[kriro]

Buy and work through "Artificial Intelligence: A Modern Approach". It's a huge book and the de facto standard for pretty much every AI 101+ course. Some of the stuff may not interest you some might but it covers a broad range (from logic based agents to Bayesian networks). It's systematic and has excellent references and further reading notes for each chapter. The focus is not on the currently sexy "data science" aspects though (however you will find plenty of material that is relevant).

The edX class from Berkeley is pretty fun and hands on. It uses Pacman as a running example and essentially teaches the agents stuff from AIAMA:

https://www.edx.org/course/artificial-intelligence-uc-berkel...

The Stanford class by Thrun and Norvig himself (one of the authors of AIAMA) is also good but I prefer the edX one:

https://www.udacity.com/course/intro-to-artificial-intellige...

Edit: changed to direct links for the courses

[tansey]

The AIMA book is sort of a Good Old-Fashioned AI (GOFAI) book that focuses a lot on agents and planning. The jobs this article is talking about are really machine learning ones-- taking large volumes of data and extracting knowledge, so as to build recommender systems and such. For that, Kevin Murphy's book, "Machine Learning: A Probabilistic Approach" is without a doubt the best book out there, both in terms of explaining things from the ground up and being the most comprehensive/up-to-date source.

[kriro]

There's still quite a bit of material on Bayesian networks (with the dreadfull dentist example :D), neural networks and support vector machines but overall you're right the focus is on agents. The relevant chapters are great staring points though and as always filled with great reference material for further reading.

+ I'm pretty sure if you apply for an AI job somewhere and it's labaled AI and not "data science" they'll expect that you know the material in AIAMA.

[juliangregorian]

Murphy's book is actually subtitled "A Probabilistic Perspective" -- "Machine Learning: A Probabilistic Approach" is a different book by a different author.

[wimagguc]

+1 for the Stanford course. Great intro to AI and super easy to follow - I've done it after my uni class elsewhere, and it helped to internalise what I've learned there.

[musername]

reading the book still requires a significant amount of time