Developing Intelligent Bots with Azure Training Course

This live, instructor-led training in Taiwan (online or onsite) is designed for intermediate to advanced professionals seeking to build and deploy AI-powered cloud applications using Microsoft Azure.

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

• Develop event-driven and serverless applications using Azure Functions.
• Manage Azure storage solutions and virtual machines.
• Deploy and scale web applications using Azure App Service and Docker containers.
• Integrate AI, machine learning, and natural language processing using Azure AI Services.
• Leverage GitHub Copilot to assist in AI-driven cloud application development.

This instructor-led, live training in Taiwan (online or onsite) is aimed at engineers who wish to use Azure ML's drag-and-drop platform to deploy Machine Learning workloads without having to purchase software and hardware and without having to worry about maintenance and deployment.

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

• Write highly-accurate machine learning models using Python, R, or zero-code tools.
• Leverage Azure's available data sets and algorithms to train and track machine learning and deep-learning models.
• Use Azures interactive workspace to collaboratively develop ML models.
• Choose from different Azure-supported ML frameworks such as PyTorch, TensorFlow, and scikit-learn.

Microsoft Azure Infrastructure and Deployment

This instructor-led, live training in Taiwan (online or onsite) targets developers and technical professionals at beginner, intermediate, or advanced levels who wish to utilize Microsoft Azure to build, test, and deploy AI agents for business applications.

By the end of this training, participants will be able to understand Azure AI agent architecture, create and configure a functioning agent, connect agents to business knowledge sources, and evaluate and prepare agents for deployment.

This training enables delegates to enhance their Microsoft Azure solution design skills.

Upon completion, participants will gain a thorough understanding of Azure service features and capabilities, allowing them to identify trade-offs and make informed decisions for designing both public and hybrid cloud solutions.

Throughout the course, appropriate infrastructure and platform solutions that align with functional, operational, and deployment requirements will be defined across the solution life-cycle.

This instructor-led, live training in Taiwan (online or onsite) is designed for DevOps engineers, developers, and project managers who wish to leverage Azure DevOps to build and deploy optimized enterprise applications faster than traditional development approaches.

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

• Grasp the fundamental DevOps vocabulary and principles.
• Install and configure the necessary Azure DevOps tools for software development.
• Leverage Azure DevOps tools and services to continuously adapt to the market.
• Build enterprise applications and evaluate current development processes based on Azure DevOps solutions.
• Manage teams more efficiently and accelerate software deployment time.
• Adopt DevOps development practices within the organization.

This instructor-led, live training in Taiwan (online or onsite) is aimed at security administrators who wish to secure Azure workloads.

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

• Administrate host security, network security, and more.
• Set up storage and database security in Azure.
• Implement security monitoring using Azure resources.
• Prevent malicious cyber attacks on data and infrastructures.

This instructor-led live training, offered in Taiwan (online or onsite), is tailored for security administrators who aim to learn how to configure Azure cloud security to protect workloads running in Azure.

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

• Configure host and network security.
• Configure Azure advanced security options.
• Use Azure to secure cloud computing workloads.
• Use endpoint protection services security against malware and viruses.
• Secure container workloads that are running in Azure.

This instructor-led live training in Taiwan (online or onsite) is aimed at intermediate-level data engineers who wish to learn how to use Azure Data Lake Storage Gen2 for effective data analytics solutions.

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

• Understand the architecture and key features of Azure Data Lake Storage Gen2.
• Optimize data storage and access for cost and performance.
• Integrate Azure Data Lake Storage Gen2 with other Azure services for analytics and data processing.
• Develop solutions using the Azure Data Lake Storage Gen2 API.
• Troubleshoot common issues and optimize storage strategies.

This instructor-led, live training in Taiwan (online or on-site) is designed for intermediate-level Java developers, software engineers, and cloud enthusiasts who want to leverage Azure OpenAI to build intelligent applications.

Upon completion, participants will be able to:

• Grasp the principles of Generative AI and its practical applications.
• Set up and manage an Azure OpenAI service.
• Integrate OpenAI models into Java applications.
• Deploy AI-driven features within web applications.

In this instructor-led, live training in Taiwan (onsite or remote), participants will master the fundamental concepts, components, and services of Microsoft Azure by stepping through the creation of a sample cloud application.

Upon completion of this training, participants will be able to:

• Comprehend the basics of Microsoft Azure
• Understand the various Azure tools and services
• Learn how to utilize Azure for building cloud applications

In this instructor-led, live training in Taiwan (online or onsite), participants will learn how to set up and manage a production-grade container environment using Kubernetes on AKS.

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

• Configure and manage Kubernetes on AKS.
• Deploy, manage, and scale a Kubernetes cluster.
• Deploy containerized (Docker) applications on Azure.
• Migrate an existing Kubernetes environment from on-premise to the AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

This instructor-led, live training (online or onsite) is tailored for machine learning engineers who aim to utilize Azure Machine Learning and Azure DevOps to facilitate MLOps practices.

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

• Build reproducible workflows and machine learning models.
• Manage the machine learning lifecycle.
• Track and report model version history, assets, and more.
• Deploy production ready machine learning models anywhere.

This instructor-led, live training in Taiwan (online or on-site) is aimed at intermediate-level data engineers who wish to become proficient in utilizing Azure Synapse Analytics for a wide range of data processing, analytics, and visualization.

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

• Understand the core concepts, architecture, and components of Azure Synapse Analytics.
• Create, configure, and manage scalable data warehouses using Azure Synapse.
• Master the techniques for ingesting, transforming, and loading data (ETL) from various sources into Azure Synapse.
• Optimize query performance, secure data, and integrate Azure Synapse with Power BI and other tools to visualize data and share insights.

This instructor-led, live training in Taiwan (online or onsite) is aimed at intermediate-level cloud engineers and IT professionals who wish to use Terraform to automate the deployment, management, and scaling of infrastructure on the Azure cloud platform.

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

• Understand the basics of Terraform and its benefits in infrastructure as code.
• Set up and configure Terraform for Azure.
• Develop, test, and deploy Terraform configuration files for various Azure services.
• Use Terraform for managing and scaling Azure resources.
• Implement best practices for Terraform state management and version control.
• Integrate Terraform with Azure DevOps for automated deployments.
• Create reusable Terraform modules for consistent resource provisioning.
• Utilize advanced features of Terraform for complex infrastructure deployments.