How to map out a plan for finding value in data.
Jerry Overton is a Data Scientist and Distinguished Technologist in DXC’s Analytics group. He is the Principal Data Scientist for the strategic alliance between DXC and Microsoft known as Industrial Machine Learning—enterprise-scale applications across six different industries: banking and capital markets, energy and technology, insurance, manufacturing, healthcare, and retail.
Jerry is the author of the O'Reilly Media eBook Going Pro in Data Science: What It Takes to Succeed as a Professional Data Scientist. He teaches the Safari live online training course Mastering Data Science at Enterprise Scale: How to design and implement machine-learning solutions that improve your organization. In his blog, Doing Data Science, Jerry shares his experiences leading open research and transforming organizations using data science.
The top 5 habits of a professional data scientist.
In this report, you will learn practices for making good decisions with missing or sketchy information, and advice for surviving (and even thriving) as a data scientist in your organization.
Using induction to test your hypotheses
How an algorithm is to a data scientist what a compound microscope is to a biologist.
A look at what it takes to be a professional data science programmer.
A real-world example of how a short delivery cycle fosters creativity.
Jerry Overton walks you through how to build and execute a data strategy, how to write algorithms, and how to experiment on an enterprise scale.