Microsoft Azure is a set of cloud computing services that constantly continues to grow. Azure helps your organization solve all kinds of business challenges. With Azure, your organization has the freedom to use your favourite tools and frameworks to develop, manage, and implement applications on a large, global network.
During the course Designing and Implementing a Data Science Solution on Azure (DP-100) you learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.
This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.
The course helps to prepare for exam DP-100.
Lunches and course materials are included. Exam fees are not included.
Deze training wordt in het Nederlands verzorgd.
Module 1: Introduction to Azure Machine Learning
Module 2: No-Code Machine Learning with Designer
Module 3: Running Experiments and Training Models
Module 4: Working with Data
Module 5: Compute Contexts
Module 6: Orchestrating Operations with Pipelines
Module 7: Deploying and Consuming Models
Module 8: Training Optimal Models
Module 9: Interpreting Models
Module 10: Monitoring Models
| Plaats | Duur | Data | ||
|---|---|---|---|---|
| Virtual Classroom | 4 dagen |
27 t/m 30 april 2026
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27 april 2026 09:00 - 16:30 uur 28 april 2026 09:00 - 16:30 uur 29 april 2026 09:00 - 16:30 uur 30 april 2026 09:00 - 16:30 uur |
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| Virtual Classroom | 4 dagen |
26 t/m 29 mei 2026
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26 mei 2026 10:30 - 18:00 uur 27 mei 2026 10:30 - 18:00 uur 28 mei 2026 10:30 - 18:00 uur 29 mei 2026 10:30 - 18:00 uur |
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| PATERSWOLDE - Groningerweg 19 | 4 dagen |
8 t/m 11 juni 2026
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8 juni 2026 09:00 - 16:30 uur 9 juni 2026 09:00 - 16:30 uur 10 juni 2026 09:00 - 16:30 uur 11 juni 2026 09:00 - 16:30 uur |
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| Virtual Classroom | 4 dagen |
8 t/m 11 juni 2026
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8 juni 2026 09:00 - 16:30 uur 9 juni 2026 09:00 - 16:30 uur 10 juni 2026 09:00 - 16:30 uur 11 juni 2026 09:00 - 16:30 uur |
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| Virtual Classroom | 4 dagen |
27 t/m 30 juli 2026
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27 juli 2026 09:00 - 16:30 uur 28 juli 2026 09:00 - 16:30 uur 29 juli 2026 09:00 - 16:30 uur 30 juli 2026 09:00 - 16:30 uur |
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| Virtual Classroom | 4 dagen |
24 t/m 27 augustus 2026
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24 augustus 2026 10:30 - 18:00 uur 25 augustus 2026 10:30 - 18:00 uur 26 augustus 2026 10:30 - 18:00 uur 27 augustus 2026 10:30 - 18:00 uur |
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| AMSTERDAM - Teleportboulevard 100 | 4 dagen |
1 t/m 4 september 2026
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1 september 2026 09:00 - 16:30 uur 2 september 2026 09:00 - 16:30 uur 3 september 2026 09:00 - 16:30 uur 4 september 2026 09:00 - 16:30 uur |
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| Virtual Classroom | 4 dagen |
1 t/m 4 september 2026
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1 september 2026 09:00 - 16:30 uur 2 september 2026 09:00 - 16:30 uur 3 september 2026 09:00 - 16:30 uur 4 september 2026 09:00 - 16:30 uur |
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| Virtual Classroom | 4 dagen |
23 t/m 26 november 2026
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23 november 2026 10:30 - 18:00 uur 24 november 2026 10:30 - 18:00 uur 25 november 2026 10:30 - 18:00 uur 26 november 2026 10:30 - 18:00 uur |
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| ZOETERMEER - Kinderen van Versteegplein 18 | 4 dagen |
1 t/m 4 december 2026
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1 december 2026 09:00 - 16:30 uur 2 december 2026 09:00 - 16:30 uur 3 december 2026 09:00 - 16:30 uur 4 december 2026 09:00 - 16:30 uur |
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| Virtual Classroom | 4 dagen |
1 t/m 4 december 2026
Bekijk rooster >
1 december 2026 09:00 - 16:30 uur 2 december 2026 09:00 - 16:30 uur 3 december 2026 09:00 - 16:30 uur 4 december 2026 09:00 - 16:30 uur |
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This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.
Before attending this course, students must have: a fundamental knowledge of Microsoft Azure; experience of writing Python code to work with data, using libraries such as Numpy, Pandas, and Matplotlib; understanding of data science, including how to prepare data, and train machine learning models using common machine learning libraries such as Scikit-Learn, PyTorch, or Tensorflow.
The course lasts three days.
The size of the group is a maximum of twelve candidates.
After the course you can participate in the exam. The course helps to prepare for exam DP-100. The exam fees are not included.
