Docker for MLOps: End-to-End Pipeline Containerization Training Course

This instructor-led, live training session, available via US (online or onsite), is designed for engineering professionals seeking to expand their expertise in Docker. The program focuses on deploying applications at scale while ensuring strict operational control.

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

• Create custom Docker images.
• Deploy and manage a high volume of Docker-based applications.
• Assess various container orchestration platforms and select the optimal solution for their environment.
• Establish continuous integration workflows specifically for Docker deployments.
• Integrate Docker solutions with existing continuous integration frameworks, providing robust tools for government agencies.
• Implement security best practices to protect Docker applications.

Upon completion of this instructional module, participants will demonstrate proficiency in the following areas:

• Construct custom Docker container images.
• Deploy and manage high volumes of Docker-based applications.
• Assess various container orchestration platforms to select the most appropriate solution for organizational needs.
• Establish continuous integration workflows tailored for Docker environments.
• Integrate Docker applications with existing CI/CD toolchains.
• Implement security best practices for Docker workloads.
• Utilize Kubernetes to deploy and manage diverse environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters effectively.

This instructor-led, live training US (online or onsite) is designed for advanced-level AI engineers and data scientists with intermediate-to-advanced experience who wish to enhance DeepSeek model performance, minimize latency, and deploy AI solutions efficiently using modern MLOps practices. This program provides essential capabilities for government agencies seeking robust artificial intelligence frameworks.

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

• Optimize DeepSeek models for efficiency, accuracy, and scalability.
• Implement best practices for MLOps and model versioning.
• Deploy DeepSeek models on cloud and on-premise infrastructure.
• Monitor, maintain, and scale AI solutions effectively.

Docker serves as a containerization framework that facilitates the creation of consistent, portable, and reproducible environments for artificial intelligence and machine learning applications.

This instructor-led training session, available online or at a designated location, is designed for intermediate-level practitioners seeking to package ML codebases, dependencies, and models using Docker to ensure reliable transitions from development to production within government operations.

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

• Constructing and managing Docker images specifically optimized for AI and ML initiatives.
• Containerizing machine learning pipelines, tools, and associated dependencies.
• Enhancing Docker environments to improve performance and portability for government use cases.
• Deploying containerized ML services across diverse runtime environments.

Course Delivery Format

• Conceptual demonstrations accompanied by guided analysis.
• Practical exercises targeting real-world containerization requirements.
• Implementation strategies utilizing live-lab Docker environments.

Customization for Government Entities

• To tailor this training to your specific organizational needs, please contact us to arrange a schedule that fits government workflows.

Continuous Integration and Continuous Delivery for artificial intelligence represents a systematic methodology for automating the packaging, validation, containerization, and deployment of models through established CI/CD pipelines.

This instructor-led program, available in online or onsite formats, targets intermediate professionals seeking to automate end-to-end AI model delivery processes utilizing Docker and CI/CD platforms.

Upon completion of this training, participants will demonstrate the ability to:

• Develop automated pipelines for the construction and testing of AI model containers.
• Establish version control mechanisms to ensure reproducibility throughout the model lifecycle.
• Incorporate automated deployment strategies for artificial intelligence services.
• Apply CI/CD best practices specifically adapted for machine learning operations.

Course Format

• Instructor-guided presentations and technical discussions.
• Practical laboratories and hands-on implementation exercises.
• Realistic CI/CD workflow simulations conducted in a controlled environment.

Customization Options

• For government entities requiring customized pipeline workflows or specific platform integrations, please contact us to tailor this course.

The Certified Kubernetes Administrator (CKA) credential is administered by The Linux Foundation in partnership with the Cloud Native Computing Foundation (CNCF).

Kubernetes has established itself as a premier platform for container orchestration.

NobleProg has provided Docker and Kubernetes instruction since 2015. Having successfully completed over 360 training initiatives, the organization is recognized globally as a leading provider of expertise in containerization solutions for government and public sector workflows.

Since 2019, we have assisted clients in validating their Kubernetes proficiency by preparing them for the CKA and CKAD certification examinations.

This instructor-led live training, available either online or onsite, is designed for system administrators and Kubernetes practitioners seeking to validate their expertise through the CKA examination process.

Additionally, the curriculum emphasizes practical administrative skills; therefore, participation is recommended even for those who do not plan to pursue official certification.

Course Format

• Interactive lectures and facilitated discussions.
• Extensive exercises and practice opportunities.
• Hands-on implementation within a live laboratory environment.

Customization Options

• To request customized training for this course, please contact us to arrange.
• For more information regarding CKA certification, visit: https://training.linuxfoundation.org/certification/certified-kubernetes-administrator-cka

The Certified Kubernetes Application Developer (CKAD) curriculum was established by The Linux Foundation and the Cloud Native Computing Foundation (CNCF), which hosts Kubernetes.

This instructor-led live training, available online or on-site, is designed for Developers seeking to validate their proficiency in designing, building, configuring, and exposing cloud native applications within Kubernetes environments.

Furthermore, the program emphasizes practical application development skills; participation is recommended for professional development, regardless of an intent to sit for the CKAD examination.

NobleProg has provided Docker and Kubernetes training since 2015. With over 360 successfully completed projects, the organization has become a leading provider globally in containerization education. Since 2019, we have assisted clients in demonstrating their capabilities within k8s environments by preparing them to pass the CKA and CKAD exams.

Course Format

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

Customization Options

• To arrange customized training for this course, please contact our team.
• For additional information regarding CKAD, please visit: https://training.linuxfoundation.org/certification/certified-kubernetes-application-developer-ckad/

This professional development resource is designed for government agencies and contractors seeking to enhance their technical capabilities.

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

This instructor-led live training, available online or on-site, is intended for engineering personnel seeking to utilize Docker for deploying and managing software as containers rather than relying on conventional standalone architectures. The program supports federal workforce development for government entities and their contractors.

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

• Install and configure the Docker platform.
• Comprehend and apply software containerization principles.
• Administer applications built on Docker technology.
• Establish network connectivity among Dockerized applications and systems.
• Navigate and modify Docker registries.

Course Structure

• Incorporates interactive lectures and policy-aligned discussions.
• Features extensive exercises and practical application.
• Provides hands-on implementation within a secure live-lab environment.

Customization Availability

• To request a tailored training module for this course, please contact the administration to arrange logistics.
• For additional information regarding Docker capabilities, visit: https://www.docker.com

This comprehensive five-day instructional program provides federal personnel with the necessary expertise to construct, implement, and manage containerized infrastructure utilizing Docker, Kubernetes, and OpenShift technologies. The curriculum delivers rigorous, practical instruction on critical domains including container image management, Kubernetes workload orchestration, cluster networking configurations, persistent storage solutions, security protocols, monitoring frameworks, and operational administration of OpenShift environments. By completing this training for government professionals, attendees will acquire the competencies required to sustain contemporary container platforms and effectively diagnose application issues within both development and production workflows.

During this instructor-led live training conducted in US (either onsite or remotely), attendees will acquire the skills necessary to create and administer Docker containers and subsequently deploy a sample application within such an environment. The curriculum also covers the automation, scaling, and management of containerized workloads within a Kubernetes cluster. Furthermore, the instruction addresses advanced subjects, guiding participants through the procedures for securing, expanding capacity, and monitoring Kubernetes infrastructure. This comprehensive approach ensures that personnel are equipped with the technical expertise required for effective government operations and is designed specifically for government use cases.

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

• Configure and operate Docker containers.
• Deploy containerized servers and web-based applications.
• Construct and oversee Docker images.
• Establish a combined Docker and Kubernetes cluster environment.
• Utilize Kubernetes to deploy and manage clustered web applications.
• Implement security measures, scaling protocols, and monitoring systems for a Kubernetes cluster.

Kubeflow serves as an open-source framework intended to optimize the construction, execution, and deployment of machine learning operations within Kubernetes environments.

This facilitated live instruction, available via remote or on-location delivery, targets professionals with introductory to intermediate expertise who seek to establish dependable machine learning pipelines utilizing Kubeflow tools.

Upon concluding this program, participants will acquire the capability to:

• Traverse the Kubeflow environment and its fundamental elements.
• Develop consistent workflows using Kubeflow Pipelines.
• Execute scalable training tasks on Kubernetes infrastructure.
• Deploy machine learning models efficiently through Kubeflow Serving.

Course Format

• Structured presentations combined with collaborative dialogue.
• Practical laboratory sessions utilizing active Kubeflow components.
• Applied exercises for constructing complete machine learning workflows.

Customization Options

• Tailored iterations of this training are available to ensure alignment with an organization’s specific technology infrastructure and operational mandates, particularly for government entities requiring specialized compliance or integration standards.

This instructor-led, live training in US (delivered online or onsite) is designed for developers and data scientists aiming to build, deploy, and manage machine learning workflows on Kubernetes.

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

• Install and configure Kubeflow on-premises and in the cloud.
• Build, deploy, and manage ML workflows based on Docker containers and Kubernetes.
• Run entire machine learning pipelines on diverse architectures and cloud environments.
• Using Kubeflow to spawn and manage Jupyter notebooks.
• Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This instructor-led, live training in US (online or onsite) is designed for engineers who need to assess current methodologies and tools to make informed decisions regarding the adoption of MLOps practices within their agencies.

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

• Install and configure essential MLOps frameworks and utilities for government use cases.
• Assemble skilled teams capable of constructing and sustaining an effective MLOps infrastructure.
• Prepare, validate, and version data sets to ensure compatibility with machine learning models.
• Comprehend the essential components of an ML pipeline and identify the necessary tools for implementation.
• Evaluate various machine learning frameworks and servers suitable for production deployment in secure environments.
• Operationalize the end-to-end machine learning lifecycle to ensure reproducibility, maintainability, and accountability for government operations.

MLOps on Kubernetes provides a structured framework for automating the training, validation, packaging, and deployment of machine learning models through containerized pipelines and GitOps methodologies. This approach supports efficient operational workflows for government data science initiatives.

This instructor-led, live training (available online or onsite) is designed for intermediate-level practitioners seeking to establish automated and scalable MLOps pipelines on Kubernetes infrastructure. The curriculum addresses specific requirements for government systems.

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

• Architect end-to-end continuous integration and delivery (CI/CD) pipelines for machine learning applications.
• Implement GitOps workflows to manage model deployment and version control.
• Automate the training, testing, and packaging processes for ML models.
• Integrate comprehensive monitoring, alerting mechanisms, and rollback strategies.

Format of the Course

• Instructor-guided presentations and technical deep dives.
• Hands-on exercises that build real-world CI/CD workflows.
• Live-lab practice deploying ML workloads to Kubernetes.

Course Customization Options

• Organizations may request tailored content aligned with their internal MLOps tools and infrastructure.