Producing numbers is not enough; effective data scientists know how to interpret the numbers and communicate findings accurately to stakeholders to inform business decisions. Visualization is a relatively recent field of research in computer science that links perception, cognition, and algorithms to exploit the enormous bandwidth of the human visual cortex. In this course you will design effective visualizations and develop skills in recognizing and avoiding poor visualizations.
Just because you can get the answer using big data doesn’t mean you should. In this course you will have the opportunity to explore the ethical considerations around big data and how these considerations are beginning to influence policy and practice.
Learning Goals: After completing this course, you will be able to:
1. Design and critique visualizations
2. Explain the state-of-the-art in privacy, ethics, governance around big data and data science
3. Explain the role of open data and reproducibility in data science