LEARNING OUTCOMES
At the end of this course, the student can
- describe the main algebraic methods used in data science
- apply these methods
- recognize problems in data science that can be solved using algebraic methods
Credits: 5
Schedule: 07.01.2025 - 04.04.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Kaie Kubjas
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:
See syllabus for each edition.
Assessment Methods and Criteria
valid for whole curriculum period:
Teaching methods: lectures and exercises
Assessment methods: homework and final project
Workload
valid for whole curriculum period:
Contact hours 36h, self-study ca 96h
DETAILS
Study Material
valid for whole curriculum period:
See syllabus for each edition.
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 - IV
2025-2026 No teaching