Datan käsittely ja koneoppiminen (5 cr)
Code: TX00DZ36-3001
General information
Enrollment
04.05.2020 - 30.08.2020
Timing
24.08.2020 - 11.10.2020
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
ICT ja tuotantotalous
Campus
Myllypurontie 1
Teaching languages
- Finnish
Seats
0 - 40
Degree programmes
- Tieto- ja viestintätekniikan tutkinto-ohjelma
Teachers
- Juha Kopu
- Vesa Ollikainen
Groups
-
TVT18-OOhjelmistotuotanto
Objective
After completion of the course, the student understands the possibilities in data handling, modelling and, particularly, machine learning. The course participants have acquired hands-on experience in data storage, retrieval, and manipulation as well as the methods and tools in machine learning.
Content
- Large volumes of data in ICT business: applicability, models, opportunities, and processes, legislative and ethical constraints.
- Data acquisition and preprocessing.
- Data management solutions.
- Machine learning methods (classification, association analysis, clustering, prediction of numeric values) , their fields of use and applicability.
- Machine learning software.
- Validation and visualisation of results.
- Machine learning in natural language processing.
Evaluation scale
0-5
Assessment criteria, satisfactory (1)
The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level.
Assessment criteria, good (3)
The student has achieved the course objectives well, even though the knowledge and skills need improvement on some areas. The student has completed the required learning exercises in good or satisfactory level. The student is able to define the course concepts and models and is able to justify the analysis.
Assessment criteria, excellent (5)
The student has achieved the objectives of the course with excellent marks. The student master commendably the course subject area’s concepts and models. The student has completed the required learning exercises in good or excellent level. The student is able to make justified and fluent analysis.
Assessment criteria, approved/failed
The student has achieved the course objectives fairly. The student will be able to identify, define and use the course subject area’s concepts and models. The student has completed the required learning exercises in minimum requirement level.