MLOps Data Science

A practical introduction and comprehensive insight into MLOps.

This two-day training provides data science specialists with a hands-on introduction to MLOps, optimizing the entire machine learning lifecycle through automation and standardization. With a focus on code and data versioning, as well as model parameter monitoring, it ensures consistent and reproducible results. Continuous Integration and Continuous Deployment (CI/CD) accelerate the launch of new ML solutions and enhance the efficiency of the development process.

Our training team consists of professionals who are both active in machine learning research and have extensive experience in the practical implementation of data models in companies.

Refresh the basics of machine learning and terminology
Learn techniques for data acquisition, preparation, and versioning
Understand and develop MLOps processes: model training and development using pipelines
Use DVC for data versioning and CML for ML pipelines
Get to know other tools like MLFlow and Kubeflow in the MLOps ecosystem

Participants need a laptop with direct internet access

Our training is aimed at people who work with data and data models and already have prior knowledge in data science, and who want to learn techniques and processes to deploy and maintain services from these data and models.

CHF 2200 / participant for two days.
Group sessions consisting of 8 to 24 participants.
Includes catering and documentation.
Discounts available for groups of 12 participants or more.

Content

Our trainings consist of diverse presentations and hands-on labs to deliver the content in an engaging way. We are happy to refer to your infrastructure in consultation. If additional content is needed, we can make adjustments upon your request.