Achieve your first Machine Learning project in Python in 2h

In just 2 hours you will be able to complete a Machine Learning project from start to finish.

You will know all the steps of a Data Science project and how to carry them out in Python.

So far you have probably learned a lot about the theory of Machine Learning but you have no idea how to apply it to real life cases.

You may want to incorporate Machine Learning into your professional projects to improve your results but this seems overwhelming.

If you keep going like this, you can continue to learn about Machine Learning without going into practice and lose a lot of time. Worse, you might even get discouraged and give up all your efforts.

The real problem is that there are a lot of things to take into account in a Data Science project, from data collection, to data preparation, to the choice of model, to the optimisation of the algorithm.

The solution to all this is a clear plan with simple to follow but very powerful instructions, applicable to any Machine Learning project.

That's why I wanted to create a complete course, which details all the steps of Machine Learning projects, from start to finish, by implementing them directly in Python.

Be careful, this training is intense, many technical concepts are covered, as well as several Python libraries and functions. You need to be motivated.

You will have to carefully follow the different steps mentioned to make sure that the final result is valuable.

After completing this training, you will know how to solve a problem using Machine Learning and Python. You will discover how powerful this discipline can be.

Whenever you will be given any set of data, you will switch on your computer and start your project by following the different steps presented here. You will no longer be confused by where to start.

As you keep coding, you will remain confident in your approach because you will know where you are going.

You will have more and more ideas of how to apply it in your professional life.

In this course, you will discover the powerful technique of feature engineering.

You will learn 3 simple but powerful techniques used to explore data.

You will discover how to automate data preparation with 4 tools used by data scientists.

Finally, you will learn how to significantly improve your model, automatically, with a very robust method.

If you currently know few Machine Learning models, don't worry, I explain the intuition behind the models I use. This course is also suitable for those who only have a few basics in Python because the code is explained as we go along.

This course is a real guide for any Python Learning Machine project.

See you in the training.

See you soon,

Damien