Data analysis (5 cr)
Code: RO00FQ46-3001
General information
- Enrollment
- 14.12.2024 - 31.03.2025
- Registration for the implementation has ended.
- Timing
- 13.01.2025 - 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
- English
- Degree programmes
- Degree Programme in Robotics and Artificial Intelligence
- Teachers
- Henry Lähteenmäki
- Teacher in charge
- Henry Lähteenmäki
- Groups
-
ROKV23SPRobotics and artificial intelligence, full-time studies
- Course
- RO00FQ46
Objective
You understand the use of different libraries in data analysis.
You know how to use programming-based computation in data processing.
You understand the basics of data wrangling in programming.
You can use data visualization to gain insights from data.
You know how to prepare data for machine learning.
Content
How are different libraries used in data analysis?
How is data analysis related to machine learning?
What types of computation are used in data analysis?
How is data processed?
Why is data visualized?
How is data prepared to be suitable for machine learning models?
Evaluation
a. use professional vocabulary systematically.
b. look for information in the key information sources of the field.
c. identify interrelated tasks.
e. use the key models, methods, software and techniques of the professional field.
g. justify their actions according to the ethical principles of the professional field.
Course material
Lecture notes and calculations.
Study forms and methods
Final exam.
RDI and work-related cooperation
This course does not include RDI and work-related cooperation.
Evaluation scale
1-5
Qualifications
Knowledge of programming, object-oriented programming, and mathematics is required.