Containerized AI & ML Deployment with Docker Training Course

This instructor-led, live training in Romania (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 manager 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.

Upon completing this training, participants will be capable of:

• Creating custom Docker images.
• Deploying and managing a high volume of Docker applications.
• Evaluating various container orchestration platforms and selecting the optimal solution.
• Establishing a continuous integration pipeline for Docker-based applications.
• Integrating Docker applications into existing continuous integration workflows.
• Implementing security measures for Docker applications.
• Utilizing Kubernetes to deploy and manage diverse environments within a single cluster.
• Securing, scaling, and monitoring a Kubernetes cluster.

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

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

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

• Establishing automated pipelines for constructing and testing AI model containers.
• Ensuring version control and reproducibility throughout the model lifecycle.
• Integrating automated deployment strategies for AI services.
• Applying 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 conducted in a controlled environment.

Customization Options

• If your organization requires tailored pipeline workflows or specific platform integrations, please reach out to us for course customization.

The Certified Kubernetes Administrator (CKA) certification was established by The Linux Foundation in collaboration with the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as the premier platform for container orchestration.

Since 2015, NobleProg has specialized in Docker and Kubernetes training. With over 360 successfully delivered training projects, we have become one of the world’s most recognized training providers in the field of containerization.

Since 2019, we have further supported our customers by preparing them to validate their performance in Kubernetes environments through 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. Therefore, we recommend participating even if you do not plan to take the CKA exam.

Course Format

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

Course Customization Options

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

The Certified Kubernetes Application Developer (CKAD) program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

This instructor-led live training (available online or onsite) targets developers who wish to validate their ability to design, build, configure, and expose cloud-native applications on Kubernetes.

Additionally, the training emphasizes gaining practical experience in Kubernetes application development, so we encourage participation even if you do not plan to take the CKAD exam.

NobleProg has delivered Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training companies globally in the field of containerization. Since 2019, we have also assisted our customers in validating their performance in Kubernetes environments by preparing and encouraging them to pass the CKA and CKAD exams.

Format of the Course

• Interactive lecture and discussion.
• Ample 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 CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

Docker is an open-source platform designed to automate the construction, distribution, and execution of applications within containers.

This instructor-led live training (available online or onsite) targets engineers who want to adopt Docker for deploying and managing software as containers rather than relying on traditional standalone applications.

Upon completing this course, participants will be equipped to:

• Install and configure Docker.
• Grasp and apply software containerization techniques.
• Manage Docker-based applications.
• Network various Docker applications and systems.
• Understand and manipulate Docker registries.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical sessions.
• Hands-on implementation within a live-lab environment.

Customization Options

• To arrange customized training for this course, please contact us.
• For further information on Docker, visit: https://www.docker.com

Learn how to build, deploy, and administer containerized environments using Docker, Kubernetes, and OpenShift. This five-day, hands-on training covers container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants gain the skills needed to operate modern container platforms and troubleshoot applications across development and production environments.

In this instructor-led, live training in Romania (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.

Docker serves as a robust containerization platform that enables the creation of reproducible, portable, and scalable environments tailored for machine learning systems.

This live, instructor-led training—available either online or onsite—is designed for technical professionals with intermediate to advanced expertise who are looking to containerize and operationalize comprehensive ML pipelines using Docker.

By the end of this program, participants will be equipped to:

• Encapsulate ML training, validation, and inference workloads within containers.
• Architect and orchestrate end-to-end ML pipelines leveraging Docker and complementary tools.
• Establish versioning, reproducibility, and CI/CD practices for ML components.
• Deploy, monitor, and scale ML services within containerized infrastructures.

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises dedicated to constructing real-world ML pipeline components.
• Live laboratory sessions for implementing end-to-end containerized workflows.

Customization Options

• To tailor the training to specific ML infrastructure requirements, please reach out to discuss potential customizations.

Training Objectives: Acquire theoretical and practical skills in Docker and Kubernetes.

Leveraging GPU acceleration is critical for executing high-performance deep learning tasks with both scalability and efficiency.

This live, instructor-led session—available online or onsite—is designed for intermediate-level technical professionals seeking to configure, optimize, and execute GPU-driven AI workloads inside Docker containers.

Upon completing this course, participants will have the capability to:

• Develop and execute GPU-enabled containers for both training and inference tasks.
• Configure CUDA, drivers, and runtime libraries to support containerized AI workflows.
• Optimize resource allocation and isolation specifically for GPU-intensive applications.
• Deploy scalable, containerized deep learning services in production settings.

Course Structure

• Interactive teaching methods complemented by real-world demonstrations.
• Practice exercises centered on GPU-enabled development practices.
• Practical, hands-on implementation within a live-lab setting.

Customization Opportunities

• For training tailored to your specific infrastructure or GPU stack, please reach out to arrange a custom session.

Hybrid AI deployment involves executing AI inference across cloud, on-premise, and edge environments through unified, container-based workflows.

This instructor-led live training (available online or onsite) targets advanced professionals aiming to design and implement distributed AI inference systems within heterogeneous settings.

Upon completing this course, participants will be equipped to:

• Construct secure and scalable containerized AI services for multi-site environments.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Leverage orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across diverse infrastructure.

Course Format

• In-depth presentations and discussions led by experts.
• Extensive hands-on practice with applied exercises.
• Real-world experimentation in a controlled live-lab environment.

Customization Options

• To tailor this course to align with your organization’s specific infrastructure or use cases, please contact us for customization.

In this instructor-led, live training in Romania (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers, then automate, scale, and manage their containerized servers within a Kubernetes cluster. The training goes on to more advanced topics, walking 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.

During this instructor-led live training in Romania, participants will acquire the essential skills needed to build microservices using Spring Cloud and Docker. Knowledge is tested via exercises and the step-by-step construction of sample microservices.

By the end of the 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.

This instructor-led live training, conducted Romania (online or onsite), targets intermediate developers and DevOps engineers seeking to build, deploy, and manage microservices using Spring Cloud and Docker.

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

• Develop microservices using Spring Boot and Spring Cloud.
• Containerize applications with Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices in production environments.
• Deploy and orchestrate microservices using Kubernetes.