Seminar: Machine Learning and Data Engineering (5 cr)
Code: R504D97-3001
General information
Enrollment
13.03.2023 - 25.09.2023
Timing
11.09.2023 - 17.12.2023
Credits
5 op
Mode of delivery
Contact teaching
Unit
Bachelor of Engineering, Information Technology
Teaching languages
- English
Seats
0 - 30
Teachers
- Jyri Kivinen
- Kenneth Karlsson
Responsible person
Kenneth Karlsson
Student groups
-
R54D23SBachelor of Engineering, Machine Learning and Data Engineering (full time studies), 2023
Objective
Student gains high-level understanding of Machine Learning and Data Engineering (MLDE), learning about fundamental concepts, principles, terminology, applications, relations to other areas of study and is able to form a bigger picture of own professional field.
Content
A series of seminars that cover various themes of machine learning through presentations by students
Location and time
Meetings at Jokiväylä 11, Rovaniemi.
Tentative meeting topics and schedule:
week 37: Course contents, getting started, grading, and other practicalities
week 38: What is AI
week 39: Seminar topics
week 40: AI problem solving
week 41. Real world AI
week 43. Machine learning
week 45. Machine learning
week 47. Neural networks
week 48. Guest lecture
week 49. Student seminar
week 50. Wrap-up
Materials
Elements of AI and materials in Moodle workspace.
Teaching methods
Student gains high-level understanding of Machine Learning and Data Engineering (MLDE), learning about fundamental concepts, principles, terminology, applications, relations to other areas of study and is able to form a bigger picture of own professional field.
A series of seminars that cover various themes of machine learning through presentations by students.
Assessment criteria, approved/failed
Active participation in group work
Active and critical information retrieval
Evaluation scale
Approved/Rejected
Assessment criteria, approved/failed
Approved if the student is actively participating in group work