1. Congratulations
Well done! You made it through the course!
2. You learned things
In Chapter 1 you saw how to fit a simple linear regression with both a numeric and a categorical explanatory variable, and how to interpret the model coefficients.
In Chapter 2 you saw how to make predictions with a linear regression model, how to work with model objects, what regression to the mean means, and how to transform model variables.
In Chapter 3 you saw how to quantify and visualize model fit, and learned about outliers, leverage, and influence of observations.
In Chapter 4 you fitted a simple logistic regression model, calculated its predictions in several different ways, and calculated performance metrics using a confusion matrix.
3. Multiple explanatory variables
The next step in your journey is to learn how to run regressions with more than one explanatory variable.
4. Unlocking advanced skills
Once you've done that, it will unlock a lot more DataCamp content covering advanced modeling and machine learning skills.
5. Regression is important everywhere
Regression is such an important modeling technique because it is used in so many different fields. Naturally, DataCamp has courses that specialize in these applications.
6. Let's practice!
I hope you enjoyed the course. Happy learning!