Editor’s Note: This post is republished with permission from Trust Insights, a company that helps marketers solve/achieve issues with collecting data and measuring their digital marketing efforts.
A question I’m asked almost daily now is, “what are the best resources for getting started with data science, machine learning, and AI, especially for marketers?”
This list will be updated from time to time as new resources become available, but the basics should remain relatively stable.
What Order to Learn In
We recommend the following path:
- Statistics fundamentals
- Ethics
- Data science
- Machine learning & AI
Statistics
The fundamental underpinning of data science is statistics, so we strongly encourage you to read and become proficient with statistics. Read this book:
Ethics
We also strongly recommend anyone interested in data science, machine learning, and artificial intelligence to be well versed in professional ethics. Read this book:
- Ethics and Data Science (free!)
Data Science
For learning practical data science techniques, we recommend the R statistical language and this book:
Prefer podcasts? Check out:
For those preferring a course, look to MIT’s data science course (free!):
- 6.001 Introduction to Computer Science
- 6.002 Introduction to Computational Thinking and Data Science
Machine Learning and AI
Machine learning is the science of training machines to write their own software based on data provided to them.
- AI for Marketers – my short guide on the topic
For a much more technical, mathematical look, check out this book on Amazon:
A keynote address on YouTube I gave that gives a solid overview:
Prefer podcasts? Check out:
For those preferring a course, Google has an excellent free course:
- Machine Learning Crash Course (free!)
Other Resources
Be sure to check out the following useful blogs:
Christopher S. Penn
Christopher S. Penn is cofounder and Chief Data Scientist at Trust Insights.