Azure Machine Learning (15 op)
Toteutuksen tunnus: TT00EO92-3007
Toteutuksen perustiedot
- Ajoitus
- 01.08.2024 - 17.10.2024
- Toteutus on päättynyt.
- Opintopistemäärä
- 15 op
- Virtuaaliosuus
- 15 op
- Toteutustapa
- Etäopetus
- Toimipiste
- Karaportti 2
- Opetuskielet
- englanti
- Paikat
- 0 - 5000
- Koulutus
- Tieto- ja viestintätekniikan tutkinto-ohjelma
- Opettajat
- Virve Prami
- Vastuuopettaja
- Janne Salonen
- Ryhmät
-
hakijan_työpöydältä_poistetut_toteutuksetMaksullisesta poistetut toteutukset
- Opintojakso
- TT00EO92
Aika ja paikka
Course can be done with own pace in TechClass environment.
Oppimateriaalit
Lecture slides
Tutorial videos
Quizzes
Exercises
Project
Harjoittelu- ja työelämäyhteistyö
N/A
Tenttien ajankohdat ja uusintamahdollisuudet
Online.
Kansainvälisyys
N/A
Toteutuksen valinnaiset suoritustavat
N/A
Arviointimenetelmät ja arvioinnin perusteet
Exercises 50%
Quizzes 25%
Project 25%
Opiskelijan ajankäyttö ja kuormitus
Lectures = 85h
Exercises = 95h
Self-study = 100h
Quizzes = 15h
Project = 65h
Total = 360 hours
Sisällön jaksotus
Up to Student her-/himself.
Opetusmenetelmät
100% online Self-Study course.
- Tutorial Videos
- Exercises
- Quiz
- Project
- Self-study
Arviointiasteikko
Hyväksytty/Hylätty
Arviointikriteerit, tyydyttävä (1)
- The student is familiar with the cloud-based service.
- The student is familiar with about Azure Machine Learning Studio.
- The student knows about how to use Azure Machine Learning Designer service.
- The student is familiar how to train a model using Azure Machine Learning Designer.
- The student is familiar with concept of Automated Machine Learning service in AML.
- The student is familiar with different compute resource in AML.
Arviointikriteerit, hyvä (3)
- The student knows how to use Automated Machine Learning Service to implement and deploy different machine learning models.
- The student knows the how to use Jupyter notebook and run and manage it.
- The student is familiar with different assets in Azure Machine Learning Studio.
- The student is familiar with Azure Machine Learning SDK.
- The student knows how to setup his/her local computer.
- The student knows how to use Azure machine learning compute resource to train his/her models.
- The student is familiar with the concept of Experiment.
- The student is familiar with the concept of Event Grid.
Arviointikriteerit, kiitettävä (5)
- The student knows how to create an environment for his/her model.
- The student can prepare his/her code for deploying different machine learning models.
- The student can understand the technical document of Azure Machine learning Services.
- The student is familiar with Microsoft cognitive service.
- The student knows how transfer learning models work.