OpenFaas for Developers 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.

This instructor-led, live training in Slovakia (onsite or remote) is designed for engineers aiming to deploy and manage IoT devices on AWS.

Upon completion, participants will be equipped to build an IoT platform that includes deploying and managing a backend, gateway, and devices on top of AWS.

This instructor-led, live training in Slovakia (online or onsite) is aimed at developers who wish to install, configure, and manage AWS IoT Greengrass capabilities to create applications for various devices.

By the end of this training, participants will be able to use AWS IoT Greengrass to build, deploy, manage, secure, and monitor applications on intelligent devices.

This instructor-led, live training in Slovakia (onsite or remote) is targeted at developers aiming to use AWS Lambda to build and deploy services and applications to the cloud, without worrying about provisioning the execution environment (servers, VMs, containers, availability, scalability, storage, etc.).

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

• Configure AWS Lambda to execute a function.
• Understand FaaS (Functions as a Service) and the advantages of serverless development.
• Build, upload, and execute AWS Lambda functions.
• Integrate Lambda functions with different event sources.
• Package, deploy, monitor, and troubleshoot Lambda-based applications.

DO180 serves as a practical introduction to containers, core Kubernetes principles, and Red Hat OpenShift platform concepts, emphasizing hands-on technical skills.

This instructor-led, live training (available online or onsite) is designed for technical professionals at beginner to intermediate levels who aim to master container workflows, Kubernetes primitives, and the deployment and operation of applications on OpenShift.

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

• Construct and manage container images and registries, adhering to best practices for security and reproducibility.
• Deploy and administer Kubernetes objects, including pods, deployments, and services, within an OpenShift environment.
• Leverage OpenShift features such as routes, BuildConfigs, and the web console to accelerate application delivery.
• Configure persistent storage, management of configurations, and handling of secrets for stateful workloads.
• Apply fundamental security measures, Role-Based Access Control (RBAC), and monitoring practices to ensure cluster and application health.

Course Format

• Interactive lectures and discussions.
• Daily hands-on labs conducted in a live OpenShift environment.
• Scenario-based exercises and troubleshooting workshops.

Customization Options

• To request a tailored version of this course, please contact us to make arrangements.

This instructor-led, live training in Slovakia (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for DevOps workflows.
• Implement continuous integration and continuous delivery (CI/CD) pipelines.
• Automate testing, monitoring, and deployment processes using AWS Cloud9.
• Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows.
• Utilize source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in Slovakia (available online or onsite) is targeted at intermediate-level professionals who wish to learn how to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda.

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

• Understand the fundamentals of serverless architecture.
• Set up AWS Cloud9 for serverless application development.
• Develop, test, and deploy serverless applications using AWS Lambda.
• Integrate AWS Lambda with other AWS services such as API Gateway and S3.
• Optimize serverless applications for performance and cost efficiency.

This instructor-led, live training in Slovakia (online or onsite) is designed for engineers who want to use Helm to simplify the installation and management of Kubernetes applications.

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

• Install and configure Helm.
• Develop reproducible builds for Kubernetes applications.
• Distribute applications as Helm charts.
• Deploy third-party applications stored as Helm charts.
• Manage Helm package releases.

Summary:

• Grasping IoT architecture and its fundamental functions.
• Examining the principles of "Things" and "Sensors," the broader Internet of Things landscape, and aligning business objectives with IoT solutions.
• A thorough review of IoT software components, encompassing hardware, firmware, middleware, cloud infrastructure, and mobile applications.
• Core IoT capabilities: Fleet management, data visualization, SaaS-based Facility Management and Data Visualization, alert and alarm systems, onboarding sensors and "things," and geo-fencing.
• Foundational concepts of IoT device-to-cloud communication via MQTT.
• Linking IoT devices to AWS using MQTT through AWS IoT Core.
• Integrating AWS IoT Core with AWS Lambda for computational tasks and Amazon DynamoDB for data storage.
• Establishing a connection between a Raspberry Pi and AWS IoT Core to enable seamless data exchange.
• Practical lab exercise: Constructing a smart device employing a Raspberry Pi and AWS IoT Core.
• Visualizing sensor data and managing web interface interactions.

This instructor-led, live training in Slovakia (online or onsite) is designed for beginner to intermediate software developers and DevOps professionals who wish to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local machine.
• Understand the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for developing, testing, and debugging applications.

This instructor-led, live training in Slovakia (online or onsite) is designed for intermediate developers and DevOps engineers aiming to utilize Minikube within their development workflows.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and debug applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.