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
-
R54D21SBachelor 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.