Azure AI Training in Taiwan

Azure Machine Learning (ML) and Azure OpenAI are cloud services designed to help teams develop, assess, and deploy machine learning and generative AI capabilities into production applications.

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

By the end of this training, participants will be able to:

• Navigate Azure Machine Learning Studio and implement complete ML workflows from start to finish.
• Preprocess data, train models, conduct testing, and evaluate model performance using appropriate validation metrics.
• Register, package, and reliably deploy models to managed endpoints.
• Integrate Azure OpenAI models and Azure AI Search into applications following best practices.

Format of the Course

• Interactive lectures and discussions.
• Ample exercises and practice sessions.
• 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 Taiwan (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level developers and technical professionals who wish to use Microsoft Azure to build, test, and deploy AI agents for business applications.

By the end 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 instructor-led, live training in Taiwan (online or onsite) is aimed at intermediate-level developers and technical professionals who wish to use Azure OpenAI to build secure, useful, 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.