Developing Intelligent Bots with Azure Training Course

This instructor-led, live training in Malaysia (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to build and deploy AI-powered cloud applications using Microsoft Azure.

By the end 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 Malaysia (online or onsite) is targeted at engineers who want to use Azure ML's drag-and-drop platform to deploy machine learning workloads. Participants can avoid the need to purchase software and hardware, as well as the concerns related to maintenance and deployment.

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

• Develop highly accurate machine learning models using Python, R, or zero-code tools.
• Utilize Azure's available datasets and algorithms to train and track both machine learning and deep-learning models.
• Employ Azure's interactive workspace to collaboratively develop ML models.
• Select from various Azure-supported ML frameworks, such as PyTorch, TensorFlow, and scikit-learn.

Microsoft Azure Infrastructure and Deployment

This instructor-led, live training in Malaysia (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 training empowers participants to enhance their Microsoft Azure solution design expertise.

Upon completion, delegates will grasp the features and capabilities of Azure services, enabling them to identify trade-offs and make informed decisions for designing public and hybrid cloud solutions.

Throughout the training, appropriate infrastructure and platform solutions to meet functional, operational, and deployment requirements across the solution lifecycle will be defined.

This instructor-led, live training in Malaysia (online or onsite) is aimed at DevOps engineers, developers, and project managers who wish to utilize 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:

• Understand the fundamental DevOps vocabulary and principles.
• Install and configure the necessary Azure DevOps tools for software development.
• Utilize Azure DevOps tools and services to continuously adapt to the market.
• Build enterprise applications and evaluate current development processes upon 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 Malaysia (online or onsite) is aimed at data scientists who wish to use Azure Machine Learning to build end-to-end machine learning models for predictive analysis.

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

• Build machine learning models with zero programming experience.
• Create predictive algorithms with Azure Machine Learning.
• Deploy production ready machine learning algorithms.

This instructor-led, live training in Malaysia (online or onsite) is designed for security administrators who want to secure their Azure workloads.

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

• Administer host security, network security, and other areas.
• Set up storage and database security in Azure.
• Implement security monitoring using Azure resources.
• Prevent malicious cyber attacks on data and infrastructure.

This instructor-led, live training in Malaysia (online or on-site) is designed for security administrators who wish to learn how to configure Azure cloud security to secure 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 Malaysia (online or onsite) targets developers seeking to learn how to build microservices on Microsoft Azure Service Fabric (ASF).

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

• Leverage ASF as a robust platform for building and managing microservices.
• Grasp fundamental microservices programming concepts and architectural models.
• Establish a cluster within the Azure environment.
• Deploy microservices both on-premises and in the cloud.
• Debug and troubleshoot live microservice applications.

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

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

• Comprehend the principles of Generative AI and its practical applications.
• Configure and administer an Azure OpenAI service.
• Integrate OpenAI models into Java applications.
• Deploy AI-driven features within web applications.

Through this instructor-led, live training in Malaysia (onsite or remotely), participants will explore the fundamental concepts, components, and services of Microsoft Azure by guiding them through the creation of a sample cloud application.

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

• Grasp the core principles of Microsoft Azure
• Understand the various Azure tools and services available
• Learn how to utilise Azure for developing cloud applications

The Internet of Things (IoT) refers to a network infrastructure that wirelessly connects physical objects and 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 with preconfigured solutions designed to help developers accelerate the creation of IoT projects.

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

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

• Grasp the fundamental principles of IoT architecture
• Install and configure the Azure IoT Suite
• Identify the benefits of utilizing Azure for IoT system programming
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, and IoT Device Management)
• Build, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

Format of the course

• A combination of lectures, discussions, exercises, and extensive hands-on practice

Note

• To request customized training for this course, please contact us to make arrangements.

This instructor-led, live training in Malaysia (available online or onsite) is designed for engineers who wish to deploy Machine Learning workloads to the Azure cloud.

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

• Install and configure Kubernetes, Kubeflow, and other necessary software on Azure.
• Use Azure Kubernetes Service (AKS) to simplify the process of initializing a Kubernetes cluster on Azure.
• Create and deploy a Kubernetes pipeline to automate and manage 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.