Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
LEARNING OUTCOMES
After the course, the student knows how to carry out a scientific project and write a scientific report in the field of computer and information science.
Credits: 5
Schedule: 16.09.2020 - 26.05.2021
Teacher in charge (valid 01.08.2020-31.07.2022): Jorma Laaksonen
Teacher in charge (applies in this implementation): Jorma Laaksonen
Contact information for the course (applies in this implementation):
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
A project work, done alone or in a group, from the field of machine learning, data science and artificial intelligence.
Assessment Methods and Criteria
Valid 01.08.2020-31.07.2022:
Assesment based on the report and presentation.
Workload
Valid 01.08.2020-31.07.2022:
Seminars. independent or group work (discussions with supervisor, programming, reporting, presentation and its preparation).
DETAILS
Substitutes for Courses
Valid 01.08.2020-31.07.2022:
Substitutes course CS-E4870 Research Project in Machine Learning and Data Science
Prerequisites
Valid 01.08.2020-31.07.2022:
Sufficient courses in machine learning, data science and artificial intelligence
FURTHER INFORMATION
- Teacher: Laaksonen Jorma