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

This instructor-led, live training in Malaysia (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.

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

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

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

• Develop and manage Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and dependencies within containers.
• Enhance Docker environments to achieve superior performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Conceptual demonstrations accompanied by guided discussions.
• Hands-on exercises centered on real-world containerization challenges.
• Practical implementation utilizing live-lab Docker environments.

Customization Options

• To tailor this training to your specific organizational environment, please reach out to us to discuss arrangements.

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

This instructor-led, live training (available online or onsite) targets intermediate-level professionals who aim to streamline 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 validating AI model containers.
• Enforce version control and reproducibility across model lifecycles.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for 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 organisation requires tailored pipeline workflows or platform integrations, please reach out to us to customise this course.

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

Kubernetes has emerged as the premier 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 leading training providers globally in the field of containerization.

Since 2019, we have also supported our clients in validating their proficiency in Kubernetes 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.

Additionally, the training focuses on gaining practical experience in Kubernetes Administration; therefore, we recommend participation 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.

Course Customization Options

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

The Certified Kubernetes Application Developer (CKAD) programme has been established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

This instructor-led, live training (available online or onsite) is designed for Developers who wish 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. Therefore, we recommend participating even if you do not intend 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 renowned training companies globally in the field of containerization. Since 2019, we have also assisted our customers in validating their performance in the k8s environment by preparing them and encouraging them to pass the CKA and CKAD exams.

Course Format

• Interactive lecture and discussion.
• Ample exercises and practice.
• 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 for automating the creation, distribution, and operation of applications within containers.

This instructor-led live training, available either online or onsite, targets engineers who want to leverage Docker to deploy and manage software as containers rather than conventional standalone applications.

Upon completing this training, participants will be able to:

• Install and set up Docker.
• Grasp and apply software containerisation principles.
• Manage Docker-based applications.
• Network various Docker applications and systems.
• Understand and edit Docker registries.

Course Format

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

Customisation Options

• To request a tailored training session for this course, please reach out to us to arrange it.
• For more information on Docker, visit: https://www.docker.com

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

In this instructor-led live training in Malaysia (onsite or remote), participants will learn how to create and manage Docker containers and 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 progresses to 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 enabling the creation of reproducible, portable, and scalable environments for ML systems.

This instructor-led, live training session, available online or onsite, is designed for intermediate to advanced technical professionals seeking to containerize and operationalize 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 Delivery Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centered on constructing real-world ML pipeline components.
• Live-lab implementations for comprehensive containerized workflows.

Customization Options

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

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

Accelerating deep learning workloads via GPU is a critical requirement for achieving high-performance, scalable, and efficient results.

This live, instructor-led training session (available online or on-site) is designed for intermediate-level technical professionals aiming to configure, optimize, and execute GPU-enabled AI workloads within Docker containers.

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

• Create and manage GPU-enabled containers for both training and inference tasks.
• Set up CUDA, drivers, and runtime libraries specifically for containerized AI workflows.
• Refine resource allocation and isolation strategies for GPU-intensive applications.
• Implement scalable, containerized deep learning services in production settings.

Training Structure

• Interactive teaching methods complemented by real-world examples.
• Exercise-based practice sessions focused on GPU-enabled development.
• Practical application within a live-lab environment.

Customization Availability

• For training tailored to your specific infrastructure or GPU stack, please reach out to arrange a customized session.

In this instructor-led live training at Malaysia (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 Malaysia, participants will learn the essentials of building microservices using Spring Cloud and Docker. Knowledge is assessed through practical exercises and the incremental 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 Malaysia (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 stands as a premier Kubernetes-based platform for deploying and managing containerized applications in cloud, hybrid, and on-premises environments.

This practical training guides participants through the installation, administration, and troubleshooting of OpenShift clusters, while applying best practices for security, networking, and storage. Through hands-on exercises, participants acquire the skills necessary to confidently manage production-ready OpenShift environments.