LEARNING OUTCOMES
Knowledge of core computational methods in human-computer interaction; Ability to formulate and solve realistic interaction problems using computational approaches.
Credits: 5
Schedule: 22.10.2024 - 05.12.2024
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Antti Oulasvirta
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:
Applications of optimization, Bayesian inference, reinforcement learning, and deep learning. Contents are updated every year to reflect state-of-the-art topics in HCI research.
Assessment Methods and Criteria
valid for whole curriculum period:
Exam, assignments.
Workload
valid for whole curriculum period:
Contact hours (can include class discussions led by the teacher and by students, guest speaker sessions, in-class workshops). Individual studies outside the classroom. This course includes active participation in assignments and lectures and is not designed for part-time engagement. Teams might be assigned by the teacher.
DETAILS
Study Material
valid for whole curriculum period:
Notebooks, lectures, readings.
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
8 Decent Work and Economic Growth
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn II
2025-2026 Autumn II