Data Science Methodology

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  • Course Number
  • Classes Start
    Any time, Self-paced

About This Course

Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn:
  • The major steps involved in tackling a data science problem.
  • The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment.
  • How data scientists think!
Please note that version 3.0 of this course was released on September 15, 2017. Please refer to the Change Log section in the course for a detailed description of the changes and updates. You can start creating your own data science projects and collaborating with other data scientists using IBM Data Science Experience. When you sign up, you get free access to Data Science Experience. Start now and take advantage of this platform.

Course Syllabus

Module 1: From Problem to Approach
  • Business Understanding
  • Analytic Approach
Module 2: From Requirements to Collection
  • Data Requirements
  • Data Collection
Module 3: From Understanding to Preparation
  • Data Understanding
  • Data Preparation
Module 4: From Modeling to Evaluation
  • Modeling
  • Evaluation
Module 5: From Deployment to Feedback
  • Deployment
  • 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

  • Passion for Data Science
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