Here's a roundup of the resources that I've found most useful.
Blogs and OnlineThis is my friend Brandon Rohrer's blog: https://brohrer.github.io/blog.html We worked together at Microsoft and he's a data scientist at Facebook. This is the most comprehensive and easily explained resource I've encountered. You can find him and other influencers in the field on Twitter and LinkedIn to keep informed about new resources.
Brandon is in good company on this list of 9 YouTube channels to subscribe to for ML learning.
Khan Academy is an excellent resource for brushing up on concepts like standard deviation, which can be a tricky concept.
KDnuggets has a variety of resources including this 2019 predictions article.
Andrew Ng’s AI Transformation Playbook provides a business-oriented roadmap for your company to transform into a great AI company. His newsletter The Batch is a great resource.
Kaggle provides a fun way to improve your modeling skills, complete with cash prizes! The Titanic dataset is a good introduction, as are the Iris classification and the diamond linear regression.
Here's an AI in 3 minutes presentation I wrote for my local friend PowerPoint Club.
MOOCsMost of the major online sites offer classes you can audit for free or get certified for a fee. I recommend the following platforms:
Emeritus's MIT Professional Education machine learning class (for which I'm a learning facilitator)
Lynda.com. I am taking a python class through my local library's subscription.
Superintelligence: Paths, Dangers, Strategies
Automate The Boring Stuff With Python: Practical Programming For Total Beginners
Weapons of Math Destruction
Algorithms to Live By
Statistics Done Wrong
Machine Learning for Dummies
I recently read and really enjoyed The Master Algorithm, but I'd save it for after you have a fundamental understanding of machine learning.
Developers may benefit from this more technical reading list.
ConferencesIf you are an extrovert or a hands-on learner, I recommend learning from the experts at one of these conferences.
Strata: all things big data, expect announcements from large companies about their latest tech
PAPIs: a mix of expert and more entry-level sessions, organized by an awesome European-based committee
ODSC: really friendly, volunteer organized, more accessible sessions
Harvard's Institute for Applied Computational Science holds Computefest and some other excellent lectures and events
ICML: big names in data science attend this, very expert-level
MeetupsI'll provide a Boston listing here, but look for similar resources in your city.
So you want to be a data scientist
Boston AI Tech Talks Group
Thinkful Learn to Code
Boston AI Meetup
Boston Machine Learning
Boston WITI Meetup - Women in Technology
Women Who Code Boston
Boston Predictive Analytics
Boston Deep Learning Meetup
Boston Data Science Meetup