Programming for IoT with Azure Training Course

About This Course

Through this course, learners will acquire the skills to design and build services that retrieve local and remote data from diverse sources. Additionally, participants will learn how to develop and deploy these services within hybrid environments, spanning on-premises servers and Microsoft Azure.

Audience Profile

Primary audience: .NET developers seeking to learn service development and deployment to hybrid environments.
Secondary audience: .NET developers with experience in web application development who are interested in building new applications or migrating existing ones to Microsoft Azure.

At Course Completion

Upon finishing this course, students will be able to:

• Explain fundamental concepts of service development and data access strategies within the .NET platform.
• Describe the Microsoft Azure cloud platform, including its compute, data, and application hosting capabilities.
• Design and develop data-centric applications using Visual Studio 2017 and Entity Framework Core.
• Design, implement, and consume HTTP services using ASP.NET Core.
• Extend HTTP services through ASP.NET Core.
• Host services both on-premises and in Microsoft Azure.
• Deploy services to on-premises and cloud environments while managing their interfaces and policies.
• Select appropriate data storage solutions and manage caching, distribution, and synchronization of data.
• Monitor, log, and troubleshoot services effectively.
• Describe claim-based identity concepts and standards, and implement authentication and authorization using Azure Active Directory.
• Create scalable service applications.

Acquire the essential skills to design Azure AI solutions by constructing a customer support chatbot that leverages artificial intelligence from the Microsoft Azure platform. This includes implementing language understanding and utilizing pre-built AI capabilities provided by Azure Cognitive Services.

About This Course

This course provides an overview of fundamental concepts related to artificial intelligence (AI) and the Microsoft Azure services available for developing AI solutions. Rather than aiming to train students to become professional data scientists or software developers, the course focuses on building awareness of common AI workloads and enabling participants to identify the appropriate Azure services to support those workloads. Designed as a blended learning experience, it combines instructor-led training with online materials hosted on the Microsoft Learn platform (https://azure.com/learn). The course includes hands-on exercises based on Learn modules, and students are encouraged to use Learn content as a reference to reinforce their classroom learning and explore topics in greater depth.

Audience Profile

The Azure AI Fundamentals course is designed for individuals interested in understanding the types of solutions that artificial intelligence (AI) enables, as well as the Microsoft Azure services used to build them. Prior experience with Microsoft Azure is not required, but a basic familiarity with computer technology and the Internet is assumed. Some concepts covered require a fundamental understanding of mathematics, such as the ability to interpret charts. Since the course includes hands-on activities involving data manipulation and code execution, a foundational knowledge of programming principles will be beneficial.

At Course Completion

After completing this course, you will be able to:

• Describe AI workloads and key considerations
• Describe the fundamental principles of machine learning on Azure
• Describe the features of computer vision workloads on Azure
• Describe the features of Natural Language Processing (NLP) workloads on Azure
• Describe the features of conversational AI workloads on Azure

This instructor-led, live training in Slovakia (online or onsite) is tailored for intermediate to advanced professionals seeking to build and deploy AI-enhanced cloud applications on Microsoft Azure.

Upon completion of this training, participants will be capable of:

• Developing event-driven and serverless applications using Azure Functions.
• Managing Azure storage resources and virtual machines.
• Deploying and scaling web applications via Azure App Service and Docker containers.
• Integrating artificial intelligence, machine learning, and natural language processing capabilities through Azure AI Services.
• Utilizing GitHub Copilot to support AI-driven cloud application development.

This instructor-led, live training in Slovakia (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 Azure's interactive workspace to collaboratively develop ML models.
• Choose from different Azure-supported ML frameworks such as PyTorch, TensorFlow, and scikit-learn.

About This Course

This three-day program is designed to equip AWS (Amazon Web Services) developers with the knowledge required to build comprehensive end-to-end solutions on Microsoft Azure. Throughout the course, participants will construct Azure App Service Web Apps and Azure Functions, utilize blob storage or Cosmos DB within their solutions, and implement secure cloud architectures that incorporate user authentication and authorization. The curriculum also covers API management and the development of event- and message-driven solutions. Participants will gain skills in monitoring, troubleshooting, and optimizing Azure solutions. The focus is on understanding how developers leverage Azure services, with particular emphasis on features and tasks that differ from AWS, and what these differences imply for application development on the Azure platform.

Audience Profile

This course is intended for AWS developers with professional experience who are looking to transition to or expand their skills in Azure development.

This course equips students with the essential knowledge and skills required to utilize PowerShell for the administration and automation of Windows server environments. Participants will develop the ability to identify and construct the specific commands needed to execute designated tasks. Furthermore, students will learn how to create scripts to handle advanced responsibilities, such as automating repetitive processes and generating detailed reports. This course delivers prerequisite competencies that support a wide array of Microsoft products, including Windows Server, Windows Client, Microsoft Azure, and Microsoft 365. Aligned with this objective, the course does not concentrate exclusively on any single product; however, Windows Server serves as the primary example platform for demonstrating the techniques taught, as it underpins all of these Microsoft solutions.

This course equips IT Professionals with the skills to manage Azure subscriptions, secure identities, administer infrastructure, configure virtual networking, connect Azure with on-premises environments, manage network traffic, implement storage solutions, create and scale virtual machines, deploy web apps and containers, back up and share data, and monitor overall solutions.

Designed for Azure Administrators, this training covers the implementation, management, and monitoring of identity, governance, storage, compute, and virtual networks within cloud environments. Azure Administrators will learn to provision, size, monitor, and adjust resources as needed.

This course equips Azure administrators with the skills to plan, deliver, and manage virtual desktop experiences and remote applications for any device on Azure. Participants will engage in a combination of demonstrations and hands-on labs to deploy virtual desktops and applications on Azure Virtual Desktop, optimizing them for multi-session virtual environments.

This instructor-led, live training in Slovakia (online or onsite) is designed for intermediate IT professionals and business managers who want to understand how IoT and edge computing can drive efficiency, real-time processing, and innovation across various industries.

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

• Understand the principles of IoT and edge computing and their role in digital transformation.
• Identify use cases for IoT and edge computing in manufacturing, logistics, and energy sectors.
• Differentiate between edge and cloud computing architectures and deployment scenarios.
• Implement edge computing solutions for predictive maintenance and real-time decision-making.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

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

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.

This instructor-led, live training in Slovakia (online or onsite) is aimed at product managers and developers who wish to use Edge Computing to decentralize data management for faster performance, leveraging smart devices located on the source network.

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

• Understand the basic concepts and advantages of Edge Computing.
• Identify the use cases and examples where Edge Computing can be applied.
• Design and build Edge Computing solutions for faster data processing and reduced operational costs.

This instructor-led, live training in Slovakia (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

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

• Understand the principles and benefits of Federated Learning in IoT and edge computing.
• Implement Federated Learning models on IoT devices for decentralized AI processing.
• Reduce latency and improve real-time decision-making in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

In this instructor-led, live training in Slovakia, participants will explore the various aspects of NB-IoT (also known as LTE Cat NB1) as they develop and deploy a sample NB-IoT-based application.

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

• Identify the key components of NB-IoT and understand how they integrate to form a cohesive ecosystem.
• Understand and articulate the security features inherent in NB-IoT devices.
• Develop a basic application for tracking NB-IoT devices.

ThingsBoard is an open-source IoT platform that provides device management, data collection, processing, and visualization for your IoT solution.

In this instructor-led live training, participants will learn how to integrate ThingsBoard into their IoT solutions.

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

• Install and configure ThingsBoard
• Understand the fundamentals of ThingsBoard features and architecture
• Build IoT applications with ThingsBoard
• Integrate ThingsBoard with Kafka for telemetry device data routing
• Integrate ThingsBoard with Apache Spark for data aggregation from multiple devices

Audience

• Software engineers
• Hardware engineers
• Developers

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.