Learn about the emergence of MLOps and production-level data and ML pipelines
Understanding of Kedro framework and basic functionalities
How to build a data pipeline with a demo on Kedro
Software Engineer | QuantumBlack
Module 1: The emergence of MLOps and production-level data and ML pipelines
- Learn about the trends driving interest in production-level code data science code
- Get exposure to software principles data engineers and data scientists should consider applying to their code to make it easier to deploy into the production environment
- You will need a basic understanding of data science, this module is geared to beginners
Module2: Overview of Kedro
- Learn what Kedro is by going through basic functionalities like the project template, configuration, data catalog and pipeline
- I'll show how it fits into the workflow for creating robust and reproducible data pipelines
Module 3: Short demo of building a data pipeline with Kedro
- A short demo for how to create a new Kedro project, build and visualize a data pipeline using an example dataset.
This course is for current or aspiring Data Scientists, Machine Learning and MLOps Engineers, AI Product Managers
Knowledge of following tools and concepts is useful:
Basic knowledge of Python and some familiarity of Python data science libraries (e.g. Pandas, Jupyter notebook) is recommended.
The course is aimed at data scientists and data engineers who are interested in building a production-ready data pipelines.