Data Science Methodology

Big Data University

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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: From Problem to Approach

Business Understanding - Concepts & Case Study
Analytic Approach - Concepts & Case Study

Module 2: From Requirements to Collection

Data Requirements - Concepts & Case Study
Data Collection - Concepts & Case Study

Module 3: From Understanding to Preparation

Data Understanding - Concepts & Case Study
Data Preparation - Concepts & Case Study

Module 4: From Modeling to Evaluation

Modeling - Concepts & Case Study
Evaluation - Concepts & Case Study

Module 5: From Deployment to Feedback

Deployment - Concepts & Case Study
Feedback - Concepts & Case Study

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

Requirements

None

Course Staff

John B. Rollins

John B. Rollins, Ph.D., P.E., is a Data Scientist at IBM. He is part of the IBM Analytics group and holds a Ph.D. in Petroleum Engineering and Economics from Texas A&M University. With an excellent background of engineering consulting, having been a 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.

Course Summary

Course Number
CS-13
Classes Start
Any time, Self-paced
Estimated Effort
3 hours