Azure Machine Learning (15 op)

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.