2011 Turing Award Lecture - Judea Pearl - Part 1

Judea Pearl presented his Turing Award Lecture at the AAAI-12 Conference on July 24 2012. The title of his one hour talk,

The Mechanization of Causal Inference: A “mini” Turing Test and Beyond

gives both a brief overview of the history, and a glimpse of the future of a field of work that holds much promise in advancing the discipline of AI. A video of the talk can be found at the ACM Turing award site here.

Pearl's earlier work in the 80's on combinatorial search lead to the book, Heuristics:Intelligent Search Strategies for Computer Problem Solving published in 1984. This was followed by, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference in 1988, and Causality: Models, Reasoning and Inference in 2000 of which a second edition was published in 2009.

More On-Line Courses

Following up with my previous post, Some on-line courses, here are few more:

• Human-Computer Interaction by Scott Klemmer
• Game Theory by Matthew Jackson
• Computer Security by Dan Boneh
• Natural Language Processing  by  Dan Jurafsky and  Christopher Manning

There are also two courses coming up at Udacity taught by Dale Evans and Sebastian Thrun

• CS 101: Building a Search Engine
• CS 373: Programming a Robotic Car

Some On-Line Courses

At the end of last year I took part in the online version of the Introduction to Artificial Intelligence course presented by Sebastian Thrun and Peter Norvig from Stanford University. I participated partly out of interest, and partly to see how the course was presented. In the end it was a great experience, learning from two experts in the field who are passionate about what they are teaching was well worth the time spent. The format was simple; weekly video lectures split into roughly 10 minute segments. A great inclusion were the small quizzes during the talks, which helped test your understanding of what had just been shown or challenged you to think about a topic which was coming up. The weekly on-line assignments and two exams really added to the overall enjoyment and satisfaction of knowing how well you understood the content.
There are several interesting on-line courses now on offer starting from around February 2012. I've listed a few of them below.

• Design and Analysis of Algorithms I by Tim Roughgarden
• Computer Science 101 by Nick Parlante
• Model Thinking by Scott Page
• Machine Learning by Andrew Ng
• Software as a Service by Andrew Fox and David Patterson
• Probabilistic Graphical Models  by Daphne Koller

I'll follow up with a few more on-line courses in the next post.