Docker Training in Hsinchu

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

This instructor-led live training, available both online and onsite, targets intermediate-level professionals aiming 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 for machine learning operations.

Course Format

• 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

• For organizations requiring customized pipeline workflows or specific platform integrations, please contact us to tailor this course to your needs.

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 seeking to design and deploy distributed AI inference systems across heterogeneous environments.

Upon completing this training, participants will be able to:

• Construct 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.

Course Format

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

Customization Options

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

Docker serves as a containerization platform designed to establish portable, isolated, and secure deployment environments for AI inference services.

This instructor-led live training, available online or onsite, targets beginner to intermediate technical professionals seeking to develop secure, portable AI inference microservices that deploy consistently across local machines, servers, and cloud VMs.

Upon completing this workshop, participants will be capable of:

• Constructing lightweight inference containers suitable for both local and cloud deployment.
• Securing containerized AI services through best-practice techniques.
• Establishing portable microservice workflows to ensure consistent environments.
• Deploying AI inference endpoints across diverse infrastructure setups.

Course Format

• Guided lectures combined with practical demonstrations.
• Hands-on exercises to reinforce deployment and security methodologies.
• Live-lab practice focused on building and running portable inference services.

Customization Options

• To customize this training for your specific infrastructure or AI tooling stack, please contact us to arrange.

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

GPU acceleration is critical for executing high-performance deep learning workloads in a scalable and efficient manner.

This instructor-led, live training (available online or onsite) is designed for intermediate-level technical professionals who want to configure, optimize, and deploy GPU-enabled AI workloads within Docker containers.

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

• Build and run GPU-enabled containers for training and inference.
• Configure CUDA, drivers, and runtime libraries for containerized AI workflows.
• Optimize resource allocation and isolation for GPU-intensive applications.
• Deploy scalable, containerized deep learning services in production environments.

Format of the Course

• Interactive instruction supported by real-world demonstrations.
• Exercise-driven practice focused on GPU-enabled development.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

Docker serves as a containerization platform designed to build reproducible, portable, and scalable environments for machine learning systems.

This instructor-led, live training (available online or onsite) targets intermediate to advanced technical professionals who aim to containerize and operationalize complete ML pipelines using Docker.

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

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

Course Format

• Interactive lectures supplemented by practical demonstrations.
• Hands-on exercises focused on building real ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Course Customization Options

• For customized training aligned with specific ML infrastructure needs, please contact us to discuss options.

Docker serves as a containerization platform designed to establish consistent, portable, and reproducible environments for artificial intelligence and machine learning applications.

This instructor-led live training, available online or onsite, targets intermediate professionals seeking to package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development to production.

Upon completing this course, participants will be able to:

• Create and manage Docker images specifically designed for AI and ML applications.
• Containerize machine learning pipelines, tools, and their dependencies.
• Optimize Docker environments for enhanced performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Format

• Concept demonstrations supported by guided discussion.
• Hands-on exercises focused on real-world containerization tasks.
• Practical implementation using live-lab Docker environments.

Customization Options

• To tailor this training to your organization's specific needs, please contact us to make arrangements.

This instructor-led live training in Hsinchu (online or onsite) targets intermediate-level developers and DevOps engineers aiming to build, deploy, and manage microservices using Spring Cloud and Docker.

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

• Develop microservices utilizing Spring Boot and Spring Cloud.
• Containerize applications using Docker and Docker Compose.
• Implement service discovery, API gateways, and inter-service communication.
• Monitor and secure microservices within production environments.
• Deploy and orchestrate microservices using Kubernetes.

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

Through this instructor-led, live training in Hsinchu (onsite or remote), participants will learn to create and manage Docker containers and deploy a sample application within one. Attendees will also gain skills in automating, scaling, and managing containerized applications using a Kubernetes cluster. The training concludes with advanced topics, guiding participants through the processes of securing, scaling, and monitoring a Kubernetes cluster.

Upon completing this training, participants will be able to:

• Set up and operate a Docker container.
• Deploy a containerized server and web application.
• Build and manage Docker images.
• Configure a Docker and Kubernetes cluster.
• Utilize Kubernetes to deploy and manage a clustered web application.
• Secure, scale, and monitor a Kubernetes cluster.

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

Kubernetes has emerged as a leading platform for container orchestration.

NobleProg has been delivering Docker & 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 k8s environments by preparing them for and encouraging 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, so we recommend participating even if you do not intend to take the CKA exam.

Course Format

• Interactive lecture and discussion.
• Extensive 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 CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The primary goal of this hands-on course is to equip participants with all the essential tools required to address the practical aspects of Docker and Kubernetes. This ensures they possess the necessary skills to effectively manage these technologies.

In this instructor-led, live training in Hsinchu, participants will learn how to manage Red Hat OpenShift Container Platform.

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

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerized applications on-premise, in public cloud or on a hosted cloud.
• Secure OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

In this instructor-led, live training in Hsinchu, participants will learn how to utilize the OpenShift Container Platform to deploy containerized applications.

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

• Create and configure an OpenShift setup.
• Quickly deploy applications on-premise, in a public cloud, or on a hosted cloud.

The Certified Kubernetes Application Developer (CKAD) credential was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the governing body for Kubernetes.

This instructor-led live training (available online or onsite) is designed for developers who want to validate their ability to design, build, configure, and expose cloud-native applications on Kubernetes.

Additionally, the training emphasizes practical experience in Kubernetes application development, so we highly recommend attending 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 recognized training providers globally in the field of containerization. Since 2019, we have also helped our customers validate their performance in Kubernetes environments by preparing and encouraging them to pass the CKA and CKAD exams.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice.
• Hands-on implementation in a live laboratory 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/

This instructor-led, live course in Hsinchu provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.

This instructor-led live training, available online or onsite, is aimed at engineers who wish to evaluate each of these services to make informed decisions about which to deploy within their organization.

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

• Set up a development environment that includes all needed libraries, packages, and frameworks to start developing.
• Set up, configure, and deploy a series of demo containers using a number of different approaches.
• Understand the architectural and design differences among different Docker and Kubernetes solutions within AWS.
• Automate the deployment of Docker containers.
• Set up a continuous integration and deployment pipeline.
• Integrate Docker and Kubernetes into an existing continuous integration system.

This instructor-led, live training in Hsinchu (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 platform enabling developers and system administrators to manage distributed applications. It comprises a runtime environment for executing containers and a service facilitating the sharing of containers.

Using Docker, the same application can operate without modification across laptops, dedicated servers, and virtual machines.

During the first two days, this course covers the fundamental usage of Docker, offering value to both developers and system administrators. The curriculum features numerous hands-on exercises, allowing participants to practice within their own Docker environments and construct their own Docker images.

On the final day, participants will explore advanced tools that complement Docker, specifically Docker Machine, Docker Compose, and Docker Swarm.

This instructor-led, live training in Hsinchu (online or on-site) is targeted at engineers who want to adopt Docker for deploying and managing software as containers rather than as traditional standalone applications.

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

• Install and configure Docker.
• Understand and implement software containerization.
• Manage Docker-based applications.
• Network different Docker applications and systems.
• Understand and edit Docker registries.

Docker is a platform that enables developers and system administrators to manage distributed applications. It comprises a runtime environment for executing containers and a service facilitating container sharing.

Using Docker, the same application can run seamlessly without modification across laptops, dedicated servers, and virtual servers.

This course covers the fundamental usage of Docker, benefiting both developers and system administrators. The curriculum features extensive hands-on exercises, allowing participants to practice within their own Docker environments and construct their own Docker images over the course of two days.

This instructor-led, live training in Hsinchu (online or onsite) is aimed at DevOps engineers who wish to optimize and simplify the CI/CD process with Docker and Jenkins.

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

• Automate code delivery and pipeline deployment with Jenkins.
• Build an application using Docker and Docker File.
• Configure authentication options to strengthen security.

Course Format

• Engaging interactive lectures paired with open discussions.
• Extensive exercises and practical sessions designed to reinforce learning.
• Hands-on implementation within a live-lab environment for real-world application.

Customization Options

• Interested in a tailored training experience? Reach out to us to arrange a customized course.

In this instructor-led, live training in Hsinchu, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge will be assessed through exercises and the step-by-step 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.

OpenShift Container Platform v4 is an enterprise-ready Kubernetes platform developed by Red Hat, designed to automate the deployment, scaling, and management of containerised applications.

This instructor-led, live training (online or onsite) is aimed at system administrators and DevOps engineers who wish to deploy, manage, and operate OpenShift clusters in production environments.

The course provides a hands-on approach to installing and managing OpenShift 4 clusters, working with Operators, securing workloads, and operating applications at scale.

This instructor-led, live training (available online or onsite) targets DevOps engineers who want to leverage Selenium to execute tests within Docker containers.

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

• Establish test automation infrastructure for on-demand testing.
• Develop a test automation framework using Java.
• Construct a CI/CD pipeline from the ground up using Jenkins and Docker.