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) is aimed at beginner-level, intermediate-level, and 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 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 tailored for data scientists who aim to leverage Azure Machine Learning to construct end-to-end machine learning models for predictive analytics.

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

• Build machine learning models without any prior programming experience.
• Develop predictive algorithms using Azure Machine Learning.
• Deploy production-grade machine learning algorithms.

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 developers who wish to learn how to build microservices on Microsoft Azure Service Fabric (ASF).

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

• Use ASF as a platform for building and managing microservices.
• Understand key microservices programming concepts and models.
• Create a cluster in Azure.
• Deploy microservices on premises or in the cloud.
• Debug and troubleshoot a live microservice application.

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

The Internet of Things (IoT) constitutes a network infrastructure that wirelessly links physical objects with software applications, enabling them to communicate and exchange data through network communications, cloud computing, and data capture. Azure provides a comprehensive suite of cloud services, including an IoT Suite comprised of preconfigured solutions designed to help developers accelerate the creation of IoT projects.

In this instructor-led live training, participants will learn how to develop IoT applications using Azure.

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

• Understand the fundamentals of IoT architecture
• Install and configure Azure IoT Suite
• Learn the benefits of using Azure in programming IoT systems
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

Format of the course

• Part lecture, part discussion, exercises and heavy hands-on practice

Note

• 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 engineers who wish to deploy Machine Learning workloads to Azure cloud.

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

• Install and configure Kubernetes, Kubeflow and other needed software on Azure.
• Use Azure Kubernetes Service (AKS) to simplify the work of initializing a Kubernetes cluster on Azure.
• Create and deploy a Kubernetes pipeline for automating and managing ML models in production.
• Train and deploy TensorFlow ML models across multiple GPUs and machines running in parallel.
• Leverage other AWS managed services to extend an ML application.