LEARNING OUTCOMES
After completing the course the student understands basic principles of time series modelling and forecasting with them, knows several approaches to time series predictions, and can apply the acquired knowledge in various applications.
Credits: 6
Schedule: 07.01.2025 - 12.02.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Lauri Viitasaari
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:
Topics covered include general idea and principles of making predictions, time series modelling and model selection, conditional expectation, non-parametric methods, and parametric methods including AI methods.
Assessment Methods and Criteria
valid for whole curriculum period:
Home assignments and the exam.
Workload
valid for whole curriculum period:
Lectures, exercises and the exam.
DETAILS
Study Material
valid for whole curriculum period:
Lecture slides and other material provided to the students during the course.
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 Spring III
2025-2026 Spring III