Containerized AI & ML Deployment with Docker Training Course

This instructor-led, live training in Bulgaria (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 completion of this training, participants will be able to:

• Create custom Docker images.
• Deploy and manage a large volume of Docker applications.
• Evaluate various container orchestration solutions and select the most appropriate one.
• Establish a continuous integration process for Docker applications.
• Integrate Docker applications with existing CI tooling workflows.
• Implement security measures for Docker applications.
• Utilize Kubernetes to deploy and manage multiple environments within a single cluster.
• Secure, scale, and monitor a Kubernetes cluster.

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

This instructor-led live training (available online or onsite) targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows by leveraging Docker alongside CI/CD platforms.

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

• Develop automated pipelines for constructing and evaluating AI model containers.
• Establish version control and ensure reproducibility throughout model lifecycles.
• Incorporate automated deployment strategies specifically for AI services.
• Apply CI/CD best practices adapted for machine learning operations.

Course Format

• Instructor-led presentations coupled with technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations conducted within a controlled environment.

Customization Options

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

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

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

Since 2015, NobleProg has been providing Docker and Kubernetes training. 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 assisting our clients in validating their proficiency in Kubernetes (k8s) environments by preparing them for and encouraging them to take 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.

Furthermore, the training emphasizes gaining practical experience in Kubernetes Administration. Therefore, we recommend participating even if you do not plan to take the CKA exam.

Format of the Course

• 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 make arrangements.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

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

This instructor-led, live training (available online or onsite) is aimed at Developers who want to validate their skills in designing, building, configuring, and exposing cloud native applications for Kubernetes.

Additionally, the training focuses on gaining practical experience in Kubernetes application development, so we recommend participating even if you do not plan to take the CKAD exam.

NobleProg has been delivering Docker & Kubernetes training since 2015. With more than 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 been helping our customers validate their performance in Kubernetes environments by preparing them to pass the CKA and CKAD exams.

Course Format

• Interactive lectures and discussions.
• Plenty 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 it.
• For more information about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

Docker is an open-source platform designed to automate the process of building, shipping, and running applications within containers.

This instructor-led live training (available online or onsite) targets engineers who want to leverage Docker to deploy and manage software as containers rather than relying on traditional standalone solutions.

Upon completing this training, participants will be able to:

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

Course Format

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

Customization Options

• To request a customized version of this course, please contact us to arrange it.
• For more 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 acquire the skills necessary to operate modern container platforms and troubleshoot applications across development and production environments.

In this instructor-led live training in Bulgaria (onsite or remote), participants will learn to create and manage Docker containers and deploy a sample application within one. Attendees will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Finally, the training progresses to more advanced topics, guiding 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 containerization platform designed to create reproducible, portable, and scalable environments for machine learning systems.

This live, instructor-led training, available online or on-site, is tailored for intermediate to advanced technical professionals seeking to containerize and operationalize complete ML pipelines using Docker.

By the end of this training, participants will have the capability to:

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

Course Structure

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

Customization Options

• For training tailored to specific ML infrastructure requirements, please contact us to discuss available options.

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

To execute high-performance deep learning workloads with both scalability and efficiency, GPU acceleration is indispensable.

This live, instructor-led training, available either online or on-site, is designed for intermediate-level technical professionals seeking to configure, optimize, and deploy GPU-enabled AI workloads within Docker containers.

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

• Construct and execute GPU-enabled containers for both training and inference tasks.
• Set up CUDA, drivers, and runtime libraries specifically for containerized AI workflows.
• Optimize resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerized deep learning services within production environments.

Course Format

• Interactive teaching supported by practical, real-world demonstrations.
• Exercise-focused practice centered on GPU-enabled development.
• Hands-on implementation within a live-lab environment.

Customization Options

• If you require tailored training aligned with your specific infrastructure or GPU stack, please reach out to us to discuss arrangements.

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

This instructor-led live training (available online or onsite) is designed for advanced professionals looking to design and deploy distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will be able to:

• Create secure and scalable containerized AI services for multi-location settings.
• Leverage Docker to deploy AI inference workloads across cloud platforms, local servers, and edge devices.
• Utilize orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across diverse infrastructure.

Course Format

• Instructor-led presentations and expert-driven discussions.
• Extensive hands-on practice with applied exercises.
• Real-world experimentation within a controlled live-lab environment.

Customization Options

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

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

In this instructor-led, live training held in Bulgaria, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge is put to the test through exercises and the step-by-step development of sample microservices.

By the end 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.

This instructor-led, live training in Bulgaria (online or onsite) is designed for developers and DevOps engineers with intermediate-level skills who wish to build, deploy, and manage microservices using Spring Cloud and Docker.

Upon completing this training, participants will gain the ability to:

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