Course GIK2NX

Distributed Computing

7.5 Credits
First Cycle

Starts week 45, 2022

The overall goal of the course is that students acquire knowledge and skills in collecting and processing data from a heterogeneous computerised environment including distributed sensor units, clients and servers.

After completing the course, students will be able to:

Knowledge and Understanding

  • Describe concepts related to software agents, multi-agent systems, and autonomous and distributed systems
  • Describe properties and concepts of distributed and parallel systems.

Skills and Abilities

  • Implement software agents with the support of multi-agent frameworks
  • Configure, manage and develop applications for computers with limited memory
  • Conduct data analysis related to distributed systems
  • Apply scientific approaches in the planning, design, implementation and presentation of quantitative studies

Evaluation Ability and Approach

  • Argue for selected methods and techniques in artificial intelligence, data science or statistical analysis for problem solving
  • Evaluate the results of analysed collected data and suggest improvements
Starts and ends:
week 45, 2022 - week 2, 2023
Study Rate:
50%
Location:
Borlänge
Time of Day:
Day
Teaching form:
Normal
Language:
English
Entry Qualifications:
  • Artificial intelligence 7,5 credits and Statistical Analysis 7,5 credits or Data Science och Machine Learning 7,5 credits
  • Object-Oriented Design and Problem-Solving, 7.5 credits
  • Research Methodology 7.5 credits First Cycle
  • Database Systems, 7.5 credits First Cycle
Application Code:
HDA-H3CN7
Main field of study:
Literature List

Literature lists are published at the latest one month ahead of the course start date.

To Literature List
How may we help you?

Ask us about studying at Dalarna University.
support@du.se
+46 23-77 88 88

Course room in Learn

In the learning platform Learn you can find more information about the course.

Visit the course room
Course Coordinator

Starts week 45, 2023

The overall goal of the course is that students acquire knowledge and skills in collecting and processing data from a heterogeneous computerised environment including distributed sensor units, clients and servers.

After completing the course, students will be able to:

Knowledge and Understanding

  • Describe concepts related to software agents, multi-agent systems, and autonomous and distributed systems
  • Describe properties and concepts of distributed and parallel systems.

Skills and Abilities

  • Implement software agents with the support of multi-agent frameworks
  • Configure, manage and develop applications for computers with limited memory
  • Conduct data analysis related to distributed systems
  • Apply scientific approaches in the planning, design, implementation and presentation of quantitative studies

Evaluation Ability and Approach

  • Argue for selected methods and techniques in artificial intelligence, data science or statistical analysis for problem solving
  • Evaluate the results of analysed collected data and suggest improvements
Starts and ends:
week 45, 2023 - week 2, 2024
Study Rate:
50%
Location:
Borlänge
Time of Day:
Day
Teaching form:
Normal
Language:
English
Other:
P: Course only offered as part of programme.
Entry Qualifications:
  • Artificial intelligence 7,5 credits and Statistical Analysis 7,5 credits or Data Science och Machine Learning 7,5 credits
  • Object-Oriented Design and Problem-Solving, 7.5 credits
  • Research Methodology 7.5 credits First Cycle
  • Database Systems, 7.5 credits First Cycle
Application Code:
HDA-H3EXE
Main field of study:
Tuition Fee
First Tuition Fee Installment:
16,875 SEK
Total Tuition Fee:
16,875 SEK
EU/EEA Citizens or exchange students are not required to pay fees.
Information on application and tuition fees: www.universityadmissions.se.
Literature List

Literature lists are published at the latest one month ahead of the course start date.

To Literature List
How may we help you?

Ask us about studying at Dalarna University.
support@du.se
+46 23-77 88 88

Course Coordinator