LEARNING OUTCOMES
After the course, the student
- can explain the fundamentals of neural networks function.
- is able to construct, design, implement and run a deep learning based AI analysis project in medical domain.
- has the skills to select and utilize and the tools for applying AI for the different use cases needed for medical applications.
- is able to identify and develop the data sets that provide the best results.
Credits: 5
Schedule: 03.09.2024 - 12.12.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Leo Kärkkäinen, Simo Särkkä, Aleksei Tiulpin
Contact information for the course (applies in this implementation):
CEFR level (valid for whole curriculum period):
Language of instruction and studies (applies in this implementation):
Teaching language: English. Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
valid for whole curriculum period:
The course will contain the basics in deep learning, introduce the student how machine learning is used in different medical domains, and what technologies are appropriate in different use cases. The work has mathematical and programming exercises, and a project for designing and teaching a neural network for a medical use case.
Assessment Methods and Criteria
valid for whole curriculum period:
Project work, exercises, and final examination
Workload
valid for whole curriculum period:
contact teaching, independent studies
DETAILS
Study Material
valid for whole curriculum period:
See MyCourses
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I - II
2025-2026 Autumn I - II