Artificial Intelligence with PythonLaajuus (3 cr)
Code: TT00EV76
Credits
3 op
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
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2024 - 31.07.2024
Timing
01.08.2024 - 31.07.2025
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
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
Evaluation scale
0-5
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2024 - 31.07.2024
Timing
01.08.2024 - 31.07.2025
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
Groups
-
VIOPE_NonStop7VIOPE_NonStop7
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Timing
16.04.2024 - 31.12.2025
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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_2025_MAKSULLINEN_JARJESTELMAOpen UAS 2025
-
VIOPE_2024_MAKSULLINEN_JARJESTELMAViope TiVi (NonStop), year 2024
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.
Timing
01.01.2024 - 31.12.2026
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 10000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
Verkko_opinnot_NonStop_120_opPath Studies (TiVi-NonStop), 120 ECTS
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 and CampusOnline Student via https://hakija.oma.metropolia.fi/
Metropolia's Degree Student: 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
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.
Timing
01.01.2024 - 31.12.2025
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
AVOIN_AMK_TIVI_73_opComplementary Informatics past graduate degree
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.
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.
Timing
01.01.2024 - 31.07.2025
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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_2024_MAKSULLINEN_JARJESTELMAViope TiVi (NonStop), year 2024
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.
Timing
01.01.2024 - 31.12.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 3000
Degree programmes
- Information and Communication Technology
Teacher in charge
Janne Salonen
Groups
-
ATX23_24_Tiedolla_johtamisen_asTiedolla johtamisen asiantuntija johdon päätöksen teon tukitehtäviin
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.
Enrollment
02.07.2024 - 31.07.2024
Timing
01.01.2024 - 31.07.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
Groups
-
VIOPE_NonStop6VIOPE_NonStop6
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2024 - 31.07.2024
Timing
01.01.2024 - 31.07.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
Groups
-
Viope_nonstop_11Viope_nonstop_11
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2024 - 31.07.2024
Timing
01.01.2024 - 31.07.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
Groups
-
Viope_nonstop_12Viope_nonstop_12
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2024 - 31.07.2024
Timing
01.01.2024 - 31.07.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
Groups
-
Viope_nonstop_13Viope_nonstop_13
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2023 - 31.07.2023
Timing
01.08.2023 - 31.07.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teacher in charge
Janne Salonen
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2023 - 31.07.2023
Timing
01.08.2023 - 31.07.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teacher in charge
Janne Salonen
Groups
-
Viope_nonstop_9Viope_nonstop_9
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.07.2023 - 31.07.2023
Timing
01.08.2023 - 31.07.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Campus
Karaportti 2
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
02.12.2022 - 31.12.2022
Timing
01.01.2023 - 31.07.2024
Number of ECTS credits allocated
3 op
Mode of delivery
Contact teaching
Teaching languages
- Finnish
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
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
Evaluation scale
Hyväksytty/Hylätty
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Enrollment
29.01.2024 - 05.03.2024
Timing
05.03.2024 - 30.04.2024
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Campus
Karaportti 2
Teaching languages
- English
Degree programmes
- Information and Communication Technology
Teachers
- Janne Salonen
Teacher in charge
Janne Salonen
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
Evaluation scale
0-5
Assessment criteria, approved/failed
After student has done 80% of course he/she get's grading pass.
Timing
01.08.2023 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
-
ATX22TV_Study_PackagesOpen UAS: NonStop Study Packages
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.
Timing
16.06.2023 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop3VIOPE_NonStop3
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.
Timing
16.06.2023 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
16.06.2023 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
16.06.2023 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop5VIOPE_NonStop5
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.
Timing
07.02.2023 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 100
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
- Virve Prami
Teacher in charge
Janne Salonen
Groups
-
CareerBoost_TXK_21Career Boost 21 (Tivi)
-
CareerBoost_TXK_22Career Boost 22 (TiVi)
-
Career_Boost_TXK_21Career Boost 2021 (TiVi)
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop3VIOPE_NonStop3
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop3VIOPE_NonStop3
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop3VIOPE_NonStop3
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.
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop5VIOPE_NonStop5
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop5VIOPE_NonStop5
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.
Timing
31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop5VIOPE_NonStop5
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.
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.
Timing
14.09.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop3VIOPE_NonStop3
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.
Timing
14.09.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 5000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop3VIOPE_NonStop3
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.
Timing
14.09.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
14.09.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
14.09.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 5000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop4VIOPE_NonStop4
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.
Timing
14.09.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop5VIOPE_NonStop5
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.
Timing
14.09.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 5000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop5VIOPE_NonStop5
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.
Timing
01.08.2022 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
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.
Timing
01.08.2022 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
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.
Timing
01.08.2022 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
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.
Timing
01.08.2022 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
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.
Timing
01.08.2022 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
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.
Timing
01.08.2022 - 31.12.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
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.
Timing
01.08.2022 - 31.07.2023
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
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
-
CareerBoost_TXK_21Career Boost 21 (Tivi)
-
CareerBoost_TXK_22Career Boost 22 (TiVi)
-
Career_Boost_TXK_21Career Boost 2021 (TiVi)
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.
Timing
24.05.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 5000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStop3VIOPE_NonStop3
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.
Timing
01.01.2022 - 31.12.2022
Number of ECTS credits allocated
3 op
Virtual portion
3 op
Mode of delivery
Distance learning
Unit
School of ICT
Campus
Karaportti 2
Teaching languages
- English
Seats
0 - 1000
Degree programmes
- Information and Communication Technology
Teachers
- Mika Hyyryläinen
Groups
-
VIOPE_NonStopViope (NonStop)
-
VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄViope TiVi (NonStop), year
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 and CampusOnline Student via https://hakija.oma.metropolia.fi/
Metropolia's Degree Student: 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
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.