Hybrid AI Deployment: Docker, Cloud, and Edge Integration Training Course

This instructor-led, live training in Australia (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 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.

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

Designed for intermediate-level professionals, this instructor-led live training (available online or onsite) focuses on packaging ML codebases, dependencies, and models using Docker to ensure reliable workflows from development through to production.

Upon completing this course, participants will be equipped to:

• Construct and maintain Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and dependencies within containers.
• Refine Docker environments to enhance performance and portability.
• Implement containerized ML services across diverse runtime environments.

Course Delivery Format

• Conceptual demonstrations facilitated by guided discussions.
• Practical exercises centred on real-world containerization challenges.
• Live implementation tasks using Docker lab environments.

Customisation Options

• Please get in touch to discuss tailoring this training to your specific organisational requirements.

CI/CD for AI is a structured approach to automating model packaging, testing, containerization, and deployment using continuous integration and continuous delivery pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

As the training concludes, participants will be able to:

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

Format of the Course

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations in a controlled environment.

Course Customization Options

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

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

Kubernetes has now become a leading platform for container orchestration.

NobleProg has been delivering Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have established ourselves as one of the most well-known training providers globally in the field of containerisation.

Since 2019, we have also been assisting our customers in validating their performance in Kubernetes environments by preparing them and encouraging them to sit for the CKA and CKAD examinations.

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 focuses on gaining practical experience in Kubernetes Administration; therefore, we recommend participating even if you do not intend to take the CKA exam.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training 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) programme was developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the stewards of Kubernetes.

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

Furthermore, the training emphasises gaining practical experience in Kubernetes application development. We recommend attending, even if you do not currently plan to sit for the CKAD exam.

NobleProg has been delivering Docker and Kubernetes training since 2015. With over 360 successfully completed training projects, we have become one of the most recognised training providers globally in the field of containerisation. Since 2019, we have also been assisting our customers in demonstrating their proficiency in Kubernetes environments by preparing them and encouraging them to pass the CKA and CKAD exams.

Course Format

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

Course Customisation Options

• To request bespoke 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 building, shipping, and running of applications within containers.

This instructor-led live training, available either online or onsite, targets engineers looking to deploy and manage software as containers rather than traditional standalone applications.

Upon completing this training, participants will be able to:

• Install and configure Docker.
• Comprehend and apply software containerisation principles.
• Manage applications built on Docker.
• Network disparate 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 laboratory environment.

Course Customisation Options

• To request a tailored training session for this course, please contact us to make arrangements.
• For further information on Docker, visit: https://www.docker.com

Learn how to build, deploy, and administer containerised 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 Australia (onsite or remote), participants will learn how to create and manage Docker containers, before deploying a sample application inside a container. Participants will also discover how to automate, scale, and manage their containerised applications within a Kubernetes cluster. Finally, the training covers 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 containerised 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 containerisation platform for creating reproducible, portable, and scalable environments tailored for ML systems.

This instructor-led, live training (delivered online or onsite) is designed for intermediate to advanced technical professionals looking to containerise and operationalise complete ML pipelines using Docker.

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

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

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centred on building real-world ML pipeline components.
• Live lab implementation of end-to-end containerised workflows.

Customisation Options

• For bespoke training aligned with specific ML infrastructure requirements, please get in touch to discuss available options.

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

Harnessing the power of GPU acceleration is critical for executing high-performance deep learning tasks with both scalability and efficiency.

This live, instructor-led training program (available online or on-site) is designed for intermediate technical professionals seeking to master the configuration, optimisation, and execution of GPU-enabled AI workloads within Docker containers.

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

• Construct and execute GPU-enabled containers specifically for model training and inference.
• Configure CUDA, drivers, and runtime libraries to support containerised AI workflows.
• Optimise resource allocation and isolation for applications that are intensive on GPU usage.
• Deploy scalable, containerised deep learning services in production settings.

Course Delivery Format

• Interactive instruction complemented by real-world demonstrations.
• Exercise-driven practice centred on GPU-enabled development.
• Hands-on implementation within a live-lab environment.

Customisation Options

• For training tailored to your specific infrastructure or GPU stack, please contact us to arrange details.

In this instructor-led live training in Australia (onsite or remote), participants will learn how to deploy a set of sample servers inside containers, then automate, scale, and manage these containerised servers within a Kubernetes cluster. The training advances to more complex topics, walking participants through the processes of securing, networking, and monitoring a Kubernetes cluster.

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

• Set up and run a Docker container.
• Deploy containerised databases and servers.
• Establish a Docker and Kubernetes cluster.
• Utilise Kubernetes to deploy and manage different environments within a single cluster.
• Secure, scale, and monitor a Kubernetes cluster.

In this instructor-led live training at Australia, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge will be tested through exercises and the step-by-step development of sample microservices.

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

• Understand the core concepts of microservices.
• Use Docker to build containers for microservice applications.
• Build and deploy containerised 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 Australia (online or onsite) is aimed at 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.

OpenShift is one of the leading Kubernetes-based platforms for deploying and managing containerised applications in cloud, hybrid, and on-premises environments.

This hands-on training teaches participants how to install, administer, and troubleshoot OpenShift clusters while applying security, networking, and storage best practices. Through practical exercises, participants gain the skills needed to confidently manage production-ready OpenShift environments.