Azure AI Training in Sud-Vest

Azure Machine Learning (ML) and Azure OpenAI are cloud services that empower teams to develop, assess, and implement machine learning and generative AI functionalities into production-grade applications.

This instructor-led, live training (available online or onsite) is designed for intermediate-level data and application professionals aiming to leverage Azure ML and Azure OpenAI to create, deploy, and manage comprehensive AI solutions.

Upon completion of this training, participants will be capable of:

• Navigating Azure Machine Learning Studio and implementing complete ML workflows.
• Preparing data, training, testing, and evaluating models using appropriate validation metrics.
• Reliably registering, packaging, and deploying models to managed endpoints.
• Integrating Azure OpenAI models and Azure AI Search into applications following best practices.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Sud-Vest (online or onsite) is intended for developers and technical professionals at beginner, intermediate, or advanced levels who aim to leverage Microsoft Azure to build, test, and deploy AI agents for business applications.

Upon completion of this training, participants will be able to: understand AI agent architecture on Azure, create and configure a working agent, connect agents to business knowledge sources, evaluate and prepare agents for deployment.

This live, instructor-led training in Sud-Vest (online or onsite) is designed for intermediate developers and technical professionals who want to use Azure OpenAI to build secure, practical, and scalable enterprise AI solutions.

By the end of this training, participants will be able to explain Azure OpenAI capabilities, create effective prompts, connect AI applications to enterprise data, and apply security and responsible AI practices.