Create a learning path for MLOps focusing on engineering

Before anyone hits me with "bootcamps have been dead for years", I know. I'm already a data scientist with a MSc in Math; the issue I've run into is that I don't feel I am adequate with the "full stack" or "engineering" components that are nearly mandatory for modern data scientists. I'm just hoping to get some recommendations on learning paths for MLOps: CI/CD pipelines, Airflow, MLFlow, Docker, Kubernetes, AWS, etc. The goal is basically the get myself up to speed on the basics, at least to the point where I can get by and learn more advanced/niche topics on the fly as needed. I've been looking at something like [this datacamp course](https://www.datacamp.com/tracks/machine-learning-engineer?utm_cid=23427789795&utm_aid=191337070316&utm_campaign=220808_1-ps-dscia~dsa-gen~python_2-b2c_3-nam_4-prc_5-na_6-na_7-le_8-pdsh-go_9-nb-e_10-na_11-na&utm_loc=9189172-&utm_mtd=-c&utm_kw=&utm_source=google&utm_medium=paid_search&utm_content=ps-dscia~nam-en~dsa~generic~tracks-python&gad_source=1&gad_campaignid=23427789795&gbraid=0AAAAADQ9WsEiDvZYXHXFe3SFVhmg5gDHP&gclid=Cj0KCQjw37nNBhDkARIsAEBGI8P0_-QJLNOC7KBbfccfl1IxIzrdEpoP_Ncp6WcaNLoKfuU5Ixj5JooaAsu9EALw_wcB), for example. This might be too nit-picky, but I'd definitely prefer something that focuses much more on the engineering side and builds from the ground up there, but assumes you already know the math/python/ML side of things. Thanks in advance!