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Data Engineering projectLaajuus (5 cr)

Code: MS00CN46

Credits

5 op

Objective

After completing the course, the students can
- work in the Data Engineering project
- describe and understand how Data Engineering projects are implemented

Content

Practical project related to Data Engineering

Enrollment

02.12.2024 - 31.12.2024

Timing

01.01.2025 - 31.07.2025

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Campus

Kupittaa Campus

Teaching languages
  • Finnish
  • English
Seats

10 - 25

Degree programmes
  • Master of Engineering, Data Engineering and AI
  • Master of Business Administration, Data Engineering and AI
Teachers
  • Jussi Salmi
Groups
  • YDATIS24
  • YDATTS24

Objective

After completing the course, the students can
- work in the Data Engineering project
- describe and understand how Data Engineering projects are implemented

Content

Practical project related to Data Engineering

Materials

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.

Teaching methods

Contact learning, practical exercises, independent study

International connections

Given examples and exercises support each topic studied during the lectures. Additional material in the form of tutorials and reliable information sources is provided.

Student workload

Contact hours 16 h
Inpendent studying 119h, including:
- Studying the course material
- Completing assignments
- Project

Content scheduling

-The basic idea of data engineering methods and pipelines
-different components
-integration of said components (MQ systems)
-data engineering frameworks (Apache family)

Further information

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.

Evaluation scale

H-5

Assessment methods and criteria

Assignments returned throughout the course
Small project at the end of the course

Enrollment

02.12.2023 - 15.01.2024

Timing

15.01.2024 - 30.04.2024

Number of ECTS credits allocated

5 op

Mode of delivery

Contact teaching

Unit

Engineering and Business

Teaching languages
  • Finnish
  • English
Degree programmes
  • Master of Engineering, Data Engineering and AI
  • Master of Business Administration, Data Engineering and AI
Teachers
  • Tommi Tuomola
Groups
  • YDATIS23
  • YDATTS23

Objective

After completing the course, the students can
- work in the Data Engineering project
- describe and understand how Data Engineering projects are implemented

Content

Practical project related to Data Engineering

Materials

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.

Teaching methods

Contact learning, practical exercises, independent study

International connections

Given examples and exercises support each topic studied during the lectures. Additional material in the form of tutorials and reliable information sources is provided.

Student workload

Contact hours 16 h
Inpendent studying 119h, including:
- Studying the course material
- Completing assignments
- Project

Content scheduling

-The basic idea of data engineering methods and pipelines
-different components
-integration of said components (MQ systems)
-data engineering frameworks (Apache family)

Further information

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.

Evaluation scale

H-5

Assessment methods and criteria

Assignments returned throughout the course
Small project at the end of the course