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

This guided, live training in Brazil (online or in-person) targets engineers who want to advance their Docker knowledge to deploy applications at a larger scale while maintaining control.

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

• Creating custom Docker images.
• Deploying and managing a high volume of Docker applications.
• Assessing various container orchestration solutions to select the most appropriate one.
• Establishing a continuous integration pipeline for Docker applications.
• Integrating Docker applications with existing CI tooling.
• Securing Docker applications.

Docker is a containerization platform designed to deliver consistent, portable, and reproducible environments for AI and machine learning workloads.

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

Upon completion, participants will be equipped to:

• Create and maintain Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and their dependencies.
• Enhance Docker environments for improved performance and portability.
• Deploy containerized ML services across various runtime environments.

Course Structure

• Conceptual demonstrations reinforced by guided discussions.
• Practical exercises centered on real-world containerization tasks.
• Real-world implementation within live-lab Docker environments.

Customization Options

• Reach out to us to tailor this training to your specific organizational environment.

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

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

Upon completing the training, participants will be capable of:

• Developing automated pipelines for constructing and validating AI model containers.
• Establishing version control and ensuring 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

• Should your organization require customized pipeline workflows or specific platform integrations, please reach out to us for course tailoring.

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 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 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) program was created 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 want to validate their skills in designing, building, configuring, and exposing cloud-native applications for Kubernetes.

Additionally, the training emphasizes gaining practical experience in Kubernetes application development, so we recommend participating even if you do not plan 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 recognized training companies worldwide 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.

Course Format

• Interactive lectures and discussions.
• Abundant 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 CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

Docker is an open-source platform for automating the process of building, shipping, and running applications inside containers.

This instructor-led live training (available online or onsite) targets engineers who want to deploy and manage software as containers rather than traditional stand-alone programs.

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

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

Course Format

• Interactive lectures and discussions.
• Abundant exercises and practice opportunities.
• 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 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.

This instructor-led live training, located in Brazil (onsite or remote), will teach participants how to create and manage Docker containers and deploy a sample application within one. Participants will also learn to automate, scale, and manage their containerized applications inside 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 powerful containerization platform that enables the creation of reproducible, portable, and scalable environments essential for modern ML systems.

This instructor-led training, available either online or onsite, is designed for intermediate to advanced technical professionals seeking to operationalize and containerize comprehensive ML pipelines using Docker.

Upon completing this training, participants will be equipped to:

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

Course Format

• Interactive lectures enhanced by practical, real-world demonstrations.
• Hands-on exercises dedicated to constructing genuine ML pipeline components.
• Live-lab sessions focused on implementing end-to-end containerized workflows.

Customization Options

• To tailor the training to specific ML infrastructure requirements, please reach out to discuss personalized options.

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

Unlocking the full potential of GPU acceleration is critical for executing high-performance deep learning tasks with both scalability and efficiency.

This instructor-led, live training session—available online or onsite—is designed for intermediate technical professionals seeking to master the configuration, optimization, and execution of GPU-enabled AI workloads within Docker containers.

By the end of this course, participants will possess the skills to:

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

Course Delivery Format

• Engaging instruction enhanced with practical, real-world demonstrations.
• Exercise-focused practice centered on GPU-enabled development workflows.
• Practical application within a live-lab environment.

Customization Options

• We can tailor the training to match your specific infrastructure or GPU stack; please reach out to discuss customization details.

Hybrid AI deployment involves executing AI inference across cloud, on-premises, and edge environments using 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:

• Create secure and scalable containerized AI services for multi-location setups.
• Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
• Leverage 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 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 Brazil (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 at Brazil, participants will learn the essentials of building microservices using Spring Cloud and Docker. Knowledge is reinforced 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 Brazil (online or onsite) targets 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.