GPU-Accelerated AI & Deep Learning with Docker Containers Training Course

This instructor-led live training in India (online or onsite) is aimed at engineers who wish to advance their knowledge of Docker 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 tools integration processes.
• Secure their Docker applications.

Docker serves as a containerization platform that allows for the creation of consistent, portable, and reproducible environments specifically suited for AI and machine learning workloads.

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

Upon successful completion of this course, participants will gain the ability to:

• Create and manage Docker images specifically customized for AI and ML applications.
• Containerize machine learning pipelines, tools, and associated dependencies.
• Optimize Docker environments to enhance both performance and portability.
• Deploy containerized ML services across a variety of runtime environments.

Course Format

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

Options for Course Customization

• For organizations seeking to tailor this training to their specific environment, please reach out to us to make arrangements.

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

This instructor-led live training, available both online and onsite, is designed for intermediate-level professionals aiming to automate end-to-end AI model delivery workflows leveraging Docker and CI/CD platforms.

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

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

Course Format

• 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

• Should your organization require tailored pipeline workflows or specific platform integrations, please reach out to us to customize this course.

The Certified Kubernetes Administrator (CKA) certification is jointly offered by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as a prominent platform for orchestrating containers.

NobleProg has been delivering Docker and Kubernetes training since 2015. Having successfully completed over 360 training projects, we have established ourselves as one of the globally recognized training providers in the field of containerization.

Since 2019, we have assisted our clients in validating their proficiency in Kubernetes (k8s) environments by preparing and encouraging them to take the CKA and CKAD examinations.

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 recommend participation 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 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 the CKA certification, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) certification program is jointly offered by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

This instructor-led, live training session (available online or onsite) is designed for developers who wish to validate their proficiency in designing, building, configuring, and exposing cloud-native applications on Kubernetes.

Additionally, the training emphasizes gaining practical experience in Kubernetes application development. Therefore, we recommend participating 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 established ourselves as one of the most recognized 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 sessions.
• 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 CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

Docker serves as a comprehensive platform for developers and system administrators to manage distributed applications. It features a runtime environment for executing containers alongside a service designed for sharing them.

Using Docker, the same application can operate seamlessly without modification across laptops, dedicated servers, and virtual servers.

This course covers the fundamental aspects of Docker during the first two days, providing valuable knowledge for both developers and system administrators. The curriculum includes numerous hands-on exercises where participants will work within their own Docker environments and construct their own Docker images.

On the final day, participants will explore advanced tools that complement Docker, specifically Docker Machine, Docker Compose, and Docker Swarm.

This live training, led by an instructor in India (available online or onsite), is intended for engineers looking to adopt Docker for deploying and managing software as containers, moving away from traditional standalone models.

By the conclusion 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.
• Understand and edit Docker registries.

This live, instructor-led training India (online or onsite) is tailored for DevOps engineers looking to optimize and simplify the CI/CD process using Docker and Jenkins.

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

• Automate code delivery and pipeline deployment with Jenkins.
• Build applications using Docker and Dockerfiles.
• Configure authentication options to strengthen security.

This instructor-led, live training in (online or onsite) is aimed at engineers who wish to evaluate each of these services to make an informed decisions about which to deploy within their organization.

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

• Set up a development environment that includes all needed libraries, packages and frameworks needed to start developing.
• Set up, configure and deploy a series of demo containers using a number of different approaches.
• Understand the architectural and design differences among different Docker/Kubernetes solutions within AWS.
• Automate the deployment of Docker containers.
• Set up a continuous integration and deployment pipeline.
• Integrate Docker and Kubernetes into an existing continuous integration system.

In this instructor-led, live training in India, participants will learn how to manage Red Hat OpenShift Container Platform.

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

• Create, configure, manage, and troubleshoot OpenShift clusters.
• Deploy containerized applications on-premise, in public cloud or on a hosted cloud.
• Secure OpenShift Container Platform
• Monitor and gather metrics.
• Manage storage.

In this instructor-led live training conducted in India (onsite or remote), participants will learn to create and manage Docker containers and deploy a sample application within a container. Additionally, participants will learn how to automate, scale, and manage their containerized applications within a Kubernetes cluster. The training concludes with advanced topics, guiding participants through 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 instructor-led live training, available both online and onsite, targets intermediate to advanced technical professionals who aim to containerize and operationalize comprehensive ML pipelines using Docker.

After completing this training, participants will be equipped to:

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

Format of the Course

• Interactive lectures accompanied by practical demonstrations.
• Hands-on exercises centered on constructing real-world ML pipeline components.
• Live-lab implementation for end-to-end containerized workflows.

Course Customization Options

• For customized training tailored to specific ML infrastructure requirements, please contact us to discuss available options.

Course Structure

• Interactive lectures paired with guided discussions.
• Ample opportunities for exercises and practical application.
• Real-world implementation exercises conducted in a live lab environment.

Options for Customization

• For those seeking a tailored training experience, please reach out to us to discuss your specific requirements.

This hands-on course is designed to equip participants with the essential practical skills and tools required for effectively managing Docker and Kubernetes environments. By the end of the program, learners will have the competence to administer these platforms confidently and efficiently.

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