As someone who has been in the analytics profession for the last five years, this course exceeded my expectations in so many ways. Throughout the five week course, we were able to (1) create feature, training, and inference pipelines (2) Docker-ize those pipelines and deploy them locally as microservices, and (3) push and run those microservices on cloud. We got our hands dirty with realtime data (websockets, Kafka, Redpandas), feature stores (Hopsworks), model registries (Comet ML), dashboards (Streamlit), and deployment (REST API, Quix Cloud). Pau is an expert engineer and an even better teacher. The course was conducted completely live so we got to see what goes on behind the scenes in a professional machine learning environment, including debugging and going through documentation. As an analytics professional used to Jupyter Notebooks, this course was an eye-opener. It encouraged me to rethink my coding practices, especially how I organize, package, and deploy my code. I've already begun to apply some of my learnings to my work. After going through the course, I'm confident that I can build an end-to-end ML product. Could not recommend this more.