Cloud Computing and Big Data Analytics

Cloud computing is a service model for large-scale distributed computing based on concentrated infrastructure and a set of collaborative services over which applications can be deployed and run over the network.

This course about Cloud computing has a mainly practical approach dealing with the related technologies. While most computer applications can be deployed in the cloud using the concepts explained, the classes pay particular attention to the creation of Big Data Analytics applications on the Cloud. It is offered to students of both degrees: "Master in Innovation and Research in Informatics" and "Erasmus Mundus Master in Big Data Management and Analytics".

In the lectures of this course, the students will learn the principles and the state of the art of large-scale distributed computing in a service-based model. Students will study how scale affects system properties, models, architecture, and requirements.

In the laboratory sessions of this course, the students will gain a practical view of the latest in Cloud technology to implement a prototype that meets a business idea created by the student.

Class Contents

Lecturer

Angel Toribio-González  ()

Tentative calendar!!!

Class topics and laboratory sessions
Tuesday (Group 11. Laboratory) Thursday (Lectures) Friday (Group 12. Laboratory)
February 12 Environment configuration and warm up 14 Presentation of the subject 15 Environment configuration and warm up
19 Free 21 Introduction to Cloud Computing 22 Basic knowledge toolbox
26 Basic knowledge toolbox 28 Virtualization 1 Doors in the cloud
March 5 Doors in the cloud 7 Cloud computing architecture 8 Extracting and analyzing data from the cloud
12 Extracting and analyzing data from the cloud 14 Cloud computing architecture 15 Creating a web application using cloud PaaS
19 Creating a web application using cloud PaaS 21 Cloud computing architecture 22 Enhancing your web app using additional cloud services
26 Free 28 Best practices for creating SaaS
The twelve factor methodology
Service oriented architectures
29 Enhancing your web app using additional cloud services
April 2 Programming your cloud infrastructure 4 Cloud security 5 Programming your cloud infrastructure
9 Using the Elastic Stack to study scraped data from a web page 11 Cloud security 12 Using the Elastic Stack to study scraped data from a web page
16 Easter break 18 Easter break 19 Easter break
23 Advanced Analytics as a Service in the Cloud 25 Agile and Cloud automation 26 Advanced Analytics as a Service in the Cloud
May 30 Free 2 Free 3 FIB's festivity day
7 Student project development 9 Student research assignment
Pecha Kutcha presentations
10 Student project development
14 Free 16 Student research assignment
Pecha Kutcha presentations
17 Free
21 Student project development 23 Keyonete presentation: New Relic 24 Student project development
29 Free 30 Final exam 31 Free
June 4 Student project development 6 Keynone presentation: Elastic Stack 7 Student project development
11 Student project development 13 Free 14 Student project development
18 Student project
Technical interview
presence required to pre-scheduled interviews
20 Student project
Pecha Kutcha presentations
presence required for all class
21 Student project
Technical interview
presence required to pre-scheduled interviews

Evaluation

Laboratory (teams of 2 persons) 30%
Lab 0 Environment configuration and warm up 0.0%  
Lab 1 Basic knowledge toolbox to get started in the Cloud 5.0%  
Lab 2 Doors in the cloud 5.0%  
Lab 3 Extracting and analyzing data from the cloud 5.0%  
Lab 4 Creating a web application using cloud PaaS 5.0%  
Lab 5 Enhancing your web app using additional cloud services 5.0%  
Lab 6 Programming your cloud infrastructure 5.0%  
Homework (teams of 2 persons) 20%
Lab 7 Using the Elastic Stack to study scraped data from a web page 5.0%  
Lab 8 Advanced Analytics as a Service in the Cloud 5.0%  
Research Topic to read, research and present 10.0%  
Project (teams of 5 persons) 30%
Final exam 20%