
Congratulations on completing the course, you now have a well rooted understanding of the flexibility of machine learning in exploring complex patterns in data. In addition, you have acquired a new set of tools with which you can get to work with straight away.

> A big **Well Done** for completing this course and expanding your horizons.

A few key things you now have experience in:

- You have expanded your professional's toolkit of machine learning models to deploy on your own projects.

- You have gleaned an understanding of the concepts behind the kernel trick in improving model performance, including feature expansion and non-parametric models.

- You have set to work coding examples in `python`, giving you real experience of using these tools--ready for you next challenge.

- You had a good time along the way!

... but that's not the end of the story. What you have seen in this course are effective 'light' models that introduce the principles behind non-parametric machine learning. We now want to embark upon more industry standard 'state-of-the-art' models: **Decision Trees, Random Forests & Gradient Boosting**.

## What next for your ML training?

In _The Kernel Trick_ we took a model we knew and understood, the linear model, then played a trick with the covariance of out input data features.

At the other end of the scale, what if we abstracted away any notion of model structure and followed our nose with the way the existing data splits?

This is the key idea behind tree based algorithms. By the adoption of robust statistical techniques and gradient acceleration, the tree-based algorithms are amongst the most effective to date. And so we have created a course to walk you through the understanding you need for deployment; _['Tree-based algorithms: Random Forests and Gradient Boosted Trees'](/course/random-forests-and-gradient-boosted-trees)_ with me, [Andy Corbett](https://www.linkedin.com/in/dr-andrew-corbett-427162203/).

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Information about all our courses can be found on the [course overview page on the academy website](/courses). And we'll be keeping you posted with all the exciting activities going on at digiLab on our Linkedin @digilab.

## 🏆 Downloading your Certificate of Completion

Now it's time to share your success. If you've completed all lessons along the way, you can download your Certificate of Completion [here](/request-a-certificate). Just select your course from the dropdown menu and click the _"Request your Certificate"_ button.

This is more than just a piece of paper; it's a recognition of your hard work and new skills. We encourage you to share this certificate on [LinkedIn](https://www.linkedin.com/). Show off your accomplishment and inspire others to embark on their own learning journey.


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