Machine Learning Data Lifecycle in Production

While continuing my journey to refresh and learn new concepts I have completed another excellent course Machine Learning Data Lifecycle in Production from DeepLearning.ai (offered in Coursera platform), from a specialization Machine Learning Engineering for Production (MLOps) Specialisation.

As usual, after completing the course there is a certificate of completion offered, which could be useful to show one's knowledge of the subject matter. Certificate is available online or could be downloaded if required.

Overall impression of the course is really good, since it covers a number of important topics, such as Machine Learning Metadata and Tensor Flow Extended. Description of the main concepts is good and often much clearer compared for example to the documentation.

The labs in the course are excellent and could be often reused fully or partially in real-life projects. The assignment labs are also very good, since they are, on one hand, not overcomplicated and, on another hand, not overly simple.

The course and the labs are though not for beginners and would require a bit more advanced level.

To summarize, I would definitely recommend this course to understand important topics in the MLOps space, such as ML Metadata and ML Pipelines.