Artificial intelligence with Python (3 cr)
Code: TT00EV76-3043
General information
- Timing
-
01.08.2022 - 31.12.2023
Implementation has ended.
- 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
- Mika Hyyryläinen
- Virve Prami
- Teacher in charge
- Janne Salonen
- Groups
-
VIOPE_NonStop7VIOPE_NonStop7
- Course
- TT00EV76
Objective
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
Location and time
Course is delivered via Metropolia's Viope environment and it can be done in own pace.
Materials
Online.
Teaching methods
100% online (Self-Study) course.
Employer connections
N/A
Exam schedules
Online.
International connections
N/A
Completion alternatives
None.
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
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
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.