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Charlotte, NC – City Center

525 North Tryon Street, Suite 1600, Charlotte, United States, 28202

The venue is located in Uptown Charlotte’s City Center district at 525 North Tryon Street, easily reachable by car via I‑77, I‑85, or I‑277, with access to adjacent parking garages connected via pedestrian skywalks. From Charlotte Douglas International Airport (CLT), roughly 10 miles southwest, a taxi or rideshare takes approximately 15–20 minutes via I‑485, I‑77 North, then Trade Street. Public transit is convenient: the Lynx Blue Line light rail stops at 9th Street station two blocks away, and multiple CATS bus routes travel along Tryon and Trade streets—making it accessible for participants without cars.

Cary, NC – Regus at Regency Parkway

2500 Regency Pkwy, Cary, United States, 27518

The venue sits within the Regency Park campus at 2500 Regency Parkway, conveniently accessible by car via US 1/US 64 and I‑40, with free on-site parking and adjacent lots. From Raleigh–Durham International Airport (RDU), about 15 miles northwest, taxis or rideshares typically take 20–25 minutes via US 64 East. Public transit users can use GoCary and GoRaleigh bus routes; Cary Station is about 0.8 miles away, offering access via regional transport followed by a short walk or quick rideshare to the building.

Chapel Hill, NC – Regus at Environ Way

1340 Environ Way, Chapel Hill, United States, 27517

The venue is situated on Environ Way in Chapel Hill’s sustainably designed office park, easily reached by car via US‑15‑501 and NC‑54, with ample on-site and municipal lot parking. From Raleigh–Durham International Airport (RDU), approximately 12 miles northwest, taxis or rideshares typically take 20–25 minutes via I‑40 East and US‑15‑501 South. Public transit is convenient: Chapel Hill Transit buses stop nearby on East Franklin Street, and UNC’s campus is a short walk away—making the location ideal for attendees without cars.

Durham, NC – Regus at Shannon Road

3511 Shannon Road, 3rd Floor, Durham, United States, 27707

The venue is situated in a suburban business park with easy car access via I‑40 and NC‑147, and offers ample on-site parking. From Raleigh-Durham International Airport (RDU), about 7 miles northwest, taxis or rideshares typically take 15–20 minutes via I‑40 East. Public transit options include GoDurham and GoTriangle bus routes that serve nearby Shannon and Cornwallis Roads, with a short walk to the building entrance.

Raleigh, NC – Regus at Raleigh City Plaza

421 Fayetteville Street, Plaza Downtown, Suite 1100, Raleigh, United States, 27601

The venue is located in downtown Raleigh within the One City Plaza tower on Fayetteville Street, easily accessible by car via I‑40 or I‑440, with several public parking garages within a block. From Raleigh‑Durham International Airport (RDU), approximately 17 miles west, taxis or rideshares typically take 20–25 minutes via I‑40 East. For attendees using public transit, GoRaleigh bus routes stop on Fayetteville and Salisbury Streets directly in front of One City Plaza, offering convenient walkable access to the building.

Explore Our Courses

CI/CD for AI: Automating Docker-Based Model Builds and Deployments

 21 Hours

Continuous Integration and Continuous Delivery (CI/CD) for AI represents a systematic methodology for automating model packaging, testing, containerization, and deployment via integrated pipelines.

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

Upon completion, participants will be equipped to:

  • Develop automated pipelines for constructing and testing AI model containers.
  • Enforce version control and reproducibility standards across model lifecycles.
  • Incorporate automated deployment strategies for AI services for government operations.
  • Apply CI/CD best practices aligned with machine learning operations requirements.

Course Delivery Format

  • Instructor-led presentations and technical discourse.
  • Practical laboratories and hands-on implementation exercises.
  • Simulations of realistic CI/CD workflows within a controlled environment.

Course Customization Opportunities

  • For organizations requiring bespoke pipeline workflows or platform integrations, contact us to tailor this course.
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Hybrid AI Deployment: Docker, Cloud, and Edge Integration

 21 Hours

Hybrid AI implementation involves executing AI inference across cloud, on-premise, and edge domains through standardized container-based procedures.

This instructor-led, live training module (available online or on-site) is designed for senior-level professionals seeking to architect and implement distributed AI inference systems across diverse environments.

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

  • Develop secure and scalable containerized AI services for multi-site environments.
  • Deploy AI inference workloads to cloud platforms, local servers, and edge devices using Docker.
  • Integrate coordination tools to automate distributed AI operations for government purposes.
  • Enhance inference speed, dependability, and system resilience across varied infrastructure.

Course Delivery Structure

  • Structured presentations and expert-facilitated dialogue.
  • Substantial hands-on practice and applied laboratory exercises.
  • Practical experimentation within a controlled, live laboratory environment.

Course Adaptation Options

  • To modify this course to align with specific organizational infrastructure or operational use cases, please contact us to customize the training for government requirements.
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Secure & Portable AI Inference with Docker: From Local to Cloud

 14 Hours

Docker is a containerization platform employed to establish portable, isolated, and secure deployment environments for AI inference services.

This live, instructor-led training, available online or onsite, is designed for technical professionals with beginner to intermediate proficiency who intend to develop secure, portable AI inference microservices that can be deployed consistently across local workstations, servers, or cloud virtual machines.

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

  • Construct lightweight inference containers suitable for local and cloud environments.
  • Apply best-practice security measures to containerized AI services.
  • Establish portable microservice workflows for environmental consistency.
  • Deploy AI inference endpoints across varied infrastructure architectures.

Instructional Format

  • Structured lectures accompanied by practical demonstrations.
  • Practical exercises to reinforce deployment and security protocols.
  • Interactive laboratory sessions for constructing and executing portable inference services.

Customization Options for Government

  • To adapt this training to specific infrastructure or AI tooling requirements, please contact the provider for coordination.
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Kubernetes from Basic to Advanced

 14 Hours

This instructor-led, live training is conducted in North Carolina (available onsite or remotely). The curriculum focuses on deploying sample server applications within containers, followed by the automation, scaling, and management of these workloads within a Kubernetes cluster. The course addresses advanced operational topics, guiding participants through the critical processes of securing, networking, and monitoring Kubernetes clusters.

Upon completion, participants will be capable of:

  • Initializing and operating Docker containers.
  • Deploying containerized databases and server applications.
  • Establishing and configuring Docker and Kubernetes clusters.
  • Utilizing Kubernetes to manage distinct operational environments within a unified cluster.
  • Implementing security measures, scaling protocols, and monitoring systems for Kubernetes clusters.
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GPU-Accelerated AI & Deep Learning with Docker Containers

 21 Hours

GPU acceleration is a critical component for executing high-performance deep learning workloads with scalable and efficient resource management.

This instructor-led, live training program (available online or on-site) is designed for intermediate-level technical professionals tasked with configuring, optimizing, and executing GPU-enabled AI workloads within Docker containers for government use.

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

  • Construct and execute GPU-enabled containers for both training and inference phases.
  • Configure CUDA, system drivers, and runtime libraries for containerized AI workflows.
  • Optimize resource allocation and enforce isolation protocols for GPU-intensive applications.
  • Deploy scalable, containerized deep learning services within production environments.

Course Delivery Format

  • Interactive instruction reinforced by practical, real-world demonstrations.
  • Exercise-based practice centered on GPU-enabled development standards.
  • Hands-on implementation conducted in a secure live-lab environment.

Course Customization Options

  • For tailored training aligned with specific infrastructure or GPU stack requirements, please contact us to arrange a schedule.
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Docker for MLOps: End-to-End Pipeline Containerization

 21 Hours

Docker serves as a containerization technology enabling the creation of consistent, portable, and scalable environments for machine learning systems in the public sector.

This instructor-led training session, available remotely or in person, targets intermediate to advanced technical staff seeking to containerize and operationalize full-scale machine learning pipelines for government use.

Upon successfully completing this course, participants will be equipped to:

  • Encapsulate machine learning training, validation, and inference tasks.
  • Design and manage comprehensive machine learning workflows using Docker and complementary tools.
  • Establish version control, reproducibility, and CI/CD practices for machine learning components.
  • Deploy, oversee, and scale machine learning services within containerized frameworks.

Course Format

  • Interactive instruction accompanied by practical application demonstrations.
  • Practical exercises centered on developing functional machine learning pipeline elements.
  • Live laboratory sessions for executing end-to-end containerized operations.

Customization Opportunities

  • To align training with specific government machine learning infrastructure requirements, please contact the provider for detailed options.
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Containerized AI & ML Deployment with Docker

 14 Hours
This instructor-led training in North Carolina provides intermediate professionals with the skills to containerize AI and ML workloads using Docker. Participants will acquire the knowledge to build optimized images, manage dependencies, and deploy reliable pipelines, developing hands-on competencies for consistent and portable production environments.
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Building Microservices with Spring Cloud and Docker - 5 Days

 35 Hours

This instructor-led, live training in North Carolina (online or onsite) is directed at intermediate-level developers and DevOps engineers seeking to build, deploy, and manage microservices using Spring Cloud and Docker.

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

  • Developing microservices using Spring Boot and Spring Cloud frameworks.
  • Containerizing applications with Docker and Docker Compose.
  • Implementing service discovery, API gateways, and inter-service communication mechanisms.
  • Monitoring and securing microservices in production environments.
  • Deploying and orchestrating microservices using Kubernetes.
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Docker and Kubernetes

 21 Hours

Training objectives: Develop theoretical knowledge and operational proficiency in Docker and Kubernetes technologies.

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Docker and Kubernetes: Building and Scaling a Containerized Application

 21 Hours

In this instructor-led training session held in North Carolina (onsite or remote), participants will acquire the technical proficiency to create and manage Docker containers, including the deployment of representative applications. The curriculum further instructs on the automation, scaling, and governance of containerized applications within a Kubernetes cluster. The training concludes with advanced topics, guiding participants through the rigorous processes of securing, scaling, and monitoring Kubernetes clusters to meet operational standards.

Upon completion of this training, participants will possess the following capabilities:

  • Initialization and execution of Docker containers.
  • Deployment of containerized server and web application stacks.
  • Construction and administration of Docker image repositories.
  • Configuration of Docker and Kubernetes cluster infrastructures.
  • Application of Kubernetes to deploy and oversee clustered web services.
  • Enforcement of security protocols, scaling adjustments, and continuous monitoring of Kubernetes clusters.
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Certified Kubernetes Administrator (CKA) - exam preparation

 21 Hours

The Certified Kubernetes Administrator (CKA) program is established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF).

Kubernetes has emerged as a predominant platform for container orchestration.

NobleProg has provided Docker and Kubernetes training since 2015. With over 360 successfully completed training engagements, the organization is recognized globally for its expertise in containerization.

Since 2019, NobleProg has supported clients in validating their technical proficiency within Kubernetes environments by facilitating preparation for the CKA and CKAD examinations.

This instructor-led, live training session (available online or onsite) is designed for System Administrators and Kubernetes practitioners who seek to validate their competencies through the CKA examination.

Furthermore, the curriculum emphasizes practical experience in Kubernetes administration; therefore, participation is recommended for individuals seeking to enhance operational capabilities, irrespective of their intent to pursue CKA certification for government initiatives.

Course Format

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

Course Customization Options

  • Requests for customized training programs for this course may be directed to NobleProg for scheduling.
  • Detailed information regarding CKA certification is available at: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka
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Container Platforms Administration with Docker, Kubernetes and OpenShift

 35 Hours

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 for government and troubleshoot applications across development and production environments.

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Certified Kubernetes Application Developer (CKAD) - exam preparation

 21 Hours
This instructor-led CKAD training in North Carolina prepares developers for the Certified Kubernetes Application Developer examination through practical laboratory exercises. It covers the design, development, and security of cloud-native applications for government use, utilizing core Kubernetes concepts, deployment strategies, and networking fundamentals.
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Managing Kubernetes with Rancher

 14 Hours

This instructor-led, live training course for government in North Carolina offers an overview of Rancher and demonstrates, through practical exercises, the deployment and management of a Kubernetes cluster.

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Docker and Kubernetes - Advanced Level

 35 Hours

The "Advanced Docker and Kubernetes" instruction offers a thorough analysis of the Kubernetes platform and its surrounding ecosystem. Tailored for participants with varied levels of technical proficiency, the curriculum covers a complete spectrum of fundamental and advanced features. The course addresses essential concepts including Pods, Labels, Controllers, Services, Secrets, Persistent Data Volumes, Claims, Namespaces, and Resource Quotas. It further examines the Container Networking Model, Service Discovery, Scaling mechanisms, and Load Balancing strategies. Additional topics include Cluster Management, Kubernetes installation procedures, security protocols for cluster protection, access control frameworks, High Availability of the Control Plane, monitoring and logging standards, automatic application scaling, advanced scheduling logic, microservices-based application architectures, specific application design patterns, and the deployment of applications and services on a Kubernetes cluster for government use.

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Advanced Docker

 14 Hours

This instructor-led, live training conducted in North Carolina (either online or on-site) is designed for engineers aiming to deepen their expertise in Docker to support the deployment of applications at scale while maintaining robust control.

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

  • Construct custom Docker images.
  • Deploy and manage large-scale Docker applications.
  • Evaluate diverse container orchestration solutions to determine the most suitable framework.
  • Implement continuous integration workflows for Docker applications.
  • Integrate Docker applications into existing continuous tool integration processes.
  • Enhance the security posture of Docker applications.
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Docker & Kubernetes Advanced

 21 Hours

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

  • Develop and customize proprietary Docker images.
  • Deploy and oversee a substantial volume of Dockerized applications.
  • Assess various container orchestration platforms and select the optimal solution for specific requirements.
  • Establish continuous integration pipelines tailored for Docker applications.
  • Integrate Docker workflows with existing continuous integration toolchains.
  • Implement robust security measures for Docker-based applications.
  • Leverage Kubernetes to manage diverse environments within a unified cluster.
  • Ensure the security, scalability, and observability of Kubernetes clusters.
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Introduction to Docker

 14 Hours

Docker is an open-source platform designed to automate the construction, distribution, and execution of applications within containerized environments.

This instructor-led, live training (conducted online or on-site) is intended for engineers seeking to utilize Docker for the deployment and administration of software as containers, replacing traditional standalone software models for government use.

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

  • Installation and configuration of Docker environments.
  • Implementation of software containerization strategies.
  • Management of Docker-based applications.
  • Networking of Docker applications and system components.
  • Interpretation and modification of Docker registries.

Training Delivery Format

  • Interactive instruction and facilitated discussion.
  • Extensive exercises and practical application.
  • Hands-on implementation within a live laboratory environment.

Customization Options for Training

  • To request a customized training curriculum for this course, please contact the relevant office for coordination.
  • To access additional information regarding Docker, please visit: https://www.docker.com
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Building Microservices with Spring Cloud and Docker

 21 Hours

In this instructor-led, live training session conducted in North Carolina, participants will acquire the essential skills for constructing microservices utilizing Spring Cloud and Docker. Learning outcomes are validated through rigorous exercises and the systematic development of sample microservice components.

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

  • Analyzing the core principles of microservice architecture.
  • Employing Docker to engineer containerized environments for microservice applications.
  • Implementing and deploying containerized microservices using Spring Cloud and Docker frameworks.
  • Establishing integration between microservices, discovery services, and the Spring Cloud API Gateway.
  • Conducting comprehensive end-to-end integration testing via Docker Compose.
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OpenShift Administration Fundamentals

 35 Hours

OpenShift is a prominent Kubernetes-based platform for the deployment and management of containerized applications within cloud, hybrid, and on-premises environments.

This practical training provides participants with the skills to install, administer, and troubleshoot OpenShift clusters while adhering to security, networking, and storage standards. Through applied exercises, participants acquire the capabilities necessary to confidently manage production-grade OpenShift environments for government.

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Testimonials (4)

As i said before , for a person like me (no exp. ) this was a gateway to understanding features and functions with these programs/tools & etc. .

Patrick V. Duylovski - UBB + DZI (KBC GROUP)

Course - Docker and Kubernetes

multi-tiered, structured course programme.

Bert Paelinckx - Cube SoftwareSolutions

Course - Introduction to Docker

The training met expectations with its clear explanations, real-world examples, and hands-on labs that made complex topics easy to understand. It provided valuable insights into container orchestration, security, scaling and many other advanced topics.

Anna Wyszomirska-Szmyd - Akamai

Course - Docker and Kubernetes advanced

How trainer deliver knowledge so effectively

Vu Thoai Le - Reply Polska sp. z o. o.

Course - Certified Kubernetes Administrator (CKA) - exam preparation

Upcoming Courses

Docker and Kubernetes: Building and Scaling a Containerized Application

2026-11-11 09:30
21 hours
Chapel Hill, NC – Regus at Environ Way
$ 3330 (Online)
$ 5130 (Classroom)

Building Microservices with Spring Cloud and Docker

2026-11-25 09:30
21 hours
Cary, NC – Regus at Regency Parkway
$ 3330 (Online)
$ 5130 (Classroom)

Kubernetes from Basic to Advanced

2026-12-09 09:30
14 hours
Chapel Hill, NC – Regus at Environ Way
$ 2220 (Online)
$ 3420 (Classroom)

Building Microservices with Spring Cloud and Docker

2026-12-23 09:30
21 hours
Cary, NC – Regus at Regency Parkway
$ 3330 (Online)
$ 5130 (Classroom)

Advanced Docker

2027-01-06 09:30
14 hours
Chapel Hill, NC – Regus at Environ Way
$ 2220 (Online)
$ 3420 (Classroom)

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These courses are also available in other countries

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