Architecting Microsoft Azure Solutions Training Course

This instructor-led, live training in the UAE (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.

This training program equips IT Professionals with the skills to manage their Azure subscriptions, secure identities, oversee infrastructure administration, set up virtual networking, integrate Azure with on-premises locations, control network traffic, deploy storage solutions, launch and scale virtual machines, implement web apps and containers, safeguard and share data, and oversee the entire solution.

This course is designed for Azure Administrators. These administrators are responsible for implementing, managing, and monitoring identity, governance, storage, compute resources, and virtual networks within a cloud environment. They will also be tasked with provisioning, sizing, monitoring, and adjusting these resources as needed.

This course equips Solutions Architects with the knowledge to transform business requirements into secure, scalable, and dependable solutions. The curriculum covers topics such as virtualization, automation, networking, storage, identity management, security measures, data platforms, and application infrastructure. It also highlights how decisions in these areas impact the overall solution design.

Audience Profile

This course is tailored for IT Professionals who specialize in designing and deploying solutions on Microsoft Azure. They should possess comprehensive understanding of IT operations, including networking, virtualization, identity management, security, business continuity, disaster recovery, data platforms, budgeting, and governance. Azure Solution Architects utilize the Azure Portal, and as they advance, they also employ the Command Line Interface. Candidates are expected to have advanced skills in Azure administration and experience with Azure development processes and DevOps methodologies.

Microsoft Azure Infrastructure and Deployment

This instructor-led, live training in the UAE (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 the UAE (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 the UAE (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 in the UAE (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.

The Azure Bot Service leverages the capabilities of the Microsoft Bot Framework and Azure functions to facilitate the quick development of intelligent bots.

In this instructor-led live training session, participants will learn how to effortlessly create an intelligent bot using Microsoft Azure.

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

• Master the basics of intelligent bots
• Create intelligent bots through cloud applications
• Utilize the Microsoft Bot Framework, Bot Builder SDK, and Azure Bot Service effectively
• Design bots using established bot patterns
• Develop their first intelligent bot with Microsoft Azure

Audience

• Software Developers
• Hobbyists
• Engineers
• IT Professionals

Course Format

• The course includes lectures, discussions, exercises, and extensive hands-on practice.

About This Course

This course is designed to introduce students to the essential principles of database management within a cloud environment, with a focus on foundational skills in cloud data services and Microsoft Azure. Students will gain an understanding of key data concepts such as relational databases, non-relational databases, big data, and analytics, and how these are applied using Microsoft Azure technology. They will delve into the roles, tasks, and responsibilities within the field of data management. Additionally, students will explore various relational database offerings in Azure, including their deployment and querying through cloud solutions. The course also covers non-relational databases and data storage options with Azure. Students will learn about different processing methods for creating data analytics solutions on Azure, such as Azure Synapse Analytics, Azure Databricks, and Azure HDInsight. Furthermore, they will be introduced to Power BI, including its components and how these elements function together.

Audience Profile

This course is intended for individuals interested in mastering the basics of database concepts within a cloud setting, acquiring fundamental skills in cloud data services, and establishing a solid foundation in Microsoft Azure's cloud data services.

At Course Completion

Upon finishing this course, students will be able to:

• Articulate core data concepts in Azure
• Elucidate the principles of relational databases within Azure
• Explain non-relational database concepts in Azure
• Distinguish components of a contemporary data warehouse in Azure

In this instructor-led, live training in the UAE (onsite or remote) participants will learn the fundamental concepts, components, and services of Microsoft Azure as they step through the creation of a sample cloud application.

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

• Understand the basics of Microsoft Azure
• Understand the different Azure tools and services
• Learn how to use Azure for building cloud applications

The Internet of Things (IoT) is a network infrastructure that wirelessly connects physical devices 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 expedite the development of IoT projects.

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

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

• Grasp the basics of IoT architecture
• Install and configure Azure IoT Suite
• Appreciate the advantages of utilizing Azure for programming IoT systems
• Implement various Azure IoT services (IoT Hub, Functions, Stream Analytics, Power BI, Cosmos DB, DocumentDB, IoT Device Management)
• Create, test, deploy, and troubleshoot an IoT system using Azure

Audience

• Developers
• Engineers

Course Format

• The course includes lectures, discussions, exercises, and extensive hands-on practice.

Note

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

This instructor-led, live training in the UAE (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.

In this instructor-led, live training in the UAE (online or onsite), participants will learn how to set up and manage a production-scale 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 AKS cloud.
• Integrate Kubernetes with third-party continuous integration (CI) software.
• Ensure high availability and disaster recovery in Kubernetes.

This instructor-led, live training in (online or onsite) is aimed at machine learning engineers who wish to use 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.