How do you get into artificial intelligence?

When I tell people I work in artificial intelligence, the most common question I get is how I got started. I followed the learn on the job approach. I was offered an amazing opportunity at Microsoft in 2016 and I took it, and have been learning ever since. I've held product management roles creating or expanding on AI projects for several industries, and now I work for myself in this domain. I have taken some massively open online classes (MOOCs) that offer a solid foundation in machine learning. I've attended dozens of conferences, meetups, and affinity groups.

Here's a roundup of the resources that I've found most useful.

Blogs and Online

This 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.

MOOCs

Most of the major online sites offer classes you can audit for free or get certified for a fee. I recommend the following platforms:

General Assembly
Emeritus's MIT Professional Education machine learning class (for which I'm a learning facilitator)
Coursera
Edx
Udemy
DataCamp
Thinkful
Lynda.com. I am taking a python class through my local library's subscription.

Books

Prediction Machines
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.

Conferences

If 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

Meetups

I'll provide a Boston listing here, but look for similar resources in your city.

General Assembly
So you want to be a data scientist
ODSC
Boston AI Tech Talks Group
DataWomen
ConnectAI
Thinkful Learn to Code
Boston AI Meetup
Boston Machine Learning
Boston TechBreakfast
Boston WITI Meetup - Women in Technology
Women Who Code Boston
Boston Predictive Analytics
Boston Deep Learning Meetup
Boston Data Science Meetup