Operationalize machine learning and generative AI solutions (AI-300T00)
placeUtrecht 7 déc. 2026 jusqu'au 10 déc. 2026voir détails event 7 décembre 2026, 09:00-17:00, Utrecht event 8 décembre 2026, 09:00-17:00, Utrecht event 9 décembre 2026, 09:00-17:00, Utrecht event 10 décembre 2026, 09:00-17:00, Utrecht |
placeUtrecht 1 mar. 2027 jusqu'au 4 mar. 2027voir détails event 1 mars 2027, 09:00-17:00, Utrecht event 2 mars 2027, 09:00-17:00, Utrecht event 3 mars 2027, 09:00-17:00, Utrecht event 4 mars 2027, 09:00-17:00, Utrecht |
placeUtrecht 31 mai 2027 jusqu'au 3 juin 2027voir détails event 31 mai 2027, 09:00-17:00, Utrecht event 1 juin 2027, 09:00-17:00, Utrecht event 2 juin 2027, 09:00-17:00, Utrecht event 3 juin 2027, 09:00-17:00, Utrecht |
placeUtrecht 30 août 2027 jusqu'au 2 sept. 2027voir détails event 30 août 2027, 09:00-17:00, Utrecht event 31 août 2027, 09:00-17:00, Utrecht event 1 septembre 2027, 09:00-17:00, Utrecht event 2 septembre 2027, 09:00-17:00, Utrecht |
This course prepares learners to design, implement, and operate Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure. It covers building secure and scalabl...
Operationalize machine learning models (MLOps)
- Experiment with Azure Machine Learning
- Perform hyperparameter tuning with Azure Machine Learning
- Run pipelines in Azure Machine Learning
- Trigger Azure Machine Learning jobs with GitHub Actions
- Trigger GitHub Actions with feature-based development
- Work with environments in GitHub Actions
- Deploy a model with GitHub Actions
Operationalize generative AI applications (GenAIOps)
- Plan and prepare a GenAIOps solution
- Manage prompts f…
Il n'y a pour le moment aucune question fréquente sur ce produit. Si vous avez besoin d'aide ou une question, contactez notre équipe support.
This course prepares learners to design, implement, and operate Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions on Azure. It covers building secure and scalabl...
Operationalize machine learning models (MLOps)
- Experiment with Azure Machine Learning
- Perform hyperparameter tuning with Azure Machine Learning
- Run pipelines in Azure Machine Learning
- Trigger Azure Machine Learning jobs with GitHub Actions
- Trigger GitHub Actions with feature-based development
- Work with environments in GitHub Actions
- Deploy a model with GitHub Actions
Operationalize generative AI applications (GenAIOps)
- Plan and prepare a GenAIOps solution
- Manage prompts for agents in Microsoft Foundry with GitHub
- Evaluate and optimize AI agents through structured
experiments
- Automate AI evaluations with Microsoft Foundry and GitHub
Actions
- Monitor your generative AI application
- Analyze and debug your generative AI app with tracing
This course is intended for data scientists, machine learning engineers, and DevOps professionals who want to design and operate production-grade AI solutions on Azure. It is suited for learners with experience in Python, a foundational understanding of machine learning concepts, and basic familiarity with DevOps practices such as source control, CI/CD, and command-line tools, who are preparing to implement MLOps and GenAIOps workflows using Azure-native services.
Fast Lane werkt met Nederlandse trainers die didactische vaardigheden combineren met veel practische ervaring.
Il n'y a pour le moment aucune question fréquente sur ce produit. Si vous avez besoin d'aide ou une question, contactez notre équipe support.

