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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_NonStop7
    VIOPE_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_JARJESTELMA
    Open UAS 2025
  • VIOPE_2024_MAKSULLINEN_JARJESTELMA
    Viope 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_op
    Path 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_op
    Complementary 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_JARJESTELMA
    Viope 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_as
    Tiedolla 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_NonStop6
    VIOPE_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_11
    Viope_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_12
    Viope_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_13
    Viope_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_9
    Viope_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_Packages
    Open 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_NonStop3
    VIOPE_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_NonStop4
    VIOPE_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_NonStop4
    VIOPE_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_NonStop5
    VIOPE_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_21
    Career Boost 21 (Tivi)
  • CareerBoost_TXK_22
    Career Boost 22 (TiVi)
  • Career_Boost_TXK_21
    Career 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_NonStop3
    VIOPE_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_NonStop3
    VIOPE_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_NonStop3
    VIOPE_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_NonStop4
    VIOPE_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_NonStop4
    VIOPE_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_NonStop4
    VIOPE_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_NonStop4
    VIOPE_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_NonStop4
    VIOPE_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_NonStop5
    VIOPE_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_NonStop5
    VIOPE_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_NonStop5
    VIOPE_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_NonStop3
    VIOPE_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_NonStop3
    VIOPE_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_NonStop4
    VIOPE_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_NonStop4
    VIOPE_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_NonStop4
    VIOPE_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_NonStop5
    VIOPE_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_NonStop5
    VIOPE_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_NonStop7
    VIOPE_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_NonStop7
    VIOPE_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_NonStop7
    VIOPE_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_21
    Career Boost 21 (Tivi)
  • CareerBoost_TXK_22
    Career Boost 22 (TiVi)
  • Career_Boost_TXK_21
    Career 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_NonStop3
    VIOPE_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_NonStop
    Viope (NonStop)
  • VIOPE_2022_MAKSULLINEN_JÄRJESTELMÄ
    Viope 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.