Intensive courses

Course in InSIS – 4IT482
Date: 13-15 January 2025, exam –
3 ECTS
Registrations: are open from 16^th September 2024
your own laptop is requried

 

Dr George Feuerlicht is a visiting lecturer at the Department of Information Technologies, Prague University of Economics. George has been actively involved in researching cloud computing developments from its emergence at the beginning of this century and has published number of articles dealing with cloud computing topics. He has presented seminars and professional development courses in Australia, Europe, Asia and USA and is the author of over 100 publications across a range of topics in computer science. He holds a PhD in Electrical Engineering from the Imperial College, London University, U.K.

 

 

Cloud computing has become the dominant approach for the implementation of information systems with many government and private organizations migrating their entire IT infrastructure to the cloud. Most recently, AI and ML (Machine Learning) services, available on leading cloud platforms, have provided a new impetus for adopting of cloud computing. Most experts today recognize the benefits of cloud computing that include fast implementation, potential for cost reduction and rapid innovation. However, the fast rate of evolution of cloud technologies and the complexity of managing large-scale cloud deployments represent a challenge for organizations making the transition into the cloud. This three-day course aims to provide attendees with a balanced view of cloud computing covering basic cloud concepts and terminology and discussing the benefits and challenges of cloud adoption. The course includes demonstrations and practical hands-on exercises using Amazon Web Services, including EC2, S3, Lambda, RDS and NoSQL databases and a range of AI and ML services.

 

Course Content

• Introduction to cloud computing: current IT technology trends, business motivations and technology drivers, benefits and challenges, cloud vs on premises IT, cloud computing in a historical context, cloud computing case studies
• Cloud computing concepts and terminology: SOA services, APIs, virtual machines and containers, serverless computing, DevOps and microservices, cloud computing service models (SaaS, IaaS, PaaS, etc.), cloud computing deployment models (public, private, and hybrid clouds), multitenancy and polymorphic applications, etc.
• Public cloud platforms: AWS, Azure, Google Cloud Platform, etc.
• AWS global infrastructure and services: Regions, Availability Zones, AWS security, AWS core services: EC2, EBS, S3, Glacier, DynamoDB, Amazon Aurora, ML services, etc.
• NoSQL databases: document databases, column databases, graph databases, etc. CAP theorem and BASE consistency, tunable consistency, MongoDB, Amazon DynamoDB, Neo4J, AWS Athena, etc.
• Cloud computing architectures and open-source frameworks: NIST Reference Architecture, Kubernetes, Open Cloud, etc.
• Cloud computing adoption: migration readiness and planning, migration strategies, AWS Adoption Framework
• Future directions: Industrialization of IT, advances in cloud-based ML services, etc.

Course in InSIS – 4IT370
Date: 20-22 May 2024
3 ECTS
Registrations: are already open (will be closed on April 30 or when the capacity will be full)

 

Large volumes and complexity of data that organizations manage today is challenging traditional approaches to data management. To address such challenges relational databases have introduced a range of advanced features that support the management of complex data objects at scale. More recently, a new generation of non-relational databases known as NoSQL have emerged. NoSQL databases include a diverse range of products designed to manage large volumes of different types of data using cloud infrastructure. In this 3-day course we discuss the motivation for NoSQL and cover a range of advanced database techniques with practical demonstrations and hands-on exercises using leading NoSQL databases, including MongoDB and Neo4J.

Course Content

• Introduction: Data management challenges, benefits and limitations of relational databases
• Advanced SQL features: User Defined Types, Collections, Object types and methods, etc.
• Management of semi-structured data: XML and JSON data types, XQuery
• Overview of NoSQL databases: Document databases, Column databases, Graph databases, Data Lakes, Lakehouses, In-memory databases, etc.
• NoSQL concepts and techniques: horizontal scalability and sharding, schema-less data, CAP theorem, data replication and BASE consistency
• NoSQL databases: MongoDB, Neo4j, etc.
• AWS database services: Amazon DynamoDB, AWS Athena, etc.
• Summary: SQL vs NoSQL- benefits and drawbacks, future developments
• Practical hand-on exercises using a selection of NoSQL database

Presenter

Dr George Feuerlicht is an Associate Professor at the Department of Information Technologies at the Unicorn University and a visiting lecturer at the Prague University of Economics and Business. George has been involved in database research and teaching for over three decades. He has presented seminars and professional development courses in Australia, Europe, Asia and USA. He is the author of over 100 publications across a range of topics in computer science. He holds a PhD in Electrical Engineering from the Imperial College, London University, U.K.

Course in InSIS – 4IT482
Date: 22-24 January 2024, exam – 26 January, 2024
3 ECTS
Registrations: are open from 23 October 2023
your own laptop is requried

 

Dr George Feuerlicht is an Associate Professor at the Department of Information Technologies at the Unicorn University and a visiting lecturer at the Prague University of Economics and Business. George has been involved in database research and teaching for over three decades. He has presented seminars and professional development courses in Australia, Europe, Asia and USA. He is the author of over 100 publications across a range of topics in computer science. He holds a PhD in Electrical Engineering from the Imperial College, London University, U.K.

 

Cloud computing has become the dominant approach for the implementation of information systems with many government and private organizations migrating their entire IT infrastructure to the cloud. Most recently, AI and ML (Machine Learning) services, available on leading cloud platforms, have provided a new motivation for the adoption of cloud computing. Most experts today recognize the benefits of cloud computing that include fast implementation, cost reduction and a potential for rapid innovation. However, the fast rate of evolution of cloud technologies and the complexity of managing large-scale cloud deployments represent a challenge for organizations making the transition into the cloud. This three-day course aims to provide the attendees with a balanced view of cloud computing covering the basic cloud concepts and terminology and discussing the benefits and challenges of cloud adoption. The course includes demonstrations and practical hands-on exercises using Amazon Web Services, including EC2, S3, Lambda, RDS and NoSQL databases and a range of AI and ML services.

 

Course Content

• Introduction to cloud computing: current IT technology trends, business motivations and
  technology drivers, benefits and challenges, cloud vs on premises IT, cloud computing in
  a historical context, cloud computing case studies
• Cloud computing concepts and terminology: SOA services, APIs, virtual machines and
  containers, serverless computing, DevOps and microservices, cloud computing service
  models (SaaS, IaaS, PaaS, etc.), cloud computing deployment models (public, private, and
  hybrid clouds), multitenancy and polymorphic applications, etc.
• Cloud databases: SQL and NoSQL databases, document databases, column databases,
  graph databases, etc. CAP theorem and BASE consistency, tunable consistency, NoSQL
  examples: MongoDB, Amazon DynamoDB, Neo4J, AWS Athena, etc.
• Public cloud platforms: AWS, Azure, Google Cloud Platform. AWS core services: EC2, EBS,
  S3, RDS (Oracle, DynamoDB, Amazon Aurora), ML, etc.Cloud computing architectures and open source frameworks: NIST Reference
  Architecture, Kubernetes, Cloud Foundry, etc.
• Cloud computing adoption: migration readiness and planning, migration strategies,
  AWS Adoption Framework
• Future directions: Industrialization of IT, IoT, Machine Learning, etc.