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

This instructor-led, live training in Botswana (online or onsite) targets advanced AI engineers and data scientists with intermediate to advanced proficiency who aim to improve DeepSeek model performance, reduce latency, and implement AI solutions efficiently through contemporary MLOps practices.

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

• Optimize DeepSeek models for enhanced efficiency, accuracy, and scalability.
• Apply best practices for MLOps and model versioning.
• Deploy DeepSeek models across cloud and on-premise infrastructures.
• Monitor, maintain, and scale AI solutions effectively.

This instructor-led, live training in Botswana (online or onsite) is designed for advanced platform engineers and DevOps professionals who aim to master application scaling through 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 environments.
• Apply best practices for security and compliance within a Kubernetes environment.

This instructor-led, live training session in Botswana (conducted online or onsite) is designed for Kubernetes professionals aiming to prepare for the CKS examination.

By the end of this programme, participants will possess the knowledge to secure Kubernetes environments and container-based applications throughout the different stages of an application's life cycle: build, deployment, and runtime.

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

Participants will delve into crafting scalable microservices architectures, refining container environments, and managing production workloads via Kubernetes. The curriculum encompasses advanced deployment strategies, GitOps-driven automation, and observability techniques to guarantee system reliability and optimal performance.

A significant emphasis is placed on navigating real-world operational challenges, including incident response, failure simulation, and root cause analysis. The programme wraps up by leveraging AI-powered tools to facilitate troubleshooting and expedite operational decision-making.

Upon completion of the training, participants will possess a solid grasp of how to build, deploy, monitor, and sustain resilient distributed systems within a Kubernetes-based ecosystem.

This instructor-led, live training in Botswana (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 live, instructor-led training held in Botswana (either online or onsite) is specifically 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.
• Create, deploy, and manage ML workflows utilizing Docker containers and Kubernetes.
• Execute complete machine learning pipelines across various architectures and cloud environments.
• Leverage Kubeflow to launch and control Jupyter notebooks.
• Develop ML training, hyperparameter tuning, and serving workloads spanning multiple platforms.

This instructor-led live training in Botswana (online or on-site) is designed for software developers and DevOps professionals at beginner to intermediate levels 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.
• Grasp 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.
• Utilize Minikube for developing, testing, and debugging applications.

This instructor-led, live training in Botswana (online or onsite) is designed for intermediate developers and DevOps engineers who want to utilise 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 Botswana (online or onsite) is designed for engineers who wish to evaluate the approaches and tools currently available, helping them make informed decisions on the path forward for adopting MLOps within their organisation.

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.