Data analytics and artificial intelligence (4cr)
Code: C-02504-TT00CD84-3004
General information
- Enrollment
- 04.08.2025 - 31.08.2025
- Registration for the implementation has begun.
- Timing
- 25.08.2025 - 16.11.2025
- The implementation has not yet started.
- Number of ECTS credits allocated
- 4 cr
- Institution
- JAMK University of Applied Sciences, Verkkototeutus
- Teaching languages
- Finnish
- Seats
- 0 - 5
- Course
- C-02504-TT00CD84
Evaluation scale
0-5
Objective
In the course, you will get an overview of the methods, possibilities and applications of data analytics and artificial intelligence, as well as the most common programming environments and libraries used in them. EUR-ACE Knowledge and understanding You understand the key concepts of data analytics and artificial intelligence. In addition, you will recognize the different stages of data processing and the libraries suitable for them. EUR-ACE Engineering practice You know how to choose libraries suitable for different stages of data analytics and machine learning and use them as part of data processing.
Content
This course will give you a comprehensive overview of the methods, possibilities and applications of data analytics and artificial intelligence. You will learn to understand the key concepts and identify the different stages of data processing and the libraries that can be used for them. You will be able to select and use libraries suitable for the different stages of data analytics and machine learning in practical data processing. This course will enable you to apply data analytics and artificial intelligence methods in a variety of situations. Data sources Data analysis Data visualisation Machine learning
Location and time
Online implementation
Materials
Course material page (lecture materials, exercises)
Teaching methods
- Online implementation, with 5 online guidance sessions during the semester - During the guidance session, selected demos selected by the teacher are reviewed and students are also offered guidance on exercises
Completion alternatives
The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.
Student workload
Distance learning 98 h (environment preparation, familiarisation with the material, exercises) Online demos led by the teacher and guidance sessions 10 h Total 108 h
Qualifications
Basics of Programming