If you're watching this video, you can be really proud of yourself, because this means you have really learned a lot in the previous three Coursera courses. You have learned about Apache spark, data integration, data research station, data modeling, artificial intelligence, deep learning and all the instruction you need to become a successful data scientist. The only thing what is missing, is some process knowledge. So, in this Capstone project, we'll teach you how to successfully deliver a data science project, end-to-end. You will start with a use case and a dataset. Starting from there, you will have an initial look at the data. You will do some ETL, which stands for Extract Transform Load, and some feature engineering. Starting from there you will then train a machine learning model and evaluate it. After some iterations that you tune and tweak your feature engineering steps, you will see how to increase model performance. After that evaluation, you have to create a data product and finally you have to create a presentation off your ground to stakeholders and to peer data scientists. Once you've completed all this, you have completed the Capstone project and given the three courses in the capstone project you're then IBM certified data scientist for advanced data science. Isn't that good? So, have fun, stay tuned and meet me in the discussion forum. I'm there for you if you have questions.