Data Science Methodology – Version 1 (Archived)

This course equips you with the skills required to solve any data science challenges. The ‘Data Science Methodology’ course provides you the know-how to analyzing problems in different ways to create a thorough understanding of the challenges.

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Course Details

Course Code: DS0103EN

Audience: Data Scientists, Data Engineers, Anyone with interest in Data Science

Course Level: Beginner

Time to Complete: 4 hours

Language: English

About the Course

This course provides you with the major steps involved in tackling a data science problem and practicing data science, with interesting real-world examples at each step – forming a concrete business or research problem, collecting and analyzing data, 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

Self-paced
Flexible enrolment
Audit multiple times

Recommended Existing Skills

None

Requirements

None

Course Staff

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.