15 Mistakes to Avoid in Data Science

Offered By: LinkedIn Learning

Tags

Data Science Courses Communication Skills Courses Stakeholder Engagement Courses Data Storytelling Courses

Course Description

Overview

Save time and grow your skills faster. Learn the top mistakes that you should avoid as a data scientist.

Syllabus

Introduction

Avoid common mistakes to excel in data science

1. Mistakes to Avoid

Communicating with overly technical language
Skipping the fundamentals
Moving too quickly
Having a data set that is too small
Failing to adopt new tools
Not considering the level of variation
Lack of documentation
Relying solely on formal education
Taking too long to share results
Including your bias
Overpromising solutions to stakeholders
Building tools from scratch
Assuming the knowledge level of stakeholders
Not telling a story with the data
Not confirming with stakeholders

Conclusion

Get started on the right path

Taught by

Lacey Westphal, Sam Cvetkovski, Louis Tremblay, Sara Anstey and Madecraft

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