I’m a couple years into my data analyst role and trying to transition into more data science and machine learning work. I’ve built some decent Python skills, but I feel stuck in the “intermediate purgatory.” Tutorials only go so far, and when I try to build projects from scratch, I hit decision fatigue fast. How did you push through that point where things are familiar but not yet fluid? I’d love recommendations on real-world projects or open datasets that helped you stretch your thinking.

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Totally relate to the “intermediate purgatory” feeling. What helped me was committing to one messy, end-to-end project—even if it wasn’t perfect. Working with datasets from Kaggle competitions or Data.gov gave me more room to practice problem framing and cleanup, which tutorials don’t cover well.

The only way to overcome this is not to let your curiosity go down. Learn from beginning to end, from data gathering to analysis to building a model, and then enjoy the joy of creating it.

The main thing is motivation. Good luck!

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