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Distributed Systems (5 cr)

Code: R504D77-3001

General information


Enrollment

13.03.2023 - 24.09.2023

Timing

25.09.2023 - 10.12.2023

Credits

5 op

Mode of delivery

Contact teaching

Unit

Bachelor of Engineering, Information Technology

Teaching languages

  • English

Seats

0 - 35

Degree programmes

  • Machine Learning and Data Engineering

Teachers

  • Juha Petäjäjärvi

Responsible person

Juha Petäjäjärvi

Student groups

  • R54D21S
    Bachelor of Engineering, Machine Learning and Data Engineering (full time studies), 2021

Objective

The student is familiar with the features and key benefits of distributed systems. The student can create distributed applications in the cloud.

Content

- Common terminology, e.g. vertical vs. horizontal scaling, decentralized vs. distributed.
- The key features and benefits of distributed systems: fault tolerancy; low latency; scalability
- The categories of distributed systems and their common applications: distributed data stores; distributed computing; distributed file systems; distributed messaging systems; distributed ledgers and distributed applications

Teaching methods

Classroom teaching and excercises. Materials will be in Moodle.

Content scheduling

- Common terminology, e.g. vertical vs. horizontal scaling, decentralized vs. distributed.
- The key features and benefits of distributed systems: fault tolerancy; low latency; scalability
- The categories of distributed systems and their common applications: distributed data stores; distributed computing; distributed file systems; distributed messaging systems; distributed ledgers and distributed applications

Evaluation scale

H-5

Assessment criteria, satisfactory (1)

The student is familar with the key features and benefits of distributed systems and some of their common applications.

Assessment criteria, good (3)

The student is familar with the key features and benefits of distributed systems and some of their common applications. The student knows how the distribution is used in some common applications to improve their latency, fault tolerancy and scalability.

Assessment criteria, excellent (5)

The student is familar with the key features and benefits of distributed systems and some of their common applications. The student can apply distribution to improve the latency, fault tolerancy and scalability of systems.

Assessment methods and criteria

This study unit is evaluated according to the student performance on assignments.

Assessment criteria, satisfactory (1-2)

The student is familar with the key features and benefits of distributed systems and some of their common applications.

Assessment criteria, good (3-4)

The student is familar with the key features and benefits of distributed systems and some of their common applications. The student knows how the distribution is used in some common applications to improve their latency, fault tolerancy and scalability.

Assessment criteria, excellent (5)

The student is familar with the key features and benefits of distributed systems and some of their common applications. The student can apply distribution to improve the latency, fault tolerancy and scalability of systems.