Secure & Portable AI Inference with Docker: From Local to Cloud Training Course

This instructor-led, live training in South Korea (online or onsite) is designed for engineers looking to advance their Docker knowledge 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 leading containerization platform that provides consistent, portable, and reproducible environments specifically tailored for AI and machine learning workloads.

This live, instructor-led training, available online or on-site, is designed for intermediate-level professionals seeking to package ML codebases, dependencies, and models using Docker to ensure reliable workflows from development through production.

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

• Develop and administer Docker images specifically optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and dependencies within containers.
• Enhance Docker environments for improved performance and ease of migration.
• Implement containerized ML services across various runtime settings.

Training Structure

• Conceptual demonstrations accompanied by facilitated discussions.
• Practical exercises centered on real-world containerization challenges.
• Applied implementation utilizing live-lab Docker setups.

Customization Options

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

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

This instructor-led live training, available online or in-person, is designed for intermediate-level professionals seeking to automate end-to-end AI model delivery workflows utilizing Docker and CI/CD platforms.

Upon completing the training, participants will be able to:

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

Course Format

• Instructor-guided presentations and technical discussions.
• Practical labs and hands-on implementation exercises.
• Realistic CI/CD workflow simulations within 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 developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as the leading platform for container orchestration today.

NobleProg has been providing Docker & Kubernetes training since 2015. With over 360 successfully completed training projects, we have established ourselves as one of the most recognized training companies 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 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; therefore, we recommend participating even if you do not intend to take the CKA exam.

Course Format

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

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

This instructor-led, live training—available either online or on-site—is designed for developers who wish to validate their proficiency in designing, building, configuring, and exposing cloud-native applications within Kubernetes environments.

Moreover, the program emphasizes practical, hands-on experience in Kubernetes application development. Therefore, we recommend participating in this course 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 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 performance in Kubernetes environments by preparing them to pass the CKA and CKAD examinations.

Course Format

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

Course Customization Options

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

Docker is an open-source platform designed to automate the process of building, shipping, and running applications within containers.

This instructor-led live training (available online or onsite) targets engineers who want to deploy and manage 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.

Course Format

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

Customization Options

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

Learn to build, deploy, and administer containerized environments leveraging Docker, Kubernetes, and OpenShift. This intensive five-day, hands-on training covers container images, Kubernetes workloads, cluster networking, storage, security, monitoring, and practical OpenShift administration. Participants will acquire the essential skills required to operate modern container platforms and troubleshoot applications across both development and production settings.

In this instructor-led live training in South Korea (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 containerization platform that enables the creation of reproducible, portable, and scalable environments for machine learning systems.

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

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

• Encapsulate ML training, validation, and inference workloads within containers.
• Architect and orchestrate end-to-end ML pipelines leveraging Docker and complementary tools.
• Establish versioning, reproducibility, and CI/CD workflows for ML components.
• Deploy, monitor, and scale ML services within containerized infrastructure.

Course Format

• Interactive lectures complemented by practical demonstrations.
• Hands-on exercises centered on constructing real-world ML pipeline components.
• Live lab sessions implementing end-to-end containerized workflows.

Customization Options

• To discuss tailored training aligned with specific ML infrastructure requirements, please contact us to explore available options.

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

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

This live, instructor-led training, available online or onsite, is designed for intermediate technical professionals looking to set up, fine-tune, and execute GPU-based AI workloads within Docker containers.

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

• Construct and execute GPU-enabled containers for both model training and inference tasks.
• Set up CUDA, drivers, and runtime libraries to support containerized AI pipelines.
• Refine resource allocation and isolation strategies for GPU-intensive applications.
• Launch scalable, containerized deep learning services in production settings.

Course Structure

• Engaging instruction reinforced by practical, real-world examples.
• Exercise-based practice centered on GPU-centric development.
• Practical implementation in a live-lab setting.

Customization Opportunities

• For training specifically tailored to your infrastructure or GPU stack, please reach out to schedule a consultation.

Hybrid AI deployment involves executing AI inference across cloud infrastructure, on-premise servers, and edge devices through unified container-based workflows.

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

Upon completing this training, participants will be able to:

• Construct secure and scalable containerized AI services suitable for multi-location setups.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Utilize orchestration tools to automate distributed AI operations.
• Enhance inference latency, reliability, and resilience across varied infrastructure.

Course Format

• In-depth presentations and expert-led discussions.
• Extensive hands-on practice and practical exercises.
• Real-world experimentation within a controlled live-lab environment.

Customization Options

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

In this instructor-led, live training in South Korea (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 conducted in South Korea, participants will learn the foundational aspects of constructing microservices using Spring Cloud and Docker. Knowledge is reinforced through exercises and the step-by-step creation of sample microservices.

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

• Understand the core principles of microservices.
• Employ Docker to build containers for microservice applications.
• Develop and deploy containerized microservices using Spring Cloud and Docker.
• Integrate microservices with service discovery tools and the Spring Cloud API Gateway.
• Apply Docker Compose for thorough end-to-end integration testing.

This instructor-led, live training in South Korea (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.