Containerized AI & ML Deployment with Docker Training Course

This live, instructor-led training in Denmark, offered online or on-site, is designed for engineers looking to enhance their Docker proficiency. It focuses on deploying applications at scale while ensuring robust control.

By the end of the course, participants will be capable of:

• Building custom Docker images.
• Deploying and managing large numbers of Docker applications.
• Evaluating container orchestration solutions to select the most appropriate one.
• Establishing a continuous integration workflow for Docker applications.
• Integrating Docker applications with existing continuous integration tools and processes.
• Securing Docker applications.

Upon completion, participants will have the skills to:

• Construct custom Docker images.
• Deploy and oversee high volumes of Docker applications.
• Assess various container orchestration tools and select the optimal solution.
• Establish continuous integration workflows for Docker-based applications.
• Connect Docker applications to existing continuous integration pipelines.
• Implement robust security measures for Docker applications.
• Leverage Kubernetes to manage multiple environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters effectively.

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

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

Upon completion, participants will be equipped to:

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

Course Format

• Instructor-led presentations and in-depth technical discussions.
• Hands-on labs and practical implementation exercises.
• Realistic CI/CD workflow simulations within a controlled environment.

Customization Options

• If your organization requires bespoke pipeline workflows or specific platform integrations, please reach out to tailor this course to your needs.

The Certified Kubernetes Administrator (CKA) program is developed by The Linux Foundation in collaboration with the Cloud Native Computing Foundation (CNCF).

Kubernetes has established itself as the leading platform for container orchestration.

NobleProg has been delivering Docker and Kubernetes training since 2015. Having successfully completed over 360 training projects, we are recognized globally as one of the premier training providers in the field of containerization.

Since 2019, we have also been supporting clients in validating their performance within k8s environments by preparing them for, and encouraging them to pass, the CKA and CKAD exams.

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

Alternatively, the training emphasizes gaining practical experience in Kubernetes Administration. Therefore, we recommend participating in this course even if you do not intend to sit for the CKA exam.

Course Format

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

Customization Options

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

The Certified Kubernetes Application Developer (CKAD) certification program was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the primary host of the Kubernetes ecosystem.

This live, instructor-led training (available online or on-site) is designed for developers seeking to validate their capabilities in designing, building, configuring, and exposing cloud-native applications within Kubernetes.

Furthermore, the curriculum emphasizes practical experience in Kubernetes application development. Therefore, we strongly recommend participating in this course, even if you do not plan to sit for the CKAD exam.

NobleProg has been providing Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognized training providers worldwide in the field of containerization. Since 2019, we have also assisted clients in validating their performance in k8s environments by preparing them to pass the CKA and CKAD exams.

Course Format

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

Customization Options

• For customized training tailored to your needs, please contact us to make arrangements.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

Docker serves as a leading open-source platform designed to streamline and automate the creation, distribution, and execution of applications within isolated container environments.

This live training session, conducted either virtually or in-person, is specifically tailored for engineers looking to shift their deployment and management strategies from traditional stand-alone software models to a containerized approach using Docker.

Upon successful completion of this course, participants will be equipped to:

• Install and configure the Docker environment.
• Grasp and apply the principles of software containerization.
• Effectively manage Docker-based applications.
• Establish networking between various Docker applications and systems.
• Interpret and modify Docker registries.

Course Delivery Format

• Engaging lectures combined with facilitated discussions.
• Extensive practical exercises and drills.
• Hands-on implementation within a live-lab setting.

Customization Options

• For bespoke training arrangements, please get in touch to discuss your specific requirements.
• For further insights into Docker, refer to: https://www.docker.com

Discover how to build, deploy, and manage 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 will acquire the skills necessary to operate modern container platforms and troubleshoot applications across development and production settings.

In this instructor-led, live training delivered Denmark (either onsite or remotely), participants will learn how to create and manage Docker containers, followed by deploying a sample application within a container. They will also discover how to automate, scale, and manage containerized applications within a Kubernetes cluster. The training concludes with advanced topics, guiding participants through the essential processes of securing, scaling, and monitoring a Kubernetes cluster.

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

• Establish and run Docker containers.
• Deploy containerized server and web applications.
• Build and manage Docker images.
• Set up Docker and Kubernetes clusters.
• Use Kubernetes to deploy and manage clustered web applications.
• Secure, scale, and monitor Kubernetes clusters.

Docker serves as a powerful containerization platform, enabling the creation of portable, reproducible, and scalable environments tailored for ML systems.

This instructor-led live training, available online or onsite, is designed for intermediate to advanced technical professionals looking to operationalize and containerize complete ML pipelines using Docker.

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

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

Course Format

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

Customization Options

• To explore customized training aligned with specific ML infrastructure requirements, please reach out to discuss available options.

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

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

This live, instructor-led course (available online or on-site) is designed for mid-level technical professionals looking to set up, fine-tune, and execute GPU-enabled AI workloads within Docker containers.

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

• Create and execute GPU-enabled containers for both training and inference tasks.
• Set up CUDA, drivers, and runtime libraries to support containerized AI workflows.
• Enhance resource allocation and isolation for applications with heavy GPU demands.
• Implement scalable, containerized deep learning services in production settings.

Course Format

• Engaging instruction complemented by practical, real-world examples.
• Practice sessions centered on GPU-enabled development through exercises.
• Practical application in a live-lab setting.

Customization Options

• Reach out to us to discuss and arrange tailored training that aligns with your specific infrastructure or GPU setup.

Hybrid AI deployment involves executing AI inference across cloud, on-premise, and edge environments within a unified, container-based workflow.

This instructor-led, live training session (available online or onsite) is designed for advanced professionals seeking to architect and deploy distributed AI inference systems across diverse environments.

Upon completion, participants will be equipped to:

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

Course Format

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

Customization Options

• To tailor the course to your organization’s specific infrastructure or use cases, please contact us for customized training.

In this live, instructor-led training session in Denmark (onsite or remote), participants will learn how to deploy a collection of sample servers inside containers. They will then explore how to automate, scale, and manage these containerized servers within a Kubernetes cluster. The training progresses to 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.

During this instructor-led, live training conducted in Denmark, participants will explore the essentials of constructing microservices with Spring Cloud and Docker. Attendees will validate their understanding through hands-on exercises and the iterative development of sample microservices.

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

• Comprehend the basics of microservices architecture.
• Utilize Docker to build containers for microservice applications.
• Create and deploy containerized microservices using Spring Cloud and Docker.
• Integrate microservices with discovery services and the Spring Cloud API Gateway.
• Apply Docker Compose for end-to-end integration testing.

This live, instructor-led training in Denmark (online or on-site) is designed for intermediate-level developers and DevOps engineers looking 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.