What topics will be covered in the Python for Data Science course?

Introduction to Python for Data Science will cover the entire data science workflow, from data acquisition and cleaning to exploration, analysis, and visualization. Throughout the course, students will work with Python's extensive ecosystem of libraries and frameworks, including NumPy, pandas, and scikit-learn, as well as popular visualization libraries such as matplotlib and seaborn. Also, students will learn how to create a data pipeline and work with different data formats.

The students will work on a final project, where they will be able to put into practice the skills they have learned and apply them to a problem of their choice.

By the end of the course, students will have a solid understanding of the fundamental concepts and techniques used in data science, as well as the ability to apply these techniques to real-world problems using Python.

You can take a look at our curriculum to see all of the topics we cover.