# The end of the beginning
This is the end of the course.
The course is an introduction to data science. Along the way, we hope you learned:
* Some of the [computational tools](../intro/computational-tools) including the
Python language, Jupyter notebooks, Numpy arrays, and Pandas data frames.
* Some of the [statistical techniques](../intro/statistical-techniques), including
simulation, testing for differences between groups with permutation, testing
for straight-line relationships, and predicting categories of data from measurements.
You now know the fundamental building blocks for the algorithms you have used; variables, arrays, for-loops, and functions.
Of course, this is just the beginning. If you are interested, we highly recommend the [Berkeley data science textbook](https://www.inferentialthinking.com). You have already read some of the chapters, because there are versions of those chapters in this course, but the Berkeley course goes much further. With the background you have now, you should be able to follow that course to the end. It's an excellent introduction.
Now, go forth, and multiply (and divide, and add and subtract). As you do, you will discover interesting things about the world. You have the tools to test and challenge our new world of [big data and ubiquitous algorithms](https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction).