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

This instructor-led, live training in Slovakia (online or on-site) 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 Slovakia (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.
• Use Helm charts for efficient service deployment.
• Monitor and maintain the health of microservices in production.
• Apply best practices for security and compliance within a Kubernetes environment.

This live, instructor-led training session in Slovakia, available online or onsite, is designed for Kubernetes practitioners seeking to prepare for the CKS examination.

Upon completion, participants will be equipped to secure Kubernetes environments and container-based applications throughout the different phases of the application life cycle, specifically during build, deployment, and runtime.

This intensive 7-day programme offers a comprehensive, hands-on exploration into the design, deployment, and operation of cloud-native applications through modern DevOps methodologies.

Participants will learn to architect scalable microservices environments, optimize container ecosystems, and manage production-grade workloads using Kubernetes. The curriculum encompasses advanced deployment tactics, GitOps-driven automation, and robust observability frameworks designed to guarantee system reliability and peak performance.

A significant emphasis is placed on addressing real-world operational complexities, such as incident management, failure simulation drills, and root cause analysis. The programme finishes by integrating AI-powered tools to enhance troubleshooting capabilities and streamline operational decision-making processes.

Upon completion of the training, participants will possess a thorough understanding of how to build, deploy, monitor, and sustain resilient distributed systems within a Kubernetes infrastructure.

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

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

• Install and configure Helm.
• Develop reproducible builds for Kubernetes applications.
• Distribute applications as Helm charts.
• Deploy third-party applications stored as Helm charts.
• Manage Helm package releases.

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

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

• Install and configure Kubeflow in both on-premise and cloud environments.
• Construct, deploy, and manage ML workflows built on Docker containers and Kubernetes.
• Operate full machine learning pipelines across diverse architectures and cloud platforms.
• Utilize Kubeflow to launch and control Jupyter notebooks.
• Build ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This instructor-led, live training in Slovakia (online or onsite) is designed for beginner to intermediate software developers and DevOps professionals who wish to learn how to set up and manage a local Kubernetes environment using Minikube.

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

• Install and configure Minikube on their local machine.
• Understand the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Set up persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for developing, testing, and debugging applications.

This instructor-led, live training in Slovakia (online or onsite) is designed for intermediate developers and DevOps engineers aiming to utilize Minikube within their development workflows.

By the conclusion 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 Slovakia (online or onsite) targets engineers who wish to evaluate current approaches and tools. This evaluation supports intelligent decision-making regarding the adoption of MLOps within their organization.

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

• Install and configure various MLOps frameworks and tools.
• Assemble a team with the appropriate 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 is reproducible and maintainable.