architects
- Modi, R. (2019). Azure for Architects: Implementing cloud design, DevOps, containers, IoT, and serverless solutions on your public cloud. Packt Publishing, 2nd edition.
- Tejada Z. (2017). Mastering Azure Analytics. Architecting in the Cloud with Azure Data Lake, HDInsight, and Spark. O`Reilly UK Ltd., 1st edition.
- White T. (2015). Hadoop - The Definite Guide. O’Reilly Media, 4th edition.
Recommended journals or selected articles:
- Mell, P., Grance, T. (2011). The NIST Definition of Cloud Computing - Recommendations of the National Institute of Standards and Technology. NIST Publications.

Other relevant journals and articles will be announced in the courses.

Typical software for this module:
Microsoft Azure, Microsoft Windows Server, Microsoft SQL Server, Apache Hadoop, Amazon Web Services, Google Cloud etc.

Mode of delivery

2,5 ECTS Lecture, 2,5 ECTS Exercise

Prerequisites and co-requisites

Module 11 and 12

Assessment methods and criteria

Lecture: final exam; Exercise: examination character