Artificial intelligence with Python (3 ECTS)

Learning outcomes

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

Content

- Python Quick Recap
- Python Arrays, Tables, Vectors, Matrices
- AI: Short Description
- AI: Regression 1
- AI: Regression 2
- AI: Classification 1
- AI: Classification 2
- AI: Miscellanae

Teaching methods

100% online (Self-Study) course.

Location and time

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

Learning materials and recommended literature

Online.

Alternative completion methods of implementation

None.

Internship and working life connections

N/A

Exam dates and retake possibilities

Online.

International connections

N/A

Student workload

Course can be done in own pace. So, the timetable is up to student her-/himself.

Content scheduling

Course can be done in own pace. So, student can schedule her/his studies 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 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.