Containerized AI & ML Deployment with Docker Training Course

This instructor-led, live training in Italy (online or onsite) is designed for engineers who wish to deepen their Docker knowledge to deploy applications at scale while maintaining control.

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

• Creating custom Docker images.
• Deploying and managing a high volume of Docker applications.
• Evaluating various container orchestration solutions and selecting the most appropriate one.
• Establishing a continuous integration workflow for Docker applications.
• Integrating Docker applications into existing continuous tooling processes.
• Ensuring the security of Docker applications.

Upon completion 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 one.
• Establish a continuous integration workflow for Docker applications.
• Integrate Docker applications into existing continuous integration toolchains.
• Enhance the security of Docker applications.
• Utilize Kubernetes to deploy and manage diverse environments within a single cluster.
• Secure, scale, and monitor a Kubernetes cluster.

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, targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

Upon completing the training, participants will be able to:

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

Course Format

• Instructor-led 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).

Kubernetes has become a leading platform for container orchestration.

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

Since 2019, we have also been supporting our customers in validating their skills in k8s environments by preparing them 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.

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

Course Format

• Interactive lectures and discussions.
• Abundant 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.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) certification program was created by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the organization responsible for hosting Kubernetes.

This instructor-led, live training (available online or in-person) is designed for developers looking 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. Therefore, we recommend participating even if you do not plan to take the CKAD exam.

NobleProg has been providing Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most renowned training providers globally in the field of containerization. Since 2019, we have also been assisting our customers in validating their performance in Kubernetes 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.

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 creation, distribution, and execution of applications within containers.

This instructor-led live training (available online or onsite) targets engineers who want to shift from deploying traditional standalone software to managing software as containers using Docker.

Upon completing this training, participants will be able to:

• Install and configure Docker.
• Comprehend and apply software containerization techniques.
• Manage applications built on Docker.
• Establish networks between various Docker applications and systems.
• Understand and modify Docker registries.

Course Format

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

Customization Options

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

Acquire the skills to build, deploy, and administer containerized environments utilizing Docker, Kubernetes, and OpenShift. This five-day, hands-on training encompasses container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants will gain the necessary competencies to operate modern container platforms and troubleshoot applications across both development and production environments.

In this instructor-led, live training in Italy (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 tailored for machine learning systems.

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

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

• Package ML training, validation, and inference workloads into containers.
• Architect and orchestrate full ML pipelines utilizing Docker alongside complementary tools.
• Establish versioning, reproducibility, and CI/CD workflows for ML components.
• Deploy, monitor, and scale ML services within containerized infrastructures.

Course Delivery Model

• Engaging lectures reinforced by practical demonstrations.
• Practical exercises centered on constructing real-world ML pipeline elements.
• Live laboratory sessions dedicated to implementing end-to-end containerized workflows.

Customization Opportunities

• To explore tailored training that aligns with your specific ML infrastructure requirements, please reach out to discuss available options.

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

GPU acceleration plays a pivotal role in executing high-performance deep learning workloads with both scalability and efficiency.

Designed for intermediate-level technical professionals, this instructor-led live training (available online or onsite) equips participants with the skills to configure, optimize, and operate GPU-enabled AI workloads within Docker containers.

By the end of the program, attendees will be empowered to:

• Develop and execute GPU-enabled containers for both model training and inference tasks.
• Set up CUDA, drivers, and runtime libraries tailored for containerized AI workflows.
• Refine resource allocation and isolation strategies for GPU-intensive applications.
• Deploy scalable, containerized deep learning services suitable for production environments.

Course Delivery Method

• Engaging interactive instruction complemented by real-world demonstrations.
• Practical, exercise-driven sessions centered on GPU-enabled development.
• Direct hands-on implementation within a live-lab setting.

Customization Opportunities

• Seeking training tailored to your specific infrastructure or GPU stack? Reach out to us to arrange a customized experience.

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 professionals aiming to design and deploy distributed AI inference systems within heterogeneous infrastructures.

Upon completing this course, participants will be able to:

• Create secure and scalable containerized AI services suitable for multi-site environments.
• Deploy AI inference workloads across 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 setups.

Course Format

• Guided presentations coupled with expert-led discussions.
• Extensive hands-on practice with applied exercises.
• Real-world experimentation within 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 to customize the training content.

Through this instructor-led live training in Italy (onsite or remote), participants will learn how to deploy a set of sample servers inside containers. They will then master the automation, scaling, and management of these containerized servers within a Kubernetes cluster. The course progresses to more advanced topics, guiding participants through the processes of securing, networking, and monitoring a Kubernetes cluster.

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

• Setting up and running a Docker container.
• Deploying containerized databases and servers.
• Establishing a Docker and Kubernetes cluster.
• Utilizing Kubernetes to deploy and manage diverse environments under a single cluster.
• Securing, scaling, and monitoring a Kubernetes cluster.

During this instructor-led, live training held in Italy, participants will acquire the essential skills for building microservices using Spring Cloud and Docker. Knowledge is reinforced 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.

This instructor-led live training in Italy (online or onsite) targets intermediate-level developers and DevOps engineers who wish to construct, 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.