AI and Machine LearningLaajuus (5 cr)
Code: R504TL137
Credits
5 op
Teaching language
- Finnish
Enrollment
24.03.2025 - 14.09.2025
Timing
15.09.2025 - 30.11.2025
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- Finnish
Seats
0 - 50
Degree programmes
- Degree Programme in Information and Communication Technology
Teachers
- Mikko Pajula
Responsible person
Mikko Pajula
Student groups
-
R54T22SBachelor of Engineering, Information Technology (full time day studies), autumn 2022
Materials
All the necessary course materials will be compiled and made available via the Moodle workspace.
Self-study prerequisites, if not familiar: Basics of Python:
Familiarity with the basic concepts and syntax of the Python programming language. Basics of Data Management: Understanding of fundamental aspects of data handling, including JSON and databases. Basics of Information Technology: Knowledge of key IT concepts, including understanding what a CPU and GPU are.
Teaching methods
Face-to-face teaching in classroom, online material and assignments
Content scheduling
- Introduction to Artificial Intelligence and Machine Learning: Applications and Utilization Opportunities
- Machine Learning Algorithms and Methods, such as Regression Analysis, Decision-Making Algorithms
- Supervised and Unsupervised Classification Algorithms, Principal Component Analysis
- Application Examples and Project Work
- Machine Learning Platforms and Libraries
Evaluation scale
H-5
Assessment methods and criteria
Grades are based on the quality, quantity, and comprehensiveness of the exercises.
Enrollment
24.03.2025 - 14.09.2025
Timing
15.09.2025 - 12.12.2025
Credits
5 op
Virtual proportion (cr)
5 op
Mode of delivery
Distance learning
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- Finnish
Degree programmes
- Degree Programme in Information and Communication Technology
Teachers
- Mikko Pajula
Responsible person
Mikko Pajula
Student groups
-
RA54T22SBachelor of Engineering, Information Technology (online studies), autumn 2022
Materials
All the necessary course materials will be compiled and made available via the Moodle workspace.
Self-study prerequisites, if not familiar: Basics of Python:
Familiarity with the basic concepts and syntax of the Python programming language. Basics of Data Management: Understanding of fundamental aspects of data handling, including JSON and databases. Basics of Information Technology: Knowledge of key IT concepts, including understanding what a CPU and GPU are.
Teaching methods
Online material. Practical exercise support offered in workshops
Content scheduling
- Introduction to Artificial Intelligence and Machine Learning: Applications and Utilization Opportunities
- Machine Learning Algorithms and Methods, such as Regression Analysis, Decision-Making Algorithms
- Supervised and Unsupervised Classification Algorithms, Principal Component Analysis
- Application Examples and Project Work
- Machine Learning Platforms and Libraries
Evaluation scale
H-5
Assessment methods and criteria
Grades are based on the quality, quantity, and comprehensiveness of the exercises.
Enrollment
18.03.2024 - 31.07.2024
Timing
01.08.2024 - 31.12.2024
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- Finnish
Seats
0 - 50
Degree programmes
- Degree Programme in Information and Communication Technology
Teachers
- Mikko Pajula
Responsible person
Mikko Pajula
Scheduling groups
- In-person group (Size: 0. Open UAS: 0.)
- Online Group (Size: 0. Open UAS: 0.)
Student groups
-
R54T21SBachelor of Engineering, Information Technology (full time day studies), autumn 2021
-
RA54T21SBachelor of Engineering, Information Technology (online studies), autumn 2021
Education groups
- In-person group
- Online Group
Evaluation scale
H-5