White Paper

The Difference Between AI and Machine Learning

The business world is overloaded with buzz terms like artificial intelligence,
machine learning, AI transformation, deep learning, and data science. We know
that these fields, technologies, and tools are changing the competitive landscape
across verticals and are soon to become more table stakes and foundational than
disruptive. However, people can know they’re important while not even knowing
what they really mean. I’d forgive you for your confusion because these words
are overloaded and they’re not even used consistently. My goal here is to dispel
any confusion by demystifying these terms: What are artificial intelligence,
machine learning, and data science? Where do they intersect? Where do they
diverge? Read on to find out.

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Hugo Bowne-Anderson

Head of Data Science Evangelism and Marketing at Coiled; Previously a Data Scientist at DataCamp

Hugo Bowne-Anderson is Head of Data Science Evangelism and VP of Marketing at Coiled, a company that makes it simple for organizations to scale their data science seamlessly. He has extensive experience as a data scientist, educator, evangelist, content marketer, and data strategy consultant at DataCamp, the online education platform for all things data. He has experience teaching basic to advanced data science topics at institutions such as Yale University and Cold Spring Harbor Laboratory, conferences such as SciPy, PyCon, and ODSC and with organizations such as Data Carpentry. He has developed over 30 courses on the DataCamp platform, impacting over 500,000 learners worldwide through his own courses. He also created the weekly data industry podcast DataFramed, which he hosted and produced for 2 years. He is committed to spreading data skills, access to data science tooling, and open-source software, both for individuals and the enterprise.

Connect with Hugo on LinkedIn and Twitter.

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