Docker Training in Belgrade

CI/CD for AI provides a structured methodology for automating the packaging, testing, containerization, and deployment of models through continuous integration and delivery pipelines.

This instructor-led training, available online or onsite, is designed for intermediate professionals seeking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

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

• Establish automated pipelines for constructing and testing AI model containers.
• Implement version control and reproducibility measures throughout the model lifecycle.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically tailored to machine learning operations.

Course Format

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations in a controlled environment.

Course Customization Options

• If your organization requires customized pipeline workflows or specific platform integrations, please contact us to tailor this course.

Hybrid AI deployment involves executing AI inference tasks across cloud, on-premises, and edge environments by leveraging unified container-based workflows.

This instructor-led live training, available online or onsite, is designed for advanced professionals who aim to design and implement distributed AI inference systems within heterogeneous infrastructures.

Upon completing this training, participants will be able to:

• Develop secure, scalable containerized AI services suitable for multi-location setups.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Utilize orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across diverse infrastructure landscapes.

Course Format

• Guided presentations and expert-led discussions.
• Comprehensive hands-on practice and applied exercises.
• Real-world experimentation within a controlled live-lab environment.

Customization Options

• For tailored adjustments to align this course with your organization’s specific infrastructure or use cases, please contact us to customize the training.

Docker serves as a containerization platform designed to create portable, isolated, and secure deployment environments specifically for AI inference services.

This instructor-led live training, available online or onsite, targets technical professionals at the beginner to intermediate levels who aim to construct secure and portable AI inference microservices. These services can be consistently deployed across local machines, servers, or cloud virtual machines.

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

• Construct lightweight inference containers suitable for both local and cloud deployment.
• Enhance the security of containerized AI services by applying best-practice techniques.
• Implement portable microservice workflows to ensure consistent operational environments.
• Deploy AI inference endpoints across various infrastructural setups.

Course Format

• Guided lectures accompanied by practical demonstrations.
• Hands-on exercises designed to reinforce deployment and security methodologies.
• Live laboratory practice focused on building and operating portable inference services.

Customization Options for the Course

• To tailor this training to your specific infrastructure or AI tooling stack, please contact us to arrange.

In this instructor-led live training at Belgrade (onsite or remote), participants will learn how to deploy a set of sample servers inside containers, then automate, scale, and manage these containerized servers within a Kubernetes cluster. The training progresses to more advanced topics, guiding participants through the process of securing, networking, and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy containerized databases and servers.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage different environments under the same cluster.
• Secure, scale and monitor a Kubernetes cluster.

GPU acceleration is crucial for executing high-performance deep learning tasks in a scalable and efficient way.

This instructor-led, live training (available online or onsite) is designed for intermediate-level technical professionals who want to configure, optimize, and run GPU-enabled AI workloads within Docker containers.

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

• Build and run GPU-enabled containers for training and inference.
• Configure CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimize resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerized deep learning services in production environments.

Course Format

• Interactive instruction supported by real-world demonstrations.
• Exercise-driven practice focused on GPU-enabled development.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• For tailored training aligned with your infrastructure or GPU stack, please contact us to arrange.

Docker serves as a containerization platform designed to create reproducible, portable, and scalable environments for machine learning systems.

This instructor-led, live training (available online or onsite) targets intermediate to advanced technical professionals who aim to containerize and operationalize complete ML pipelines using Docker.

Upon completing this training, participants will be able to:

• Containerize ML training, validation, and inference workloads.
• Design and orchestrate end-to-end ML pipelines using Docker and complementary tools.
• Implement versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerized environments.

Format of the Course

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centered on building real-world ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Course Customization Options

• For customized training aligned with specific ML infrastructure needs, please contact us to discuss options.

Docker serves as a containerization platform that facilitates consistent, portable, and reproducible environments for AI and machine learning tasks.

This instructor-led training, available online or onsite, targets intermediate professionals looking to package ML codebases, dependencies, and models using Docker for reliable development-to-production workflows.

Upon completing this course, participants will be able to:

• Build and manage Docker images designed for AI and ML applications.
• Containerize machine learning pipelines, tools, and dependencies.
• Optimize Docker environments for performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Concept demonstrations accompanied by guided discussions.
• Hands-on exercises focused on real-world containerization tasks.
• Practical implementation using live-lab Docker environments.

Course Customization Options

• To tailor this training to your organizational needs, please contact us to arrange it.

This instructor-led, live training in Belgrade (online or onsite) is designed for intermediate developers and DevOps engineers aiming to build, deploy, and manage microservices utilizing Spring Cloud and Docker.

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

• Build microservices utilizing Spring Boot and Spring Cloud.
• Containerize applications using Docker and Docker Compose.
• Deploy service discovery, API gateways, and inter-service communication mechanisms.
• Monitor and secure microservices within production environments.
• Deploy and orchestrate microservices using Kubernetes.

Course Objectives: Gain theoretical and operational skills in Docker and Kubernetes.

In this instructor-led live training conducted in Belgrade (onsite or remote), participants will learn how to create and manage Docker containers, then deploy a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training goes on to more advanced topics, walking participants through the process of securing, scaling and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Set up a Docker and Kubernetes cluster.
• Use Kubernetes to deploy and manage a clustered web application.
• Secure, scale and monitor a Kubernetes cluster.

The Certified Kubernetes Administrator (CKA) program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Today, Kubernetes stands as a leading platform for container orchestration.

NobleProg has been providing Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training providers globally in the field of containerization.

Since 2019, we have also been helping our customers validate their performance in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams.

This instructor-led, live training (available online or onsite) is designed for System Administrators and Kubernetes users who wish to validate their knowledge by passing the CKA exam.

Additionally, the training focuses on gaining practical experience in Kubernetes Administration, so we recommend participation even if you do not intend to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice.
• Hands-on implementation in a live lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The goal of this hands-on course is to equip participants with the practical tools and skills required for the effective management of Docker and Kubernetes.

In this instructor-led, live training in Belgrade, participants will learn how to manage Red Hat OpenShift Container Platform.

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

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerized applications on-premise, in public cloud or on a hosted cloud.
• Secure OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

In this instructor-led, live training in Belgrade, participants will learn how to use OpenShift Container Platform to deploy containerized applications.

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

• Create and configure an OpenShift setup.
• Rapidly deploy applications on-premise, in a public cloud, or on a hosted cloud.

The Certified Kubernetes Application Developer (CKAD) program has been developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host of Kubernetes.

This instructor-led, live training (online or onsite) is aimed at Developers who wish to confirm their skills in design, build, configure, and expose cloud native applications for Kubernetes.

On the other hand, training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part in it, even if you don't intend to take CKAD exam.

NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training company worldwide in field of containerization. Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led, live course in Belgrade provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.

This instructor-led, live training (available online or onsite) is aimed at engineers who wish to evaluate each of these services to make an informed decision about which to deploy within their organization.

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

• Set up a development environment that includes all needed libraries, packages and frameworks needed to start developing.
• Set up, configure and deploy a series of demo containers using a number of different approaches.
• Understand the architectural and design differences among different Docker/Kubernetes solutions within AWS.
• Automate the deployment of Docker containers.
• Set up a continuous integration and deployment pipeline.
• Integrate Docker and Kubernetes into an existing continuous integration system.

This instructor-led, live training in Belgrade (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker so as to deploy applications at a larger scale while maintaining control.

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

• Build their own Docker images.
• Deploy and manage a large number of Docker applications.
• Evaluate different container orchestration solutions and choose the most suitable one.
• Set up a continuous integration process for Docker applications.
• Integrate Docker applications with existing continuous tools integration processes.
• Secure their Docker applications.

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

• Create custom Docker images.
• Deploy and manage a high volume of Docker applications.
• Assess various container orchestration solutions and select the most appropriate option.
• Establish a continuous integration pipeline for Docker applications.
• Integrate Docker applications with existing continuous integration workflows.
• Enhance the security of Docker applications.
• Leverage Kubernetes to deploy and manage multiple environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters.

Docker provides a comprehensive platform for developers and system administrators to manage distributed applications. It features a runtime environment for executing containers and a service that facilitates the sharing of container images.

With Docker, applications can be deployed and run identically across various environments, including local laptops, dedicated servers, and virtual machines, without modification.

Over the first two days, this course covers the fundamental usage of Docker, offering value to both software developers and IT operations professionals. The training emphasizes practical, hands-on exercises, allowing participants to configure their own Docker environment and create custom Docker images.

On the final day, participants will explore advanced tools that extend Docker's capabilities, including Docker Machine, Docker Compose, and Docker Swarm.

This instructor-led, live training in Belgrade (online or onsite) is tailored for engineers who want to use Docker to deploy and manage software as containers instead of traditional stand-alone software.

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

• Install and configure Docker.
• Understand and implement software containerization.
• Manage Docker-based applications.
• Network different Docker applications and systems.
• Understand and edit Docker registries.

Docker serves as a platform designed for developers and system administrators to manage distributed applications. It comprises a runtime environment for executing containers and a service that facilitates the sharing of these containers.

Thanks to Docker, the same application can operate seamlessly on laptops, dedicated servers, and virtual machines without requiring modifications.

This course covers the fundamental usage of Docker, offering value to both developers and system administrators. The program features numerous practical exercises, allowing participants to work within their own Docker environments and create their own Docker images over the course of two days.

This instructor-led, live training in Belgrade (online or onsite) is designed for DevOps engineers who wish to optimize and simplify the CI/CD process using Docker and Jenkins.

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

• Automate code delivery and pipeline deployment using Jenkins.
• Construct applications using Docker and Dockerfiles.
• Configure authentication mechanisms to enhance security.

Course Format

• Interactive lectures accompanied by discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live laboratory environment.

Customization Options

• For those interested in customizing this training, please reach out to us to discuss your requirements.

In this instructor-led live training held in Belgrade, participants will learn the essential principles of developing microservices using Spring Cloud and Docker. Knowledge is tested through exercises and the incremental development of sample microservices.

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

• Understand the fundamentals of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerized microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Use Docker Compose for end-to-end integration testing.

OpenShift Container Platform v4 is an enterprise-grade Kubernetes solution created by Red Hat, designed to automate the deployment, scaling, and management of containerized applications.

This instructor-led, live training (available online or onsite) is designed for system administrators and DevOps engineers who want to deploy, manage, and operate OpenShift clusters in production environments.

The course takes a practical approach to installing and managing OpenShift 4 clusters, working with Operators, securing workloads, and operating applications at scale.

This instructor-led, live training (online or onsite) targets DevOps engineers who wish to use Selenium to execute tests within Docker containers.

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

• Create test automation infrastructure for on-demand testing.
• Develop a test automation framework using Java.
• Build a CI/CD pipeline from scratch with Jenkins and Docker.