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

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

• Create custom Docker images.
• Deploy and manage a high volume of Docker applications.
• Assess various container orchestration solutions and select the most appropriate option.
• Establish a continuous integration pipeline for Docker applications.
• Integrate Docker applications with existing continuous integration workflows.
• Enhance the security of Docker applications.
• Leverage Kubernetes to deploy and manage multiple environments within a single cluster.
• Secure, scale, and monitor Kubernetes clusters.

This instructor-led, live training in Serbia (online or onsite) targets advanced-level AI engineers and data scientists with intermediate-to-advanced experience who aim to enhance DeepSeek model performance, reduce latency, and deploy AI solutions efficiently using modern MLOps practices.

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

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

This instructor-led, live training in Serbia (online or onsite) is designed for advanced-level platform engineers and DevOps professionals who want to master application scaling 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.
• Use 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 instructor-led live training in Serbia (delivered online or onsite) is tailored for Kubernetes professionals looking to prepare for the CKS exam.

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

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

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

• Install and configure Helm.
• Build reproducible Kubernetes application deployments.
• Distribute applications as Helm charts.
• Execute third-party applications packaged as Helm charts.
• Manage releases of Helm packages.

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

By the end of the session, participants will be capable of:

• Installing and configuring Kubeflow in both on-premise and cloud environments.
• Creating, deploying, and managing ML workflows using Docker containers and Kubernetes.
• Running full machine learning pipelines across diverse architectures and cloud environments.
• Utilizing Kubeflow to start and control Jupyter notebooks.
• Building ML training, hyperparameter tuning, and serving workloads across multiple platforms.

This instructor-led, live training in Serbia (online or onsite) targets beginner to intermediate software developers and DevOps professionals who want 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.
• Grasp the fundamental concepts and architecture of Kubernetes.
• Deploy and manage containers using kubectl and the Minikube dashboard.
• Configure persistent storage and networking solutions for Kubernetes.
• Leverage Minikube for application development, testing, and debugging.

This instructor-led, live training in Serbia (online or onsite) is designed for intermediate-level developers and DevOps engineers who aim to use Minikube as 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 Serbia (online or onsite) is aimed at 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.