MLOps Crash Course for Beginners
Data scientists at the start of their careers often have the misconception that their job will be largely focused on training and improving models in a Jupyter notebook. The reality is that most data science value is created outside of a notebook.
This crash course is intended for data scientists with basic knowledge of developing machine learning models in a Jupyter notebook setting. By the end of the session, you will know:
- What is MLOps (Machine Learning Operationalization) and why it’s necessary?
- What is a machine learning pipeline?
- How to create and deploy a fully reproducible MLOps pipeline from scratch.
- Learn the basics of continuous training, drift detection, alerts, and model deployment.
Co-Creator of ZenML
We are looking for passionate people willing to cultivate and inspire the next generation of leaders in tech, business, and data science. If you are one of them get in touch with us!