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Introduction to Artificial Intelligence (3 cr)

Code: TT00EV75-3072

General information


Timing
01.01.2025 - 30.07.2026
Implementation is running.
Number of ECTS credits allocated
3 cr
Local portion
0 cr
Virtual portion
3 cr
Mode of delivery
Online
Unit
(2019-2024) School of ICT
Campus
Karaportti 2
Teaching languages
English
Seats
0 - 5000
Degree programmes
Information and Communication Technology
Teachers
Virve Prami
Teacher in charge
Janne Salonen
Groups
Viope_nonstop_15
Viope_nonstop_15
Course
TT00EV75
No reservations found for implementation TT00EV75-3072!

Objective

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

Location and time

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

Materials

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

Teaching methods

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

Employer connections

N/A

Exam schedules

N/A

International connections

N/A

Completion alternatives

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

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

Evaluation scale

Hyväksytty/Hylätty

Assessment criteria, approved/failed

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

Assessment methods and criteria

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

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