Data Science Methodology – Version 1 (Archived)

Grab you lab coat, beakers, and pocket calculator…wait what? wrong path! Fast forward and get in line with emerging data science methodologies that are in use and are making waves or rather predicting and determining which wave is coming and which one has just passed.

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Update - September 11, 2016:


BDU is committed to offer quality and current content. This course is archived as of September 19th, 2016 (end date).   A new version of this course is now available! The archived course is fully available all the time to those who enrolled before the course end date. They can continue with the course as usual, and even obtain a completion certificate; however we encourage you to take the updated course.  Certificate information will stay in your profile even after the course is archived, though the course name will be changed to include the course version number.

About This Course

Learn how data scientists think!

  • Learn the major steps involved in tackling a data science problem.
  • Learn the major steps involved in practicing data science, with interesting real-world examples at each step: from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.

Course Syllabus

  • Module 1 - Introduction to Data Science Methodology
  • Module 2 - Business Understanding
  • Module 3 - Analytic Approach
  • Module 4 - Data Compilation
  • Module 5 - Data Preparation
  • Module 6 - Data Modeling
  • Module 7 - Model Evaluation
  • Module 8 - Model Deployment and Feedback

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.

Recommended skills prior to taking this course

  • None


  • None

Course Staff

John B. Rollins, Instructor of Data Science Methodology

John B. Rollins

John B. Rollins, Ph.D., P.E., is a Data Scientist.   He is a  part of IBM Analytics in IBM. He holds a Ph.D. in Petroleum Engineering and Economics from Texas A&M University. With an excellent background of engineering consulting, professor and researcher, he has authored many patents, books, and papers. He achieved honors and awards from IBM as an IBM Second Plateau Inventor.  He has great experience in data science methodology.

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