GPU-Accelerated AI & Deep Learning with Docker Containers Training Course

This instructor-led, live training in Mexico (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 containerization platform that facilitates the creation of consistent, portable, and reproducible environments specifically designed for AI and machine learning tasks.

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

Upon finishing this course, participants will be capable of:

• Creating and managing Docker images customized for AI and ML applications.
• Containerizing machine learning pipelines, tools, and dependencies.
• Optimizing Docker environments to enhance performance and portability.
• Deploying containerized ML services across various runtime environments.

Course Format

• Concept demonstrations complemented by guided discussions.
• Practical exercises centered on real-world containerization challenges.
• Hands-on implementation using live Docker lab environments.

Customization Options

• To tailor this training to your organization's specific needs, please reach out to us to arrange a session.

CI/CD for AI represents a structured methodology for automating the packaging, testing, containerization, and deployment of models by leveraging continuous integration and continuous delivery pipelines.

This instructor-led live training, available either online or onsite, targets intermediate-level professionals seeking to automate end-to-end AI model delivery workflows utilizing Docker and CI/CD platforms.

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

• Establishing automated pipelines for constructing and testing AI model containers.
• Enforcing version control and reproducibility throughout the model lifecycle.
• Integrating automated deployment strategies for AI services.
• Applying 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.

Course Customization Options

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

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

Kubernetes has emerged as the leading platform for container orchestration.

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

Since 2019, we have also been assisting our clients in validating their Kubernetes skills by preparing them for and encouraging the pursuit of 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 expertise by passing the CKA exam.

Furthermore, the training emphasizes gaining practical experience in Kubernetes Administration. Therefore, we highly recommend participating, even if you do not plan to take the CKA exam.

Course Format

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

Course Customization Options

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

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

This instructor-led live training (available online or in-person) is designed for Developers who want to validate their abilities in designing, building, configuring, and exposing cloud-native applications on Kubernetes.

Additionally, the training emphasizes gaining hands-on experience in Kubernetes application development; therefore, we encourage participation 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 been helping our customers validate their performance in Kubernetes environments by preparing them to pass the CKA and CKAD exams.

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 make arrangements.
• To learn more about CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This instructor-led live training in Mexico (available online or on-site) is aimed at engineers who want to utilize Docker to deploy and manage software as containers instead of traditional standalone software.

By the end 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.

Learn how to build, deploy, and administer containerized 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 Mexico (onsite or remote), participants will learn how to create and manage Docker containers, followed by deploying a sample application inside a container. Participants will also learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. Furthermore, the training covers 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 designed to create reproducible, portable, and scalable environments for machine learning systems.

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

After completing this training, participants will be able to:

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

Course Format

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

Customization Options

• For tailored training aligned with specific ML infrastructure requirements, please reach out to discuss available options.

Course Objectives: Gain both theoretical and practical skills in Docker and Kubernetes.

Hybrid AI deployment involves executing AI inference across cloud, on-premises, and edge environments through unified, container-based workflows.

This instructor-led live training (available online or onsite) targets advanced professionals seeking to design and deploy distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will be able to:

• Develop 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.
• Enhance 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

• For tailored adjustments to align this course with your organization’s infrastructure or specific use cases, please contact us to customize the training.

In this instructor-led, live training in Mexico (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 in Mexico, participants will learn the fundamentals of building microservices using Spring Cloud and Docker. Participant knowledge is put to the test 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.

This instructor-led, live training in Mexico (online or onsite) targets intermediate developers and DevOps engineers looking 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 containerized 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.