Introduction to Artificial Intelligence (3 ECTS)

Learning outcomes

After completing a course, student has learned what are the basic tehniques to manifest artificial intelligence in practise.

Content

- Introduction
- Data Exploration
- Supervised learning
- Unsupervised learning
- Deep Learning
- Reinforcement learning

Teaching methods

Course is 100% online (Self-Study) course and it can be done in own pace.

Location and time

Course is delivered via Metropolia's Viope environment and it can be done in own pace.

Learning materials and recommended literature

All of course material is online in Metropolia's Viope.

Alternative completion methods of implementation

N/A

Internship and working life connections

N/A

Exam dates and retake possibilities

N/A

International connections

N/A

Student workload

Course is self-study course, so, timetable is totally up to student her-/himself.

Content scheduling

Course is self-study course, so, student can schedule course her-/himself.

Further information for students

ENROLLING

Open UAS Student via https://hakija.oma.metropolia.fi/
CampusOnline Students via eform which can be find via https://campusonline.fi

Metropolia's Degree Student
- Go to https://vw4.viope.com/login?org=metropolia
- Register to system -> Click the link “Enroll on the course”
- Choose any course of (NonStop).
- Fill the others fields

If you have problems with enrolling into this course or questions about it, please contact to viopesupport@metropolia.fi

Assessment methods and criteria

After student has done at least 80% of tasks he/she can get grade pass.

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, approved/failed

After student has done 80% of course he/she get's grading pass.