Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision-making process is either lost or not maximized at all too often, we don’t have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.

This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem-solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn:

• – The major steps involved in tackling a data science problem.
• – The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.
• – How data scientists think!

IBM