Top 10 Study Groups & Resources for Stanford’s Open Class on AI

We are all aware of the groundbreaking change that has struck academia, one of the Stanford’s first full courses is now available to the public for free. If you are not enrolled, click here. In a class of 140K+ students, one needs to find a good study group and resources, where they can post their questions and discuss AI concepts. Here is a list of top study groups which I could find in todays date.

1. Facebook Groups

Yes, this will be our top most source, since Facebook is the first thing that many of us open when connected to the internet. I could find the following groups for the open class on Facebook :

AI-class – “Introduction to Artificial Intelligence” online course
Strong Artificial Intelligence
ANU – ML and AI Stanford Course
Stanford Open Class (Thai)
IA-Stanford (Español)

2. Google Group & others

They are very much alive and serve as a nifty forum for academic discussions.

Google Group e-mail address: stanford-ai-class@googlegroups.com

Other AI forums for discussions are http://stanfordclass.com and http://aiqus.com/

3. Twitter Feeds

Official AI-Class:@aiclass
Unofficial AI-Class: @StanfordAIClass
Stanford professor @SebastianThrun
I don’t think he will actually reply to your tweets. Just saying!

Twitter feed with #aiclass can help you to find plenty more users who have enrolled for the open class.

4. Reddit

This is actually a pretty good service, which I always underestimated. You can find plenty of AI folks discussing stuff here.

5. Meetup

Use keywords like Stanford, AI, Open Class or Artificial Intelligence in the search.
For the folks in Bay Area check out >> http://ai-meetup.org/

6. YouTube

Here is a collection of useful videos explaining the concepts used in the AI Open Class by Prof. Peter Norvig and Prof. Sebastian Thrun. You can discuss your doubts in the comments and view lectures before they are visible on your AI-Class profile. There are plenty more sources like Khan Academy etc.

Also, if you have issues in watching videos on YouTube. Try AI-Class Subs Browser created by Eduard Ruzga

7. AI eBooks

I’m not sure which legal approach you want to pursue, but just grab a good AI book which can help you in solving problems. I found this link >> Click here

8. Stanford AI Class Notes on Google Docs

The AI community/class has collaborated & put together the following notes at the moment. Just go through the handout for a recapitulation of the lecture.

9. Google Hangouts

You can add yourself to this Stanford AI Circle, decide your open class G+ Hangout friends. Click here

Furthermore, you can add Prof. Peter Norvig to your group study circles. Yes, he’s on Google plus. BTW, add me as well.

10. Learning Python in less time

Google Code and The New Boston have some incredible tuts on Python. Just a matter of minutes…

If I have missed any of the good resources, feel free to leave a comment below. All the best to all the folks who have enrolled for the open class!

Hat tip to Linh Pham for sharing the latest updates on this topic via Google+

Update [9th November 2011] : Stanford AI Office Hours

You can submit questions on the current week’s material on the discussion page. Professor Thrun and Professor Norvig will answered the top questions and recorded their answers. Here we go…

Donald Knuth’s Annual Christmas Tree Lecture – Free Live Lecture

Stanford is broadcasting a free annual xmas lecture from Professor Donald Knuth on Bayesian trees and BDDs on Thursday Dec 8 at 6:30pm PST. It might be a great supplement to Professor Thrun’s discussion on Bayesian networks. Register Online! (Thanks to Linh Pham for sharing this update)

Tags: , , , , , , ,

9 Responses to “Top 10 Study Groups & Resources for Stanford’s Open Class on AI”

  1. Nima October 10, 2011 at 7:05 pm #

    Hello,
    we have created a forum for all of the stanford online classes at http://stanfordclass.com in first day we had more than 50 signups and this is our second day :)

  2. Daniel Bostwick October 10, 2011 at 9:57 pm #

    I just wanted to let you know that there’s an AI Class meetup in Boston, too!

    http://www.danielbostwick.com/aiclass-studygroup/

  3. Edgar Altamirano October 11, 2011 at 2:08 am #

    Tenemos un grupo en Facebook para hispanohablantes que toman el Curso de IA – Stanford.
    Compartimos y discutimos y nos apoyamos escribiendo en español.

    https://www.facebook.com/groups/IAStanford/

  4. Doug Johnson October 12, 2011 at 1:45 am #

    There’s a Wiki for notes from the ML Class.
    Maybe AI Class should consider creating one too?
    Eh? Eh?
    https://mlclassstudygroup.wikispaces.com

  5. Phil Hartfield October 12, 2011 at 7:54 am #

    For some really good lectures on Python, the Intro to Computer Science and Programming video’s on MIT’s OpenCourseWare is good:

    http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-00-introduction-to-computer-science-and-programming-fall-2008/video-lectures/lecture-1/

  6. Kamilo Cervantes October 17, 2011 at 1:47 am #

    There is also a IRC channel at freenode: #ai-class, #db-class and #ml-class

  7. erigena January 23, 2012 at 3:35 am #

    Stanford Course on consciousness
    Hi all,
    We are currently offering a course on “Neuroscience and experience” precisely as
    taught as an advanced seminar in Stanford. A sample lecture and outline of the course can be found at
    http://floyddogdesign.com/sean/newsyll2010.html
    Queries can be sent to
    universityofireland@gmail.com

    It does NOT use video, as we believe that slides + voiceover is a more economical means of learning. The method of assessment is essay submission at the end of the course

  8. erigena February 3, 2012 at 2:05 am #

    Stanford consciousness course will start as scheduled on Feb 7 2012

    There is an outline and sample lectures at

    http://floyddogdesign.com/sean/newsyll2010.html

    Please just follow the blog at

    http://consciousnesstalk.blogspot.com/

    if you want to register

    I will then supply passwords etc

    Please note;

    1.While this course is being taught precisely as at Stanford, it will not give Stanford credits
    2.Unlike the current batch of courses, it is NOT being delayed

    To repeat;

    It does NOT use video, as we believe that slides + voiceover is a more economical means of learning. The method of assessment is essay submission at the end of the course. As with all the other courses recently offered following the AI model, it is NOT accredited by Stanford, but taught exactly as in Stanford

    The detailed syllabus follows;

    Course description

     Subject area Cognitive:  science
     Position within subject area: Neuroscience and philosophy of mind

     Intended audience
     College students; intelligent and interested laypeople

     Course objectives

    When students have Completed this course, they will:

     -know the essentials of neuroscience, including the perhaps more veridical theories of neural function and communication that may currently be emerging from such areas as non- linear systems, quantum mechanics, and analysis of subthreshold neural oscillations

     - know the basic arguments in the philosophy of mind from Plato through Descartes, Berkeley, Hume, Kant, Levine and such popular putative contributions as that of Chalmers.

     - In the absence of any certain conclusions about the nature of subjective experience , which this course dues not claim to give, be able to evaluate the many current and future claims that will be presented to them proposing a direct link from neural fact to subjective experience

     Prerequisites for students

     Interest in the area; commitment to engage with others in dialogue

     Session by Session

     Week 1: Historical aspects: Plato, Aquinas, Descartes, Locke, Berkeley, Hume, Kant, Husserl, Levine; the advent of cognitive science.  Neurophysiological plausibility: assessment of conventional neural networks, the integrate and fire paradigm, and approaches built on subthreshold resonance. Introduction of the resonate and fire (RFNN)paradigm; vocabulary of non-linear systems to be used in the course. The Hilbert transform as superset of the Fourier transform; its applicability to brain function. Criteria for consequences for phenomenal experience.

     Week 2: RFNs continued. The encompassing context; how does this work relate to contemporary controversies exemplified by the Noe/Hurley/Block debate, and the notion of a neural correlate of conscious experience.

     Week 3:   Continuation of analysis of the work of RNF theorists like Izhekevich, Reinker and Doris. The interaction of spatial and temporal codes. Topographic maps that go point-to-point into higher-level maps and retinotopic mapping  from the retina to LGN, from there to V1, and in the other “V areas” up to IT.  How do these spatial maps interact with spectral codes of Karl Pribram?

     Week 4: Multimodal mapping. Spatial location and information integration. What other binding mechanisms are there, for example in Martin’s LIMSI work? ;Filling ; mechanisms and change blindness.

     Week 5  The contrastive approach in consciousness studies. Axonal versus dendritic communication. The FM radio analogy pioneered by Izhekevich, Doris  and Freeman. Meaning as AM  in the work of Freeman

     Week 6:  Other theories of consciousness; conscious inessentialism in Lashley and Jackendoff. Fodor versus Descartes on modularity. Freeman, Suppes; consciousness as a sample.

     Week 7:   Edelman, involving the dynamic core hypothesis. Llinas and the thalamocortical system. Pellionisz and Llinas on tensors in the work popularized by Churchland

     Week 8: Recapitualtion of historical aspects and summary.. What theory, if any, will prevail? What seem to be the relevant criteria?

     Weeks 9 and 10 Student presentations.

     Methods of Instruction While the instructor will prepare a detailed presentation for each topic, the students will be encouraged to debate the topics vigorously throughthe internet , and work together to give presentations

     Credit requirements and course grade 50% end of session examination50% project work (to be finalised)

     Background Reading
     Barlow H. B. (1972) Single
    Neurons and Sensation: A neuron doctrine for perceptual psychology. Perception. Perception 1, 371-394.
     Biebel, U.W., Langner, G., 1997. Evidence for “pitch neurons” in the auditory midbrain of chinchillas. In: Syka, J. (Ed.), Acoustic Signal Processing in the Central Auditory System. Plenum Press, New York
     Braun, M., 2000. Inferior colliculus as candidate for pitch extraction: multiple support from statistics of bilateral spontaneous otoacoustic emissions. Hear. Res. 145, 130-140.
     Braun, M., 1999. Auditory midbrain laminar structure appears adapted to f 0 extraction: further evidence and implications of the double critical bandwidth.
     Hear. Res. 129, 71-82.
     J. C. Eccles (1957). The Physiology of Nerve Cells. Academic Press, New York, 1957
     G Callewaert, J Eilers, and A Konnerth Axonal calcium entry during fast ‘sodium’ action potentials in rat cerebellar Purkinje neurones J Physiol (Lond) 1996 495: 641-647
     Georgopoulos, A., Kalaska, J., Caminiti, R., & Massey, J. (1982). On the relations between the directionof two-dimensional arm movements and cell discharge in primate motor cortex. Journal ofNeuroscience, 2(11), 1527-1537.
     Hubel and Wiesel (1959) Receptive fields of single neurons in the cat’s striate cortex
     Hutcheon, B. and Yarom, Y. “Resonance, oscillation, and the intrinsic frequency preferences of neurons” Trends Neurosci. 2000 May; 23(5): 216-22
     Izhikevich (2002) “Resonance and selective communication via bursts in neurons having subthreshold oscillations” Biosystems 67(2002) 95-102
     Langner, G., Schreiner, C.E., Biebel, U.W., 1998. Functional implications of frequency and periodicity coding in auditory midbrain. In: Palmer, A.R., Rees, A.,
     Summerfield, A.Q., Meddis, R. (Eds.), Psychophysical and Physiological Advances in Hearing.
     Whurr, London, pp. 277-285. Langner, G., Schreiner, C.E. and Merzenich, M.M. (1987) Covariation of latency and temporal resolution in the inferior colliculus of the cat. Hear. Res. 31, 197-201
     McCulloch, W. and Pitts, W. (1943). A logical calculus of the ideas immanent in nervous activity. Bulletin of Mathematical Biophysics, 7:115 – 133.
     Rees, A. and Sarbaz, A. (1997) The influence of intrinsic oscillations on the encoding of amplitude modulation by neurons in the inferior colliculus. In: J. Syka (Ed.), Acoustic Signal Processing in the Central Auditory System, Plenum Press, New York, pp. 239-252
     O Nuallain, Sean (2003) The Search for Mind; third edition. Exeter: England
     Pribram, K. (1991) Brain and Perception: holonomy and structure in figural processing. N.J. : Lawrence Erlbaum
     Reinker, S, E. Puil, and R.M. Miura (2004) “Membrane Resonance and Stochastic resonance modulate firing patterns of Thalamocortical neurons: Journal of computational Neuroscience 16 (1): 15-25, January-February, 2004
     Rock, I. (1983) The logic of perception. Cambridge, Mass: MIT Press
     Rudolph, M. and A. Destexhe (2001) “Do neocortical pyramidal neurons display stochastic resonance?” Journal of computational neuroscience 11,19-42
     DeSchutter, E. and Bower, J.M. (1993) Parallel fiber inputs gate the Purkinje cell response to ascending branch synaptic inputs. Soc. Neurosci. Abst. 19:1588.
     Sherrington CS. 1906. Integrated Action of the Nervous System. Cambridge University Press: Cambridge, UK
     Wu, M, C-F Hsiao, and S.C. Chandler (2001) “Membrane resonance and subthreshold membrane oscillations in Mesencephalic V Neurons: Participants in Burst Generation The Journal of Neuroscience, June 1, 2001, 21(11):3729-3739

Leave a Reply