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Congratulations!

1. Congratulations!

You made it!

2. You've gone a great distance.

From domain knowledge to automated feature selection, you can now preprocess a raw dataset to make it fit for analysis and prediction. You can implement a gamut of feature engineering techniques that go from manual variable selection to creating new quantitative variables from qualitative ones and apply advanced methods such as feature hashing, polynomial fitting, and hyperparameter tuning. Not only that, but you are able to implement a full workflow and assess the performance of your model. You are ready to apply these skills at work and take them to the next level.

3. Where to go from here?

Dimensionality reduction with R will delve into a deeper understanding of some of the techniques you learned here, plus a few more. Then, advanced dimensionality reduction will help you consolidate that knowledge along with a few new tricks. To up your modeling game, the modeling with tidymodels in the R course will extend the workflow toolset you learned here and give you the tools to move ahead. Whatever you decide. Take a bold step and keep modeling!

4. Go get them all!

It is time for you to apply your knowledge wherever you are!