Hybrid AI Deployment: Docker, Cloud, and Edge Integration Training Course

This instructor-led, live training in Turkey (online or on-site) targets engineers who wish to enhance their Docker knowledge 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 manage a 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 integration processes.
• Secure their Docker applications.

By the end of this training, participants will be capable of:

• Creating custom Docker images.
• Deploying and managing a high volume of Docker applications.
• Evaluating various container orchestration platforms and selecting the most appropriate solution.
• Establishing a continuous integration pipeline for Docker applications.
• Integrating Docker applications into existing CI/CD toolchains.
• Implementing security best practices for Docker applications.
• Utilizing Kubernetes to deploy and manage diverse environments within a single cluster.
• Securing, scaling, and monitoring a Kubernetes cluster.

Docker serves as a robust containerization platform, facilitating the creation of consistent, portable, and reproducible environments specifically designed for AI and machine learning tasks.

This live, instructor-led training session, available either online or onsite, is designed for intermediate-level professionals seeking to encapsulate ML codebases, dependencies, and models using Docker to ensure seamless development-to-production transitions.

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

• Develop and oversee Docker images optimized for AI and ML applications.
• Encapsulate machine learning pipelines, tools, and their dependencies within containers.
• Enhance Docker environments to prioritize both performance and portability.
• Implement containerized ML services across various runtime environments.

Course Structure

• Conceptual demonstrations accompanied by facilitated discussions.
• Practical exercises centered on real-world containerization challenges.
• Implementation through interactive, live-lab Docker environments.

Customization Possibilities

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

CI/CD for AI provides a systematic framework for automating the packaging, testing, containerization, and deployment of models through continuous integration and delivery pipelines.

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

By the conclusion of the training, participants will be able to:

• Establish automated pipelines for constructing and validating AI model containers.
• Ensure version control and reproducibility throughout the model lifecycle.
• Integrate automated deployment strategies for AI services.
• Apply CI/CD best practices specifically adapted for machine learning operations.

Course Format

• Instructor-guided presentations and technical discussions.
• Practical labs with 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 now become a leading platform for container orchestration.

NobleProg has been delivering Docker & Kubernetes training since 2015. With more than 360 successfully completed training projects, we have become one of the best-known training companies worldwide in the field of containerization.

Since 2019, we have also been helping our customers confirm their performance in k8s environments by preparing them and encouraging them to pass the CKA and CKAD exams.

This instructor-led, live training (available online or onsite) is aimed at System Administrators and Kubernetes users who wish to confirm their knowledge by passing the CKA exam.

On the other hand, the training is also focused on gaining practical experience in Kubernetes Administration, so we recommend participating in it even if you do not intend to take the CKA exam.

Format of the Course

• Interactive lecture and discussion.
• 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.
• To learn more about CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) program is developed by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), the host of Kubernetes.

This instructor-led, live training (online or onsite) is aimed at Developers who wish to confirm their skills in design, build, configure, and expose cloud native applications for Kubernetes.

On the other hand, training is also focused on gaining practical experience in Kubernetes application development, so we recommend taking part in it, even if you don't intend to take CKAD exam.

NobleProg have been delivering Docker & Kubernetes training from 2015. With more than 360 successfully completed training projects, we became one of the best known training company worldwide in field of containerization. Since 2019 we are also helping our customers to confirm their performance in k8s environment by preparing them and encouraging to pass CKA and CKAD exams.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.
• 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 creation, deployment, and execution of applications within containers.

This guided live training session (available online or in-person) targets engineers looking to transition from traditional standalone software deployments to managing software as containers using Docker.

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

• Install and configure Docker.
• Grasp and apply software containerization principles.
• Manage applications based on Docker.
• Network various Docker applications and systems.
• Understand and manipulate Docker registries.

Course Format

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

Customization Options

• To request a tailored training version of this course, please contact us for arrangements.
• For further information on 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 gain the skills necessary to operate modern container platforms and troubleshoot applications across development and production environments.

In this instructor-led live training in Turkey (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 containerization platform that enables the creation of reproducible, portable, and scalable environments for ML systems.

This live, instructor-led training—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 course, participants will be equipped to:

• Containerize ML training, validation, and inference workloads.
• Design and orchestrate end-to-end ML pipelines using 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 centered on constructing genuine ML pipeline components.
• Live lab sessions dedicated to end-to-end containerized workflows.

Customization Options

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

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

To achieve high-performance, scalable, and efficient deep learning operations, GPU acceleration is a critical requirement.

Designed for intermediate-level technical professionals, this live instructor-led training (available online or on-site) focuses on configuring, optimizing, and executing GPU-enabled AI workloads within Docker containers.

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

• Develop and execute GPU-enabled containers for both model training and inference tasks.
• Configure CUDA, drivers, and runtime libraries to support containerized AI workflows.
• Optimize resource allocation and isolation strategies specifically for GPU-intensive applications.
• Implement scalable, containerized deep learning services in production environments.

Course Delivery Format

• Interactive instruction enhanced with practical, real-world demonstrations.
• Exercise-driven practical sessions centered on GPU-enabled development.
• Live implementation activities conducted in a hands-on lab environment.

Customization Options

• For training tailored to your specific infrastructure or GPU stack, please reach out to us for custom arrangements.

In this instructor-led, live training at Turkey (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 proceeds 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 Turkey, participants will acquire the foundational skills needed to build microservices using Spring Cloud and Docker. Knowledge is assessed through practical exercises and the step-by-step creation of sample microservices.

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

• Comprehend the fundamental principles of microservices.
• Use Docker to construct 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.
• Apply Docker Compose for end-to-end integration testing.

This live, instructor-led training in Turkey (online or onsite) is designed for intermediate developers and DevOps engineers who aim 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.