Data Science: Applying Data Science fundamentals to Stock Market Data

In this talk we will demonstrate the typical steps that a Data Science project will go through using stock market data; setting a goal, acquiring and exploring the data, modeling, analysis, visualizing, evaluating the results and setting future goals. Ting and I will perform the different roles on a data science project and use multiple tools to achieve the end result. The presentation will be a mix of code demos, slides and graphs/reports.

Yin-Ting Chou, M.S., Statistics, University of Minnesota-Twin Cities
Ting is an Engineering Intern at ChannelAdvisor and specializes in Data Predictive Analytics.

Conrad D'Cruz, M.S., Computer Science, Bowling Green State University
Conrad is a Project Manager, Business Systems Analyst and Data Analyst and has been studying the stock market for a long long time.