Data science (5 cr)
Code: RO00FQ48-3001
General information
- Enrollment
- 02.12.2024 - 31.12.2024
- Registration for the implementation has ended.
- Timing
- 01.01.2025 - 30.04.2025
- Implementation has ended.
- Number of ECTS credits allocated
- 5 cr
- Local portion
- 5 cr
- Mode of delivery
- Contact learning
- Unit
- Department of Construction and Energy Engineering
- Campus
- Kouvola Campus
- Teaching languages
- Finnish
- Teacher in charge
- Henry Lähteenmäki
- Groups
-
ROKV23SPRobotics and artificial intelligence, full-time studies
- Course
- RO00FQ48
Objective
You understand how machine learning relates to data science.
You know the basics of data collection.
You are familiar with statistical methods used in exploratory data analysis.
You understand the significance of statistics in data science.
You can apply machine learning models in data science.
You can program advanced machine and deep learning models
Content
What machine learning models are used in data science?
How are advanced machine learning models programmed and fine-tuned?
What are the application areas of machine learning?
What is meant by statistical methods in data science?
Evaluation
a. use professional vocabulary and concepts extensively and proficiently in different situations.
b. justify their information sources in a versatile and critical way.
c. work innovatively and independently in working life expert duties and creatively identify and solve the problems of the professional field.
d. promote and develop operations in customer/client, user and target group situations.
e. assess and develop models, methods, software and techniques.
f. manage and develop team work.
g. promote the application of ethical principles in unfamiliar situations.
Evaluation scale
1-5
Qualifications
Advanced knowledge of machine learning and deep learning is required.