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

This instructor-led, live training in Nigeria (online or onsite) 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 Nigeria (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 instructor-led live training, offered in Nigeria (either online or onsite), targets Kubernetes practitioners aiming to prepare for the CKS exam.

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

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 Nigeria (online or onsite) is designed for engineers who want to leverage Helm to simplify the installation and management of Kubernetes applications.

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

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

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

By the end of this program, participants will have the ability to:

• Install and set up Kubeflow in on-premise and cloud environments.
• Create, deploy, and control ML workflows using Docker containers and Kubernetes.
• Execute full machine learning pipelines across different architectures and cloud infrastructures.
• Use Kubeflow to generate and administer Jupyter notebooks.
• Implement ML training, hyperparameter tuning, and serving workloads across various platforms.

This instructor-led, live training in Nigeria (online or onsite) is aimed at beginner-level to intermediate-level 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 basic 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 Nigeria (online or onsite) is designed for intermediate-level developers and DevOps engineers who want to incorporate Minikube into their development workflow.

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

• Set up and manage a local Kubernetes environment using Minikube.
• Gain insight into deploying, managing, and debugging applications on Minikube.
• Integrate Minikube into their continuous integration and deployment pipelines.
• Enhance their development process by leveraging Minikube's advanced features.
• Apply best practices for local Kubernetes development.

This instructor-led live training in Nigeria (online or onsite) is designed for engineers who wish to evaluate the available approaches and tools to make informed decisions on adopting MLOps within their organisations.

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.