More Applied Data Science with Python

About this course

In our increasingly interconnected world, we’re collecting more raw data than ever. In “More Applied Data Science with Python,” you’ll learn how to extract and analyze complex data sets using Python. Practice using real-world data sets, like health data and comment sections, to develop visual representations and identify key patterns amongst populations. You’ll also learn to manage missing and messy data using advanced manipulation methods. Throughout this course series, you’ll build a foundation for advanced analytics and machine learning with the help of Scikit-Learn and NLP libraries by applying methods for data mining, clustering, topic modeling, network modeling, and information extraction. Upon completing the series, you'll have gained advanced data analysis skills that will help you gain insights into the datasets you're exploring. Learners should have intermediate Python programming skills before enrolling in the Specialization. It is encouraged that you complete Applied Data Science with Python prior to beginning this Specialization.

Course objectives

• build a foundation for advanced analytics and machine learning
• gain insights into diverse datasets