AI programmingLaajuus (5 cr)
Code: IT23ABC01
Credits
5 op
Objective
The goal is to learn how to program real-time systems, and understand machine learning
Content
-Node.js
- Azure ML and Stream Analytics
- Tensorflow.js
Qualifications
All year 3 courses
Assessment criteria, satisfactory (1)
At least 10p/30p
Assessment criteria, good (3)
At least 18p/30p
Assessment criteria, excellent (5)
At least 26p/30p
Materials
Moodle
Enrollment
01.12.2024 - 26.01.2025
Timing
27.01.2025 - 27.04.2025
Number of ECTS credits allocated
5 op
Mode of delivery
Contact teaching
Unit
Faculty of Technology and Seafaring
Campus
Vasa, Wolffskavägen 33
Teaching languages
- English
- Svenska
Degree programmes
- Degree Programme in Information Technology
- Degree Programme in Information Technology
Teachers
- Kaj Wikman
Teacher in charge
Kaj Wikman
Groups
-
ITE23D-VInformation Technology, full time studies 2023, Vasa
Objective
The goal is to learn how to program real-time systems, and understand machine learning
Content
-Node.js
- Azure ML and Stream Analytics
- Tensorflow.js
Location and time
Spring, Vasa
Materials
Moodle
Teaching methods
The course is based on lectures, self-study and exercises in a classroom environment. The labs are compulsory.
Exam schedules
Spring
Student workload
About 50% attendance studies and about 50% self-study.
Evaluation scale
H-5
Assessment criteria, satisfactory (1)
At least 10p/30p
Assessment criteria, good (3)
At least 18p/30p
Assessment criteria, excellent (5)
At least 26p/30p
Assessment methods and criteria
Of the marks of the examination questions, you must obtain at least 33% in order to obtain a grade in the course, irrespective of the total score of the exams. 33% for pass, per exam. In total, 33% is applied for approved and linear scale.
Assessment criteria, satisfactory (1-2)
At least 10p/30p
Assessment criteria, good (3-4)
At least 18p/30p
Assessment criteria, excellent (5)
At least 26p/30p
Qualifications
All year 3 courses