Online or onsite, instructor-led live Docker training courses demonstrate through interactive discussion and hands-on practice how to set up Docker for developing and deploying containerized applications.
Docker training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Natal onsite live Docker trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
Docker training courses cover setup and management of Docker containers, including scaling and orchestration with Kubernetes.
NobleProg -- Your Local Training Provider
Natal - Hub Plural
Rio Grande do Norte Natal, Natal, brazil, 59016-000
Unleash your creativity in the heart of Alecrim with flexible working at Hub Plural Natal. In this vibrant neighborhood southwest of downtown Natal, you're surrounded by a wide variety of creative businesses. It's a great place to build your network.
CI/CD for AI represents a structured methodology for automating the packaging, testing, containerization, and deployment of AI models through continuous integration and delivery pipelines.
This instructor-led live training, available online or onsite, is designed for intermediate-level professionals seeking to automate end-to-end AI model delivery workflows using Docker alongside CI/CD platforms.
Upon completion of the training, participants will be equipped to:
Develop automated pipelines for constructing and testing AI model containers.
Establish version control and ensure reproducibility throughout the model lifecycle.
Incorporate automated deployment strategies for AI services.
Apply CI/CD best practices specifically adapted for machine learning operations.
Course Format
Instructor-led presentations accompanied by 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 to tailor this course to your needs.
Hybrid AI deployment involves executing AI inference across cloud, on-premise, and edge environments through unified, container-based workflows.
This instructor-led live training, available online or onsite, is designed for advanced professionals seeking to architect and deploy distributed AI inference systems across heterogeneous infrastructures.
After completing this training, participants will be equipped to:
Construct secure and scalable containerized AI services for multi-site environments.
Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
Implement orchestration tools to automate distributed AI operations.
Enhance inference latency, reliability, and resilience across diverse infrastructure.
Course Format
Guided presentations complemented by expert-led discussions.
Ample hands-on practice and applied 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 reach out to us for customization.
Docker is a containerization platform utilized to create portable, isolated, and secure deployment environments for AI inference services.
This instructor-led live training, available online or onsite, is designed for beginner to intermediate-level technical professionals who aim to develop secure, portable AI inference microservices capable of consistent deployment across local machines, servers, or cloud virtual machines.
Upon completing this workshop, participants will be able to:
Build lightweight inference containers suitable for both local and cloud deployment.
Secure containerized AI services by applying best-practice techniques.
Implement portable microservice workflows to ensure consistent environments.
Deploy AI inference endpoints across various infrastructures.
Course Format
Guided lectures combined with practical demonstrations.
Hands-on exercises to reinforce deployment and security techniques.
Live-lab practice for constructing and running portable inference services.
Course Customization Options
To tailor this training to your specific infrastructure or AI tooling stack, please contact us to arrange.
In this instructor-led live training in Natal (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.
GPU acceleration is crucial for executing high-performance deep learning tasks in a scalable and efficient manner.
This instructor-led live training, available online or onsite, targets intermediate-level technical professionals seeking to configure, optimize, and run GPU-enabled AI workloads within Docker containers.
Upon completing this course, participants will be able to:
Build and run GPU-enabled containers for training and inference tasks.
Configure CUDA, drivers, and runtime libraries for containerized AI workflows.
Optimize resource allocation and isolation for GPU-intensive applications.
Deploy scalable, containerized deep learning services in production environments.
Course Format
Interactive instruction supported by real-world demonstrations.
Exercise-driven practice focused on GPU-enabled development.
Hands-on implementation in a live-lab environment.
Course Customization Options
For tailored training aligned with your infrastructure or GPU stack, please contact us to arrange.
Docker serves as a containerization platform designed to build reproducible, portable, and scalable environments for machine learning systems.
This instructor-led live training, available either online or on-site, targets intermediate to advanced technical professionals looking to containerize and operationalize complete ML pipelines using Docker.
Upon completing this training, participants will be able to:
Containerize ML training, validation, and inference workloads.
Design and orchestrate end-to-end ML pipelines using Docker and complementary tools.
Implement versioning, reproducibility, and CI/CD practices for ML components.
Deploy, monitor, and scale ML services within containerized environments.
Course Format
Interactive lectures supported by practical demonstrations.
Hands-on exercises focused on constructing real-world ML pipeline components.
Live lab implementation for end-to-end containerized workflows.
Customization Options
For training tailored to specific ML infrastructure requirements, please contact us to discuss available options.
Docker serves as a containerization platform that facilitates consistent, portable, and reproducible environments for artificial intelligence and machine learning workloads.
This instructor-led live training, available online or onsite, targets intermediate professionals aiming to package ML codebases, dependencies, and models using Docker to establish reliable development-to-production workflows.
Upon completing this course, participants will be able to:
Create and manage Docker images specifically designed for AI and ML applications.
Containerize machine learning pipelines, tools, and dependencies.
Optimize Docker environments for improved performance and portability.
Deploy containerized ML services across various runtime environments.
Course Format
Concept demonstrations supported by guided discussions.
Hands-on exercises centered on real-world containerization tasks.
Practical implementation using live-lab Docker environments.
Customization Options
To tailor this training to your organization's specific environment, please contact us to make arrangements.
This instructor-led, live training in Natal (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.
This instructor-led live training, located in Natal (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.
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/
This instructor-led, live course in Natal provides participants with an overview of Rancher and demonstrates through hands-on practice how to deploy and manage a Kubernetes cluster with Rancher.
This guided, live training in Natal (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.
This instructor-led, live training in Natal (online or onsite) is designed for engineers who wish to utilize Docker to deploy and manage software as containers, moving away from 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.
In this instructor-led live training held at Natal, 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.
OpenShift Container Platform v4 is an enterprise-grade Kubernetes platform created by Red Hat, designed to automate the deployment, scaling, and management of containerized applications.
This instructor-led, live training (available online or onsite) targets system administrators and DevOps engineers who wish to deploy, manage, and operate OpenShift clusters in production environments.
The course provides a hands-on approach to installing and managing OpenShift 4 clusters, working with Operators, securing workloads, and operating applications at scale.
the trainer had a lot of knowledge and patience to share with us
Bogdan Olaru
Course - Introduction to Docker
The knowledge and exchanges with Augustin
Laurent - L'Office national des vacances annuelles (ONVA)
Course - Docker and Kubernetes
we learn new technique on doing the configuration
Christian - Beacon Solutions Inc
Course - Kubernetes from Basic to Advanced
The trainer's broad knowledge, his abilities to solve issues that spontaneously occurred during the practice sessions. Also, the exercises themselves are adequate to help fix the subjects contained in the course.
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