Welcome to this course, Aggregation for Data Scientists. I'm Nathan, and it's my pleasure to be one of your instructors for this course. This course is part of our specialization MongoDB Analytics, which has been designed to provide you with a broader understanding of how to fully utilize MongoDB from a data science and analytics perspective. In this course, you will learn how to leverage MongoDB's powerful aggregation of framework to shape and ask questions of your data. You will also learn the basics of how to handle that data once transformed by converting into a data frame and use basic machine learning models to make predictions. These topics will be introduced and explained in stages. First, you'll be gradually introduced to the Aggregation Framework, and how to perform shaping and analysis operations. Once you have a solid grasp of the Aggregation Framework, we'll be looking into several different datasets and using the popular Python machine learning library, scikit-learn, to train models and make predictions. This course is for both recent additions to the MangoDB family that would like to learn about data science and machine learning, and for experienced data science practitioners who would like to understand how to leverage the power of MongoDB to improve their workflows. Finally, I just want to welcome you again to the second course of MongoDB. We hope that you enjoy the material that we prepared for you. We wish you the best of luck.