Short Course Description

Bridging Statistics and Data Science

With the recent big data revolution, enterprises ranging from FORTUNE 500 to startups across the US are using Data Science to bring valuable business insight from all the data collected. Statisticians are great data scientist candidates, but there are relatively few data scientists with statistics education background. This course aims to bridge the gap between Statistics and Data Science. Data science is a combination of science and art with data as the foundation. We will cover both the science part and the art part (such as data science project flow, general pitfalls in data science projects, and soft skills to communicate with business stakeholders effectively). The course will be hands-on and we will use the Databricks community edition cloud platform and R-Studio to illustrate programming, big data platform usage (such as Spark) and standard machine learning algorithms.

Instructor Bios

Dr. Ming Li (Amazon) Dr. Ming Li is currently a Senior Data Scientist at Amazon and an Adjunct Faculty member of the Department of Marketing and Business Analytics at Texas A&M University-Commerce. Dr. Li was the 2017 Chair of the ASA Section on Quality & Productivity. He was a Data Scientist at Walmart and a Statistical Leader at General Electric Global Research Center. He obtained his Ph.D. in Statistics from Iowa State University in 2010. With an in-depth statistics background and a few years’ experience in data science, he has trained and mentored numerous junior data scientist from diverse backgrounds such as statistician, programmer, software developer, database administrator and business analyst. He is also an Instructor of Amazon’s internal Machine Learning University and was one of the key founding members of Walmart’s Analytics Rotational Program which bridges the skill gaps between new hires and productive data scientists Dr. Hui Lin (DowDuPont) Dr. Hui Lin is currently a Data Scientist at DowDuPont. She is the leader in the company at applying advanced data science to enhance Marketing and Sales Effectiveness. She has been providing statistical leadership for a broad range of predictive analytics and market research analysis since 2013. She is a co-founder of the Central Iowa R User Group, blogger of scientistcafe.com and 2018 Program Chair for the ASA Section on Statistics in Marketing. She enjoys making analytics accessible to a broad audience and teaches tutorials and workshops for practitioners on data science. She holds M.S. and Ph.D. degrees in statistics from Iowa State University, and a B.S. in mathematical statistics from Beijing Normal University.