Big Data EngineeringLaajuus (5 op)
Tunnus: TT00CN70
Laajuus
5 op
Osaamistavoitteet
After completing the course the student can:
- describe basic solutions for data architectures and big data
- select and use suitable data architecture
- apply ETL process and tools for handling of big data
Sisältö
Architecture and Components of Big Data Frameworks
ETL process with Big Data for batch and streaming
Practical work with suitable tools and frameworks
Ilmoittautumisaika
29.11.2023 - 18.01.2024
Ajoitus
08.01.2024 - 30.04.2024
Opintopistemäärä
5 op
Toteutustapa
Lähiopetus
Yksikkö
Tekniikka ja liiketoiminta
Toimipiste
Kupittaan kampus
Opetuskielet
- Englanti
Paikat
10 - 50
Koulutus
- Tieto- ja viestintätekniikan koulutus
- Tietojenkäsittelyn koulutus
- Degree Programme in Information and Communications Technology
Opettaja
- Tommi Tuomola
Vastuuopettaja
Tommi Tuomola
Ryhmät
-
PTIETS22deaiPTIETS22 Datatekniikka ja Tekoäly
-
PTIVIS22IData Engineering and AI
Tavoitteet
After completing the course the student can:
- describe basic solutions for data architectures and big data
- select and use suitable data architecture
- apply ETL process and tools for handling of big data
Sisältö
Architecture and Components of Big Data Frameworks
ETL process with Big Data for batch and streaming
Practical work with suitable tools and frameworks
Oppimateriaalit
Teacher provided lecture material
Supporting public online material
Teacher provided virtual machines
All needed material (or at least a link to them) will be available in itslearning.
Opetusmenetelmät
Contact learning, practical exercises, independent study
Pedagogiset toimintatavat ja kestävä kehitys
Given examples and exercises support each topic studied during the lectures. Additional material in the form of tutorials and reliable information sources is provided.
Opiskelijan ajankäyttö ja kuormitus
Contact hours 56 h
Inpendent studying 79h, including:
- Studying the course material
- Completing exercises
- Project
Sisällön jaksotus
-The basic idea of data engineering methods and pipelines
-different components
-integration of said components (MQ systems)
-data engineering frameworks (Apache family)
-The goal of the course is to be able to build a data pipeline from start to finish
Viestintäkanava ja lisätietoja
Itslearning and contact classes are the main communication channels used on this course.
The student is required to have a computer capable of running a simple Ubuntu virtual machine.
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
Homework exercises returned throughout the course
Small project at the end of the course
Ilmoittautumisaika
02.12.2023 - 16.01.2024
Ajoitus
01.01.2024 - 30.04.2024
Opintopistemäärä
5 op
Toteutustapa
Lähiopetus
Yksikkö
Tekniikka ja liiketoiminta
Toimipiste
Kupittaan kampus
Opetuskielet
- Englanti
Paikat
20 - 40
Koulutus
- Tieto- ja viestintätekniikan koulutus
- Degree Programme in Information and Communications Technology
Opettaja
- Tommi Tuomola
Vastuuopettaja
Tommi Tuomola
Ryhmät
-
PTIVIS21HTerveysteknologia
Tavoitteet
After completing the course the student can:
- describe basic solutions for data architectures and big data
- select and use suitable data architecture
- apply ETL process and tools for handling of big data
Sisältö
Architecture and Components of Big Data Frameworks
ETL process with Big Data for batch and streaming
Practical work with suitable tools and frameworks
Oppimateriaalit
Teacher provided lecture material
Supporting public online material
Teacher provided virtual machines
All needed material (or at least a link to them) will be available in itslearning.
Opetusmenetelmät
Contact learning, practical exercises, independent study
Pedagogiset toimintatavat ja kestävä kehitys
Given examples and exercises support each topic studied during the lectures. Additional material in the form of tutorials and reliable information sources is provided.
Opiskelijan ajankäyttö ja kuormitus
Contact hours 56 h
Inpendent studying 79h, including:
- Studying the course material
- Completing exercises
- Project
Sisällön jaksotus
-Introduction to data engineering
-The basic idea of data engineering methods and pipelines
-different components
-integration of said components (MQ systems)
-data engineering frameworks (Apache family)
Viestintäkanava ja lisätietoja
Itslearning and contact classes are the main communication channels used on this course.
The student is required to have a computer capable of running a simple Ubuntu virtual machine.
Arviointiasteikko
H-5
Arviointimenetelmät ja arvioinnin perusteet
Homework exercises returned throughout the course
Small project at the end of the course