The Data Science Method

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Despite and influx in computing power and access to data over the last couple of decades, our ability to use data within the decision-making process is either lost or not maximized all too often. We do not have a strong grasp of the questions asked and how to apply the data correctly to resolve the issues at hand.

The purpose of this course is to share the methods, models and practices that can be applied within data science, to ensure that the data used in problem-solving is relevant and properly manipulated to address business and real-world challenges.

You will learn how to identify a problem, collect and analyze data, build a model, and understand the feedback after model deployment.

Advancing your ability to manage, decipher and analyze new and big data is vital to working in data science. By the end of this course, you will have a better understanding of the various stages and requirements of the data science method and be able to apply it to your own work.

What you will learn

• Explain why a methodology for approaching data science problems is needed
• List the major steps involved in tackling a data science problem
• Determine appropriate data sources for your data science analysis methodology
• Describe the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study
• Demonstrate your understanding of the data science methodology by applying it to a problem that you define

Skills you learn

• Big Data
• Problem Solving
• Data Science

Auto Summary

Enhance your data science skills with "The Data Science Method," an IT & Computer Science course by edX. Taught by IBM experts, this foundational course focuses on applying data science methods, models, and practices to solve real-world problems. Learn to identify issues, collect and analyze data, build models, and interpret feedback. Ideal for beginners, this course offers a skill badge upon completion. Subscription options include a Starter plan.