GPU-Accelerated AI & Deep Learning with Docker Containers Training Course

This instructor-led, live training in Greece (online or on-site) is designed for engineers who wish to advance their knowledge of Docker 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.

Upon completion, participants will be able to:

• Create custom Docker images.
• Deploy and manage a high volume of Docker applications.
• Evaluate various container orchestration solutions and select the most appropriate option.
• Establish a continuous integration workflow for Docker applications.
• Integrate Docker applications with existing continuous integration toolchains.
• Implement security measures for Docker applications.
• Leverage Kubernetes to deploy and manage diverse environments within a single cluster.
• Secure, scale, and monitor a Kubernetes cluster effectively.

Docker serves as a leading containerization platform, facilitating the creation of consistent, portable, and reproducible environments specifically designed for AI and machine learning workloads.

This live, instructor-led training, available online or on-site, is tailored for intermediate-level professionals aiming to streamline their development-to-production workflows by packaging ML codebases, dependencies, and models using Docker.

Upon successful completion of this course, participants will possess the ability to:

• Create and maintain Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, associated tools, and dependencies within containers.
• Enhance Docker environments to ensure peak performance and portability.
• Implement containerized ML services across various runtime platforms.

Course Delivery Method

• Theoretical concepts illustrated through guided discussions.
• Practical exercises centered on real-world containerization scenarios.
• Hands-on implementation using live-lab Docker environments.

Customization Possibilities

• For adapting this training to align with your specific organizational context, please reach out to discuss arrangements.

CI/CD for AI represents a structured 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, is designed for intermediate-level 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.
• Enforce version control and reproducibility throughout the model lifecycle.
• Incorporate 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 conducted in a controlled environment.

Customization Options

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

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. Having successfully completed over 360 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 customers in validating their performance within Kubernetes environments by preparing 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; therefore, we recommend participating even if you do not intend to take the CKA exam.

Course Format

• Interactive lectures and discussions.
• Ample exercises and practice opportunities.
• Hands-on implementation in a live laboratory environment.

Course Customization Options

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

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/

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

This instructor-led live training (available online or on-site) targets engineers who aim to adopt container-based deployment for their software, moving away from traditional stand-alone models.

Upon completing this course, participants will be able to:

• Install and configure Docker.
• Grasp and apply software containerisation principles.
• Manage applications built on Docker.
• Network various Docker applications and systems together.
• Understand and modify Docker registries.

Course Format

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

Customisation Options

• For bespoke training tailored to your needs, please get in touch to arrange a session.
• For further information on Docker, visit: https://www.docker.com

Master the skills required to build, deploy, and administer containerized environments utilizing Docker, Kubernetes, and OpenShift. This intensive five-day, hands-on training encompasses container images, Kubernetes workloads, cluster networking, storage solutions, security protocols, monitoring techniques, and practical OpenShift administration. Attendees will acquire the necessary expertise to operate modern container platforms effectively and troubleshoot applications across both development and production landscapes.

In this instructor-led, live training in Greece (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, enabling the creation of reproducible, portable, and scalable environments for machine learning systems.

Designed for intermediate to advanced technical professionals, this instructor-led live training—available online or onsite—focuses on containerizing and operationalizing comprehensive ML pipelines using Docker.

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

• Encapsulate ML training, validation, and inference workloads.
• Design 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 ecosystems.

Course Format

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

Customization Options

• For training tailored to specific ML infrastructure requirements, please reach out to discuss available options.

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

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) is designed for advanced-level professionals aiming to design and deploy distributed AI inference systems within heterogeneous environments.

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

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

Format of the Course

• Guided presentations and expert-led discussions.
• Extensive hands-on practice and applied exercises.
• Real-world experimentation in a controlled live-lab setup.

Course Customization Options

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

In this instructor-led live training Greece (onsite or remote), participants will learn how to deploy sample servers within containers and subsequently automate, scale, and manage these services in a Kubernetes cluster. The training covers advanced topics, guiding participants through the processes of securing, networking, and monitoring a Kubernetes environment.

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

• Set up and run Docker containers.
• Deploy containerized databases and servers.
• Configure a Docker and Kubernetes cluster.
• Utilize Kubernetes to deploy and manage multiple environments within the same cluster.
• Secure, scale, and monitor a Kubernetes cluster.

During this instructor-led live training in Greece, participants will learn the essentials of developing microservices using Spring Cloud and Docker. Understanding is validated through practical exercises and the incremental development of sample microservices.

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

• Understand the core principles 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.
• Utilize Docker Compose for end-to-end integration testing.

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

By the end 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.