LEARNING OUTCOMES
After the course, the student knows how to carry out a scientific project and write a scientific report in the field of machine learning, data science and artificial intelligence.
Credits: 5 - 10
Schedule: 18.09.2024 - 31.07.2025
Teacher in charge (valid for whole curriculum period):
Teacher in charge (applies in this implementation): Jorma Laaksonen
Contact information for the course (applies in this implementation):
Jorma Laaksonen <jorma.laaksonen@aalto.fi> room B326 in the CS building.
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:
A project work, done either alone or in a group, from the field of machine learning, data science and artificial intelligence. Students can either 1) report the research work carried out during their internships, 2) find a topic and supervisor by themselves, or 3) select a topic among available ones in a matchmaking process run in September.
Assessment Methods and Criteria
valid for whole curriculum period:
Assesment based on the report and presentation.
Workload
valid for whole curriculum period:
Independent or group work including discussions with a supervisor, programming, experimenting, reporting and presenting the results.
applies in this implementation
One ECTS credit point matches 27 hours of work.
DETAILS
Substitutes for Courses
valid for whole curriculum period:
Prerequisites
valid for whole curriculum period:
SDG: Sustainable Development Goals
1 No Poverty
2 Zero Hunger
3 Good Health and Well-being
4 Quality Education
5 Gender Equality
6 Clean Water and Sanitation
7 Affordable and Clean Energy
8 Decent Work and Economic Growth
9 Industry, Innovation and Infrastructure
10 Reduced Inequality
11 Sustainable Cities and Communities
12 Responsible Production and Consumption
13 Climate Action
14 Life Below Water
15 Life on Land
16 Peace and Justice Strong Institutions
17 Partnerships for the Goals
FURTHER INFORMATION
Further Information
valid for whole curriculum period:
Teaching Language: English
Teaching Period: 2024-2025 Autumn I - Summer
2025-2026 No teachingRegistration:
The course is primarily available for major students in CCIS Machine Learning, Data Science and Artificial Intelligence (Macadamia) and exit year students in EIT Digital Master School's Data Science major. Other students need to contact the responsible teacher before enrolling.
applies in this implementation
Academic year 2024–2025 is the last implementation of the course.
Details on the schedule
applies in this implementation
The last day to submit the project reports is 30.7.2025.