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

Upon completion, participants will have the skills to:

• Construct custom Docker images.
• Deploy and oversee high volumes of Docker applications.
• Assess various container orchestration tools and select the optimal solution.
• Establish continuous integration workflows for Docker-based applications.
• Connect Docker applications to existing continuous integration pipelines.
• Implement robust security measures for Docker applications.
• Leverage Kubernetes to manage multiple environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters effectively.

This instructor-led live training, offered in Denmark (online or on-site), is tailored for advanced AI engineers and data scientists with intermediate-to-advanced experience who seek to enhance DeepSeek model performance, minimise latency, and deploy AI solutions efficiently using modern MLOps practices.

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

• Optimise DeepSeek models for improved efficiency, accuracy, and scalability.
• Apply best practices for MLOps and model versioning.
• Deploy DeepSeek models on cloud and on-premise infrastructure.
• Monitor, maintain, and scale AI solutions with confidence.

This live, instructor-led course offered in Denmark (either online or on-site) is designed for advanced platform engineers and DevOps practitioners seeking to excel in application scaling via microservices and Kubernetes.

By the end of this engagement, participants will be capable of:

• Architecting and constructing scalable microservice systems.
• Managing and operating applications on Kubernetes clusters.
• Employing Helm charts to facilitate streamlined service rollouts.
• Maintaining and monitoring the operational stability of microservices in production.
• Enforcing security and compliance standards within a Kubernetes environment.

This instructor-led, live training programme, delivered in Denmark (online or on-site), is designed for Kubernetes practitioners seeking to prepare for the CKS exam.

By the end of this training, participants will understand how to secure Kubernetes environments and container-based applications throughout the various stages of an application's life cycle: build, deployment, and runtime.

This instructor-led live training, delivered in Denmark (either online or on-site), is crafted for engineers seeking to utilize Helm to optimize the installation and administration of Kubernetes applications.

By the end of the session, attendees will be equipped to:

• Set up and configure Helm.
• Build reproducible versions of Kubernetes applications.
• Distribute applications through Helm charts.
• Execute third-party applications available as Helm charts.
• Handle the release cycle of Helm packages.

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

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

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

This instructor-led, live training in Denmark (delivered online or onsite) is designed for beginner to intermediate-level software developers and DevOps professionals seeking to learn how to configure and manage a local Kubernetes environment using Minikube.

By the end of the session, participants will be able to:

• Install and configure Minikube on their local machines.
• Comprehend the core concepts and architecture of Kubernetes.
• Manage container deployment using kubectl and the Minikube dashboard.
• Establish persistent storage and networking configurations for Kubernetes.
• Apply Minikube to application development, testing, and debugging workflows.

This live, instructor-led training in Denmark (online or onsite) targets intermediate developers and DevOps engineers seeking to adopt Minikube in their development routines.

Upon completion, attendees will be equipped to:

• Establish and oversee a local Kubernetes environment through Minikube.
• Master the processes for deploying, overseeing, and troubleshooting applications within Minikube.
• Embed Minikube into existing continuous integration and deployment pipelines.
• Streamline development cycles by leveraging Minikube’s advanced capabilities.
• Implement industry-standard best practices for local Kubernetes development.

This instructor-led, live training in Denmark (online or onsite) is designed for engineers looking to evaluate current approaches and tools. It empowers participants to make intelligent decisions about 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 production deployment.
• Operationalize the entire Machine Learning process so that it is reproducible and maintainable.