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

This instructor-led, live training in Sweden (online or onsite) targets advanced-level AI engineers and data scientists with intermediate-to-advanced expertise who seek to improve DeepSeek model performance, reduce latency, and efficiently deploy AI solutions using contemporary MLOps practices.

Upon completing 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 across cloud and on-premise infrastructure.
• Monitor, maintain, and scale AI solutions effectively.

This instructor-led, live training in Sweden (online or onsite) is aimed at advanced-level platform engineers and DevOps professionals who wish to master scaling applications using microservices and Kubernetes.

By the end 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 Sweden, offered either online or onsite, is designed for Kubernetes practitioners aiming to prepare for the CKS exam.

Upon completing this program, participants will be equipped to secure Kubernetes environments and container-based applications across the entire 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 Sweden (online or onsite) is aimed at engineers who wish to use Helm to streamline the process of installing and managing Kubernetes applications.

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

• Install and configure Helm.
• Create reproducible builds of Kubernetes applications.
• Share applications as Helm charts.
• Run third-party applications saved as Helm charts.
• Manage releases of Helm packages.

This instructor-led, live training in Sweden (delivered online or on-site) targets developers and data scientists aiming to build, deploy, and administer machine learning workflows on Kubernetes.

By the conclusion of this training, participants will possess the capability to:

• Install and configure Kubeflow in on-premise and cloud environments.
• Construct, deploy, and manage ML workflows leveraging Docker containers and Kubernetes.
• Execute complete machine learning pipelines across varied architectures and cloud settings.
• Leverage Kubeflow to create and manage Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This guided, live training in Sweden (online or onsite) is tailored for software developers and DevOps practitioners at beginner to intermediate levels who want to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local workstation.
• Grasp the fundamental concepts and architectural structure of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Configure persistent storage and networking solutions for Kubernetes.
• Leverage Minikube to develop, test, and debug applications effectively.

This instructor-led, live training in Sweden (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 Sweden (online or onsite) is designed for engineers who wish to evaluate current approaches and tools, allowing them to make informed decisions about adopting MLOps within their organization.

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

• Install and configure various MLOps frameworks and tools.
• Assemble a team with the appropriate skills to build and support an MLOps system.
• Prepare, validate, and version data for use by ML models.
• Understand the components of an ML Pipeline and identify the tools required to construct one.
• Experiment with different machine learning frameworks and servers for production deployment.
• Operationalize the entire Machine Learning process to ensure it is reproducible and maintainable.