MLOps on Kubernetes: CI/CD Pipelines for Machine Learning Training Course

This instructor-led, live training in Norway (online or onsite) is aimed at 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.

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.

This instructor-led, live training in Norway (online or onsite) is designed for advanced-level platform engineers and DevOps professionals who want to master application scaling using microservices and Kubernetes.

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

• Design and implement scalable microservices architectures.
• Deploy and manage applications on Kubernetes clusters.
• Utilize Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance in a Kubernetes environment.

This live, instructor-led training in Norway—delivered online or onsite—is designed for Kubernetes practitioners seeking to prepare for the CKS exam.

By the end of the program, participants will understand how to secure Kubernetes environments and container-based applications throughout the application life cycle, covering build, deployment, and runtime phases.

This 7-day programme provides a comprehensive, hands-on journey into designing, deploying, and operating cloud-native applications using modern DevOps practices.

Participants will explore how to design scalable microservices architectures, optimise container environments, and manage production workloads using Kubernetes. The course covers advanced deployment strategies, GitOps-based automation, and observability practices to ensure system reliability and performance.

A strong focus is placed on real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme concludes with the use of AI-powered tools to support troubleshooting and accelerate operational decision-making.

By the end of the training, participants will have a clear understanding of how to build, deploy, monitor, and maintain resilient distributed systems in a Kubernetes-based environment.

This instructor-led, live training in Norway (online or onsite) is designed for engineers who want to leverage Helm to simplify the installation and management of Kubernetes applications.

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

• Install and configure Helm.
• Generate reproducible builds of Kubernetes applications.
• Distribute applications using Helm charts.
• Execute third-party applications packaged as Helm charts.
• Manage releases of Helm packages.

This live, instructor-led training in Norway, offered either online or onsite, is designed for developers and data scientists looking to build, deploy, and manage machine learning workflows on Kubernetes.

By the end of this session, participants will have the ability to:

• Install and configure Kubeflow in both on-premise and cloud settings.
• Construct, deploy, and manage ML workflows using Docker containers and Kubernetes.
• Run entire machine learning pipelines across diverse architectures and cloud environments.
• Use Kubeflow to spawn and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This instructor-led live training in Norway (online or onsite) targets beginner to intermediate software developers and DevOps professionals who wish to learn how to establish and manage a local Kubernetes environment using Minikube.

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

• Installing and configuring Minikube on their local workstation.
• Gaining a solid understanding of Kubernetes' core concepts and architecture.
• Deploying and managing containers via kubectl and the Minikube dashboard.
• Implementing persistent storage and networking solutions for Kubernetes.
• Leveraging Minikube for application development, testing, and debugging.

This instructor-led, live training in Norway (online or onsite) is aimed at intermediate-level developers and DevOps engineers who wish to use Minikube as a part of their development workflow.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Understand how to deploy, manage, and debug applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Optimize their development process using Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led live training in Norway (online or onsite) targets engineers who wish to evaluate the approaches and tools available today to make an intelligent decision on the path forward in adopting MLOps within their organization.

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

• Install and configure various MLOps frameworks and tools.
• Assemble the right kind of team with the right skills for constructing and supporting an MLOps system.
• Prepare, validate and version data for use by ML models.
• Understand the components of an ML Pipeline and the tools needed to build one.
• Experiment with different machine learning frameworks and servers for deploying to production.
• Operationalize the entire Machine Learning process so that it's reproduceable and maintainable.