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

This guided, live training in Argentina (online or at your location) is designed for engineers aiming to expand their Docker knowledge to deploy applications at scale while maintaining control.

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

• Create custom Docker images.
• Deploy and manage a large volume of Docker applications.
• Evaluate various container orchestration solutions to select the most appropriate option.
• Implement continuous integration workflows for Docker applications.
• Integrate Docker applications with existing continuous integration tools.
• Enhance the security of Docker applications.

Docker serves as a leading containerization platform, facilitating consistent, portable, and reproducible environments specifically for AI and machine learning operations.

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

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

• Construct and maintain Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and dependencies within containers.
• Refine Docker environments to enhance performance and ease of portability.
• Implement containerized ML services across diverse runtime environments.

Course Format

• Demonstrations of key concepts paired with guided discussions.
• Practical exercises centered on real-world containerization challenges.
• Application of concepts using live-lab Docker environments.

Customization Opportunities

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

CI/CD for AI is a structured approach to automating model packaging, testing, containerization, and deployment using continuous integration and continuous delivery pipelines.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to automate end-to-end AI model delivery workflows using Docker and CI/CD platforms.

As the training concludes, participants will be able to:

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

Format of the Course

• 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

• If your organization requires customized pipeline workflows or 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).

Today, Kubernetes stands 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 assisted our clients in validating their skills in Kubernetes environments by preparing them to pass the CKA and CKAD exams.

This instructor-led, live training (available online or on-site) 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 plan to take the CKA exam.

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.
• For more information about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

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

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

Additionally, the course emphasizes gaining practical experience in Kubernetes application development. We recommend participating even if you do not plan to sit for 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 assisted customers in validating their performance in Kubernetes environments by preparing 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 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 building, shipping, and running of applications within containers.

This instructor-led live training, available online or on-site, targets engineers looking to adopt Docker for deploying and managing software as containers rather than traditional standalone applications.

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

• Install and configure Docker.
• Comprehend and apply software containerization principles.
• Manage Docker-based applications effectively.
• Connect various Docker applications and systems via networking.
• Understand and manage Docker registries.

Course Format

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

Customization Options

• To request a customized training session for this course, please contact us to arrange details.
• For further information about Docker, 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 will acquire the skills necessary to operate modern container platforms and troubleshoot applications across both development and production environments.

In this instructor-led, live training in Argentina (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 powerful containerization platform, enabling the creation of reproducible, portable, and scalable environments essential for modern ML systems.

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

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

• Encapsulate ML training, validation, and inference workloads into containers.
• Architect and orchestrate comprehensive ML pipelines utilizing Docker and complementary tools.
• Establish versioning, ensure reproducibility, and implement CI/CD for ML components.
• Deploy, monitor, and scale ML services within containerized infrastructures.

Course Format

• Engaging lectures accompanied 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 customized options.

Training objectives: Acquire theoretical and operational skills in Docker and Kubernetes.

To execute high-performance deep learning tasks in a scalable and efficient way, GPU acceleration is a critical requirement.

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

By the end of this course, participants will have the capability to:

• Create and operate GPU-enabled containers for both training and inference processes.
• Set up CUDA, drivers, and runtime libraries to support containerized AI pipelines.
• Enhance resource allocation and ensure isolation for GPU-intensive applications.
• Implement scalable, containerized deep learning services in production settings.

Course Format

• Engaging instruction complemented by real-world examples.
• Practical exercises centered on GPU-enabled development.
• Live-lab hands-on implementation opportunities.

Customization Options

• To align training with your specific infrastructure or GPU stack, please reach out to us for a tailored arrangement.

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

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

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

• Create 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.

Format of the Course

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

Course Customization Options

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

In this instructor-led, live training in Argentina (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 in Argentina, participants will learn the essentials of building microservices using Spring Cloud and Docker. Knowledge is tested through exercises and the step-by-step creation 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 Argentina (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.