As in other things that you pursue in your life, practice is the only thing that will help you to improve your skills in developing ML pipelines. You need to spend a considerable amount of time with many different techniques and algorithms to deal with various problems and datasets.
Especially in real-word projects, where you may not come across similar problems, every project will require you to have a different approach. You will quickly realize that it's not only modeling that matters, but it's rather the understanding of how these technologies integrate with each other, and play nicely in enterprise software architectures.
By learning AutoML systems, you took a huge step forward and have a better understanding of AutoML pipelines. You should definitely strive to learn more about other aspects, such as the domain-specific applications in the areas of your...
