Secure & Portable AI Inference with Docker: From Local to Cloud 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 robust containerization platform, facilitating the creation of consistent, portable, and reproducible environments specifically designed for AI and machine learning workloads.

This live, instructor-led training—available online or onsite—is tailored for intermediate-level professionals seeking to package ML codebases, dependencies, and models using Docker to establish reliable development-to-production workflows.

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 associated dependencies within containers.
• Refine Docker environments to maximize performance and ease of portability.
• Implement containerized ML services across diverse runtime environments.

Course Format

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

Customization Options

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

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

This instructor-led training, available either online or in-person, is designed for 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:

• Develop automated pipelines for constructing and testing AI model containers.
• Establish version control and reproducibility throughout model lifecycles.
• Incorporate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically tailored to machine learning operations (MLOps).

Format of the Course

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

Course Customization Options

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

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/

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) is targeted at engineers who want to utilize Docker for deploying and managing software as containers rather than traditional stand-alone applications.

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

• Install and set up Docker.
• Grasp and implement software containerization concepts.
• Manage Docker-based applications.
• Connect various Docker applications and systems via networking.
• Understand and modify Docker registries.

Course Format

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

Customization Options

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

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 live, instructor-led training session, available online or onsite, is tailored for intermediate to advanced technical professionals looking to containerize and operationalize full ML pipelines with Docker.

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

• Package ML training, validation, and inference workloads into containers.
• Architect and orchestrate comprehensive ML pipelines leveraging Docker and complementary tools.
• Establish versioning, 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 focused on constructing real-world ML pipeline components.
• Live-lab sessions implementing end-to-end containerized workflows.

Customization Options

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

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

Leveraging GPU acceleration is critical for executing high-performance deep learning tasks with both scalability and efficiency.

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

Upon completing this course, participants will be equipped to:

• Create and execute GPU-capable containers for both model training and inference.
• Set up CUDA, drivers, and runtime libraries to support containerized AI pipelines.
• Enhance resource allocation and isolation strategies for applications with heavy GPU demands.
• Launch scalable, container-based deep learning services in production settings.

Course Structure

• Engaging interactive instruction complemented by practical, real-world examples.
• Practice sessions focused specifically on GPU-enabled development tasks.
• Direct, hands-on implementation within a live-lab environment.

Customization Options

• For specialized training aligned with your specific infrastructure or GPU stack, please reach out to us to discuss arrangements.

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) is designed for advanced professionals seeking to design and deploy distributed AI inference systems within heterogeneous environments.

Upon completing this training, participants will be capable of:

• Developing secure and scalable containerized AI services for multi-site environments.
• Deploying AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Integrating orchestration tools to automate distributed AI operations.
• Enhancing inference latency, reliability, and resilience across diverse infrastructure.

Course Format

• Instructor-led presentations and expert discussions.
• Extensive hands-on practice with 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.

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.