Fortnightly Mailing

Final report from the Norvig/Thrun/Stanford/Know Labs Artificial Intelligence course

Word-cloud by Sea Otter

(Other posts tagged ai-course. Post originally published on 20/12/2011, with paragraph one updated to incorporate completion numbers kindly provided by David Stavens of Know Labs, and a new concluding sentence to the final paragraph.)

Along with just over 20,000 others (some 3,000 fewer than had taken the midterm exam) I completed the final examination for the free online Introduction to Artificial Intelligence course taught by Sebastian Thrun and Peter Norvig. Here is my final participant's  report from the course.

1. The final section of the course concerned Natural Language Processing. I've had an interest in machine translation for some years [e.g.]: and it was this interest that initially made me aware of Peter Norvig's work.) So for me this meant that the best part of the course came last, and if you want to gain an underlying appreciation of the science of natural language processing, it will take you a couple of hours to work through the courses 42 short videos about NLP, starting here. It is probably worth doing despite a certain amount of dependency on earlier sections of the AI course.

2. The course has been mercifully free from programming assignments: being capable of completion using pen and paper, a calculator (and on a couple of occasions a slide rule unused since 1973).  To conclude the NLP unit there were two optional programming problems, both of which could be tackled without programming. I did the second of the problems (recovering a message from a shredded version) using scissors and adhesive tape:

Moe and Chubb - Liberating Learning

These two short videos from the Hoover Institution will give you a sense of the line of argument advanced by Terry Moe and John Chubb, who are right-of-centre, union-hostile US academics with trenchantly positive views about the value of on-line learning, and about the need to make the same kinds of technology/labour substitution in education as has already taken place in large swathes of the rest of the economy.

Terry Moe

John Chubb

For more on/from both, go to Liberating Learning - Technology, Politics, and American Education.

Apples, screwdrivers and desks: a comparative review of three Stanford free online computer science courses

Guest Contribution by Gundega Dekena

[Update posted by Seb Schmoller on 12 July 2012. Note that Gundega now works for Udacity, the company that developed from the AI course. Read how she became part of the Udacity team on the Udacity blog.]

Gundega Dekena is a self taught Linux administrator and web programmer, based in Riga, Latvia. She has been studying all three of the October to December Stanford online computer science courses in parallel - Introduction to Artificial Intelligence (AI), Introduction to Machine Learning (ML), and Introduction to Databases (DB) - putting her in a good position to compare and contrast them. Gundega can contacted at gundega.dekena [AT] gmail.com, or through Google+.

Overview

Comparing these three courses feels a bit like comparing apples, screwdrivers and desks, yet I see a lot of students doing that, usually without much thought about the differences. So, this is my look (from the perspective of a student) atthe things that can be compared, and that can be learned from all three courses, for the benefit of the next batch of courses that is going to come from Stanford next year.

Tenth report from the Norvig/Thrun/Stanford/Know Labs Artificial Intelligence course

(Other posts tagged ai-course.)

No report this week. Instead, here is a Guest Contribution by Gundega Dekena, which provides a thorough comparison between Stanford's three current free mass online computer science courses.

Food for thought. Video recording of Q&A session between Sal Khan, Peter Norvig and Sebastian Thrun

There is plenty of food for thought and a great deal to identify with - from a very diverse set of angles - in yesterday's 45 minute "Google+ Hangout" discussion between Sal Khan, Peter Norvig and Sebastian Thrun. Examples include:

• the authenticity and hence superiority of unscripted, tentative explanations, with "low" production values;
• how lectures empower lecturers not students;
• data analysis as an "underpinning process" for real personalisation;
• why their is such a mismatch between the value that a university thinks its courses provide what students think they provide;
• the challenge of combining individual study with group interaction.

 

Ninth report from the Norvig/Thrun/Stanford/Know Labs Artificial Intelligence course

Screen shot of Filip Wasilewski's Chrome plug-in explained in paragraph 7 below.

(Other posts tagged ai-course.)

Here is my ninth participant's  report from the Stanford Introduction to Artificial Intelligence course.

1. I wrote last week that the units on Games, Game Theory, and Advanced Planning had been hard work; and that the associated homework had felt demanding and been very time-consuming. Securing an adequate mark on that homework despite too many  "stupid errors" means I probably learned more than I had realised. But I also know that I was answering some of the questions from the "stored fat" of knowledge I already had, rather than from what the course had been teaching me.

Eighth report from the Norvig/Thrun/Stanford/Know Labs Artificial Intelligence course

(Other posts tagged ai-course.)

Here is my eighth participant's report from the Stanford Introduction to Artificial Intelligence course.

Last week's report focused mainly on the midterm exam, and on a conversation with Sebastian Thrun. This report conments on the midterm exam and reflects on the way the course has run this week.

First, some comments on the midterm exam

1. According to information just received from Sebastian Thrun, 23k students passed the midterm, with 85% currently falling into the B+ range.

2. There was a surprising amount of post-exam discussion between students about the substance of the exam. There was some whingeing, but not much given the very large numbers on the course.  The interesting discussion fell into three categories:

How economic inequality harms societies - Richard Wilkinson's July 2011 TED talk

With thanks to Mick Fletcher

I am glad that Richard Wilkinson got to speak at TED Global, and below is the 16 minute talk in full. For more about his and Kate Pickett's influential book "The Spirit Level" go to The Equality Trust.

The shape of the next phase of online learning

Stephen Downes points to a 9 November 2011 Educause piece by Jarret Cummings and writes:

"I think the shape of the next phase of online learning is being defined: reliance on open educational resources, supported by some sort of automated, analytics based and competency based testing mechanism."

Yes.

Seventh report from the Norvig/Thrun/Stanford/Know Labs Artificial Intelligence course

(Other posts tagged ai-course.)

Substantial  changes made to A3 and small changes made to A5 and A7 below, 21 November 2011, and to introductory paragraph, 23 November 2011. [For visitors from the Aiqus discussion about student numbers, note that more light is shed on the "YouTube video counts question" - a distracting side-issue - in paragraph seven of report number two, 18 October 2011.]

Here is my seventh participant's report from the Stanford Introduction to Artificial Intelligence course. It is in three parts. A is the report proper. B picks up on a pre-arranged call from Sebastian Thrun. C lists further free CS courses that will be available from Stanford University in January 2012.

A - Report

1. A lighter week from the point of view of studying, because the last week saw less material presented, to allow students time to prepare for the midterm "examination", aka the midterm.