
Stanford Free Classes – A review from a Stanford Student - brudolph
http://pennyhacks.com/2011/12/28/stanford-free-classes-a-review-from-a-stanford-student/
======
CurtHagenlocher
It's been over twenty years since I finished college. Last year I did a
"certificate in quantitative finance" at UW which -- like the Stanford classes
-- were both online and seemingly aimed at working professionals. It's
interesting to compare these on three fronts:

1) The amount of rigor and work required for the Stanford classes was
significantly less than the UW classes. I spent as much as 10 hours per week
on the UW homework in addition to the 3-4 hours of video lectures. That's
against about an hour for the Stanford homework and another 60-90 minutes for
the lectures. I agree with the OP's description of the ML homework as starting
out at a decent level of difficulty and quickly becoming trivially easy.

2) I found the format of the Stanford lectures considerably easier to follow.
By making a canned recording, there's a huge amount of dead time which can
simply be edited out of the lecture. That plus the ability to watch at 1.5x
speed meant that I was rarely tempted to do something else at the same time as
watching the lecture -- something which frequently caused me trouble with the
UW classes.

3) The UW classes were something like $3500/course. If my employer hadn't been
willing to reimburse me, I wouldn't have taken them.

All-in-all, I think the Stanford classes are great experiments in which I'm
happy to participate. I'm planning to take five of them in Jan-Mar.

~~~
mikedmiked
Were you a quant before you took the UW classes?

~~~
CurtHagenlocher
Nope. My background is in engineering so the calculus wasn't an issue, but my
stats knowledge was really weak.

~~~
reagan83
I'm interested to know if earning that cert from UW allowed you to jump in to
the financial sector. I'm currently pursuing a similar path and would be
interested to hear about your experiences.

------
gfodor
There are two goals with learning ML:

\- Applying known ML algorithms to a real world task

\- Coming up with new ML algorithms and research

It turns out (ahem) that the first goal, applying ML, is not only much, much
higher in demand than the second goal, but is also much, much easier to teach
than the content required to pursue the second. This dichotomy is the reason
the split between CS229a and CS229 in both content and audience works so well.
The demand for CS229 is low and the rigor is high (so it should be priced
high), and the demand for CS229a is high and the rigor is low (so it should be
priced low.) The author signed up for the wrong class. I think Stanford is
teasing out subfields of CS that have this quality, and there sure are many.

~~~
brudolph
I'm sorry if I made it confusing, but it really isn't about whether I signed
up for 229 or 229a, the point is most of my classes for the coming term are
now under this new online format and it would be shame to see them lower their
standards to fit the public.

~~~
gfodor
It's a good point -- I guess we'll find out next semester if the difficulty
being below average had to do with the nature of the class itself (the a in
229a) or the audience it was being developed for. I hope, if the classes you
mention are listed under the same course number they always have, that the
difficulty won't be less than usual.

For the rest of us, what classes are these? Part of the reason an easier class
is better for the public is because there's just less time for working people.
If the difficulty/time commitment for the offered classes next semester are
substantially more than 229a I'd imagine you'll see a much higher dropout rate
not due to lack of ability but due to lack of time. It seems odd Stanford
would try to pack a "real" course into the online/public format, but at the
same time seems odd they'd dilute a "real" course for their undergraduates.

~~~
gcb
The easier assignments are easier because they now have morehints alongside.

this i guess is not to ease for lazy slobs (what you described :) but to ease
the demand for help on the staff.

The critic is that they overdid

------
chl
My impression was that the course was designed to give someone with little or
no background in machine learning a maximally useful amount of practically
relevant information given a multitude of constraints (ergo the focus on
Andrew Ng's favourite implementation tricks of the trade, learning curves &c.;
each of dozens of such nuggets having the potential to save days, weeks or
even months in real projects).

If that was indeed the goal, the endeavour should, in my opinion, be
considered an amazing success.

An easy way to make the assignments harder (and maybe more fulfilling), if you
have the time, might be to ignore much of the handholding (e.g. by porting
everything to a very different programming environment).

Ideally, online courses like that would be "infinite" and personalized, giving
everyone as much depth (and breadth!) as desired (with a "baseline"
approximately equal to the 2011 class) and taking existing knowledge into
account.

Eventually, we'll all get our Primer!

------
laibert
I'm not sure I understand how opening up classes to the online world would
would affect the coursework of Stanford students. If the author felt that
CS229a was not rigorous enough, he should have just taken CS229 whose problem
sets could double as full-time jobs.

Morever, a good chunk of stanford CS classes are already offered online
through SCPD (the professional development system) and as far as I know, the
structure of those classes remain unchanged.

------
jmares
I took CS229 at Stanford.

ml-class.org does a phenomenal job in equipping you with the practical
knowledge needed to apply the tools of machine learning to real problems.

There is no reason why learning to use these tools should be hard. If you want
a challenge, there are plenty of problems in the world amenable to solution
via machine learning, especially in today's data deluge.

If you want a deep mathematical appreciation of the algorithms and their
derivation, you should do CS229, not CS229a.

------
andrewparker
For those who tldr;

The author should have taken CS 229, but instead took CS 229a and was
disappointed. He then overgeneralizing from his 229a experience about the
future of Stanford CS education.

------
johnohara
Put down the pen. MIT, Stanford, et.al. have already done the math on this.

20,000 "certification" exams @ $99.00 each is not insignificant. It's just shy
of 40 full-time students @ $50,000 per year.

Heats a lot of buildings.

~~~
absconditus
Principles be damned, there is money to be made!

~~~
johnohara
I don't mean to imply that schools should be in it for the $$$. I get your
point. But costs are an issue. A big issue. And right now student tuitions
shoulder a large part of that burden.

Stanford's total enrollment is about 20,000 students. $35,000 per year =
$700,000,000.

Offer 16 new online courses which yields 20,000 students per course taking a
$99 final exam. $31,680,000. Less than 5% of annual tuition-based revenue.
That's a new library without hitting the endowment fund, underwriting existing
salaries, funding pension obligations, or adding a new facility dedicated
solely to the production of online educational content.

I think Leland and Jane Stanford would be proud to know that the memorial they
built to their son is today moving in the direction of educating millions
worldwide.

It's okay to "be strong and stay strong and while being of benefit to others."

~~~
absconditus
The problem is providing a questionable education and then selling a
meaningless certification to make money.

These classes are also highly vulnerable to cheating and you can be sure that
a large number of people will take advantage of this to pump up their resumes.

~~~
johnohara
I think that's why MITx plans to use a third-party for their certification
exams. Similiar to testing centers for standardized exams like the LSAT, GMAT,
GRE, etc.

------
juanre
I took the AI class, and I also saw a degradation of the difficulty. At the
beginning it was great. I even undusted my old 48SX, and had lots of fun: they
actually made me think. But some of the lessons towards the end were almost a
joke: I sure don't need to spend time applying a trivial formula back and
forth, as we did in the computer vision lessons (deriving it would have been a
slightly more interesting exercise.) I don't know if Stanford students were
paying for this, but I'd not be very happy if I had.

On the other hand, I am very happy that they are doing it, and I intend to
take as many as my time will allow. And I wish they'll figure out a way to
charge a small fee for having "Stanford" in the title in some manner, so that
they don't have to spend about half of the certificate of accomplishment
making sure that everybody understands that this is _not_ an actual Stanford
certificate.

------
acslater00
As a stanford CS grad myself, I basically concur. I took this class as a
refresher for things I learned back in school. It was perfect for that. But
the rigor and difficulty of the class was clearly tailored towards someone
like me, who wanted to watch lecture videos over dinner for a few hours a
week, rather than a full-time student.

I actually wasn't aware that the online class was being offered for credit in
the CS department until reading this. It surprises me that they're doing so.

~~~
erlis
I did the AI class and that was not the case. Stanford students were clearly
separated from the online students. We didn't get the same assignments
neither.

~~~
dlo
I took CS221 last quarter. So I can say that you got the same assignments and
exams; you just weren't required to do the programming assignments. While ml-
class was perhaps the third iteration of putting the machine learning class
online, ai-class was probably the first time someone tried to put CS221
online; the professors simply felt that they wouldn't be able to automate the
assignments in the time that they had. In fact, many of the YouTube lectures,
which many Stanford students seemed to prefer, were often not available to us
in time for the assignments and exams.

------
diiq
My degree is in Fine Art, and _I_ thought the class was pointlessly easy. Fix
the class in two easy steps:

Lecture live, record the lectures. EVERY speaker is more effective when they
have the feedback of their audience's faces.

Expect the members of the public to meet the class' standard, don't shrivel
the curriculum to match the public. An applied CS course that doesn't demand
programming is bizarre. Flunk everyone if you have to. Grades should perhaps
reflect understanding?

~~~
nessus42
I could not disagree more. I have an MIT degree, and I thought it was
remarkably refreshing to have the difficult made easy, rather than vice versa.
Not that I have huge complaints with my MIT education, but having taken some
classes at Harvard too, where the emphasis was sometimes different, I can
appreciate that there's often a great deal of value in a class that can draw
people in and make them interested, rather than send them fleeing in terror.
Personally, I thought that Prof. Ng's lectures where brilliant in their
ability to make difficult material completely approachable.

I do think that he occasionally would belabor the obvious, but for the
intended purpose of the class, I think that it is better that he erred on the
side of being too clear, rather than on the side of being opaque.

~~~
diiq
I agree totally. The first two sins of education are making simple things
complicated and making complicated things simple. Ng was clear, and that is
commendable. My concern was not based on how difficult he made the material he
presented _seem_. I was concerned that he did not present more difficult
material.

Vocabulary is very important. But in addition to knowing the meanings of
words, its important to know _why_ concepts are carved up the way they are.
Why divide the world into supervised and unsupervised --- what does carving at
that joint win us?

Getting people interested is what the first week is for. The other eight, I
feel, should try to satisfy the curiosity the first week sparked.

~~~
nessus42
_Vocabulary is very important. But in addition to knowing the meanings of
words, its important to know why concepts are carved up the way they are. Why
divide the world into supervised and unsupervised --- what does carving at
that joint win us?_

I'm not sure that I get you. Why we have both supervised and unsupervised
algorithms was made pretty clear to me in the class. And just what more
difficult material would you have liked to seen? The real Stanford class is
made more difficult largely by doing lots of difficult math proofs. I
emphatically disagree with any assertion that this free class should be so
math heavy. What would be the purpose of that for the intended audience? Sure,
such work would make fine extra credit, but making effective use of algorithms
rarely relies on on a ability to mathematically prove that they have the
properties that they do.

I think that a big final project, as is required in the real Stanford class,
on the other hand, would have a lot of utility for the intended audience. But
as that would be impossible to automatically grade, that's a non-starter.

~~~
diiq
I agree with you that doing proofs isn't the _most_ important thing --- though
I might not be so adamant about avoiding it.

My own experience with ML is so narrow, it's hard for me to say what else
should have made an appearance --- I made up the example that you rightly
called me on. I worked with a research group on a reinforcement-learning
system with a silly name, and we used a whole messy pile of linear algebra. I
guess I shouldn't have expected to recieve the same kind of grounding in all
the ML topics.

I agree that projects would make for a huge improvement. They are difficult,
but no more difficult than they need to be, and practical. You're right,
grading 20,000 of them would be madness. And maybe that's OK --- what's wrong
with assigning work that won't be graded?

(OK, there are lots of things wring with it, starting with motivating the
student to do the work, and ending with the lack of quality feedback. But even
_suggesting_ projects for self-directed students might be enough to get a
blog-ecosystem going.

I don't know much about pedagogy --- I'll talk to some people who do, and
maybe they'll dope-slap me into agreeing with you totally.)

But I don't think we disagree particularly -- math should only appear when
necessary to understanding. Easy things shouldn't be made difficult just for
the sake of some kind of scholastic masochism. But difficult things should be
attacked with vigor, and not nerfed for the sake of the audience.

~~~
nessus42
Now that I think about it, I do think that I heard somewhere that the free AI
class has a final project. IIRC, it's a "challenge" that is the same for every
student, and the solutions are ranked by how well they solve the problem
according to some metric that can be measured automatically. Kind of like how
Netflix set up a challenge like that with a million dollar prize, only in the
AI class there was no cash prize. (I hear that they did send out requests for
job interviews, though, as rewards.) This actually sounds like a great idea to
me. Topcoder for AI. I'm sure something similar could be devised for the
Machine Learning class. Now that I think about it, I'd actually be pretty
surprised if they don't do something like this for future versions of the
class.

I've heard some people complain that the programming assignments in the
Machine Learning class were too easy. A specific complaint is that they
provided all the equations and explication you needed right in the homework
statement rather than having to remember it from the lectures. Personally, I
find this approach to be the best way to learn. My favorite approach to
learning has always been "workbook" based, where the lessons and problems to
solve are in self-contained lessons. Give me material like that and I can
learn _anything_. There are entire classes at MIT that I did extremely well in
because they were workbook based. And I took Organic Chemistry and got an A+
in the first half of the class because it was workbook based. They thought I
was a genius. Then the second half of the class used the more traditional
approach of reading 100 pages a week of terribly boring and dense textbook. I
got a D- in that half. Fortunately, it averaged to a C and I passed the class,
but if the entire class had been workbook based, maybe I'd be doing something
great with Computational Chemistry at the moment.

Back to the actual ML class, I've only completed the first few programming
exercises as of yet, as I was also taking the database class, which actually
turned out to be a lot of work. I've heard that in the ML class, the
programming exercises become progressively spoon-fed, and ultimately not much
of a challenge. That's not good, if true. While I do think that all the
information you need should be at hand, you should still be given challenges
that make you think. All the thinking should not be done for you.

------
Jun8
He says:

"Stanford “free” classes aren’t free. Stanford students have to pay for them.
The fact that I’m paying for them doesn’t bother me, the fact that people who
aren’t paying for them have changed the class more than the ones who have,
does."

which does seem to be a forceful point. However, checking the FAQ
(<http://see.stanford.edu/see/faq.aspx#aboutq2>) we find that they are funded
completely from outside sources. So this guy didn't even bother to do some
basic Google checking.

~~~
sshrin
As far as I know, the Stanford online courses are NOT the same as the ones
listed on the SEE page.

They seem to be two different initiatives. I know for sure that the ones on
the SEE page are recorded video lectures from the actual live classes.

------
tlammens
According to the website <http://cs229a.stanford.edu/> there are class
meetings, according to the blogpost everything is done solitary?

Another difference with the course offered to the public is that there is an
open ended project.

If he really wanted a harder class, why not take CS229 and not CS229A...

If you want something to be harder, to get more out of something you should
pursue it yourself, not depend on others.

I see (online) education as a guide, not as the only source of input.
Selfstudy and initiative is the most important thing.

~~~
brudolph
Class meetings were optional (which I did attend) and only a fraction of the
students actually attended. I don't have a problem with cs229a being easier
than 229, but the thing is a lot of other classes have now turned to the
online format with no alternative (like 229 to 229a). Selfstudy is great, but
sometimes the best way to learn is from a structured class.

~~~
restofus
<i> Selfstudy is great, but sometimes the best way to learn is from a
structured class</i> Well lots of people might like to be treated like grown
ups and not like the structured classes and who knows they might even write a
letter asking for refund

~~~
overgryphon
I'm surprised you think being in a structured class is equivalent to being
treated like a child. What school did you go to that did this?

~~~
restofus
I do not think structured classes is equivalent to being treated like a child.

It was intended as a general comment that some people might not like it and
equate it like that based on his comment that only a fraction people actually
attended it and maybe if it was made compulsory they might not like it and
there is a probability that they will say that.

Just a point that what ever you do there will be some group that will not like
it .

------
lekanwang
I was MS CS at Stanford, and I agree with Ben's sentiment. I took CS221, and
checked out ai-class for fun, and knew several people taking the on-campus
version of CS221 this quarter. The short of it is that the online version is
essentially the same as the on-campus version, and both fail to adequately
prepare a student for further study in AI. It's great that Norvig and Thrun
are willing to present this survey class to the public, but not at the expense
of students who are actually in the classroom at Stanford and also footing the
bill for this grand experiment.

Yes, the class was a fun introduction to AI. But no, it did not offer a deep
and thorough theoretical foundation that I would expect from a Stanford class.

------
swalsh
I think there's a great opportunity to take online classes to the masses
without sacrificing the quality of a brick and mortar education. These classes
don't need to be offered free, just cheap. If they charged $10 for the whole
class (a steal really!) they'd make $1,000,000 a semester per class. That
should pay for the bandwidth, and teacher, and material. Scale that to less
niche classes, you have a real business! I'd personally pay $10 for a class,
even if it did not qualify for credit.

~~~
pitt1980
I think your math is a little off, 100K signed up for the AI class, only 40K
actually turned in a HW, guessing that less than 20K actually finished,

guessing none of the classes this spring will have anything close to that
enrollment

~~~
swalsh
You pay at the beginning. Whether you finish or not does not change how much
you make.

~~~
ShardPhoenix
If you had to pay up-front (even $10), they'd probably have gotten <1000
signups.

------
kenjackson
It's unclear to me if this guy didn't learn enough or if it just wasn't hard
enough. I do personally think that some courses are hard for the sake of being
hard. If he learned the material stated in the syllabus and it was easy, then
that's a really great thing and a tribute to the teaching.

~~~
DennisP
Some courses are hard for the sake of being hard, because they are intended to
filter out students who can't hack it. The degree is proof that you had the
intelligence and determination to earn it.

When you're not awarding a degree anyway, that consideration is irrelevant,
and the only requirement is to teach as clearly and effectively as you can.

------
Hyena
This post needs a comparison with CS229a prior to the online courses. Was the
course harder before online classes and then got significantly dumbed down? Or
was the course easy enough that it was a good candidate for the project?

~~~
brudolph
CS229a didn't exist prior to the online courses.

~~~
Hyena
Then it seems like there isn't so much a problem and the course is plausibly
performing its intended function. Obviously the course was designed by
Stanford to fill some role; unless you think that the course had a design flaw
only detectable once it got rolling, then the best assumption would be that
your expectations were wrong.

Of course, you could certainly have asked, as a Stanford student, what drove
the design of the course and how the professor actually felt about the
execution. That would have been an interesting follow up.

------
jacobquick
This kid's a...kid, I guess we shouldn't expect a long view from him. What he
sees as a slippery slope is a normal part of education that's hard to spot if
you're only in the system for four years.

Professors have been complaining for decades that students don't start their
classes with the basics already down. Making a video version of this class,
even one that only teaches the first half of the real class, means the
professors will start to expect the students know that part already and the
real class will expand to include even more advanced topics.

There's no danger of Stanford or Harvard or MIT or anyone else making things
easy on their undergrads.

------
restofus
tldr; The experts make it look impossible but the masters make it look easy
and actually teach you

Just ranting out here so feel free to ignore :-)

This is not really aimed at the author but towards the "elite" group. There
was another _elite_ commentator in one of the other thread who said he dropped
out of ML class because This course included gems such as "if you don't know
what a derivative is, that is fine" and he thought math was important in ML.
Before the ML class I could not even argue with these guys because I did not
know squat about AI and talking to these experts their advice was to take a
year off and learn math and then start learning AI which in my case was not
possible. Today after a couple of months of online classes I am actually using
ML in my daily work and its not magic that only the elite with deep profound
math knowledge can use. Another programmer who is working in khan academy
actually had a blog post about how he implemented ML by learning from Prof
Andrew's class now that is real world impact. I may be missing something but
can one of you experts please explain why you need deep math knowledge when
the professor who has been doing a lot of research in this field a lot more
than you does not think so ?. The professor in his classes keeps reassuring
that even after using it for so many years he has difficulty in the subject
but I'm guessing these _experts_ know it all :-).

This is the reason in my opinion even though wall street is full of smart
people they do not care about the rest of the population or the general masses
the attitude is we are smart and we can do what we want you guys are dumb and
deserve what you get and if someone outside of their elite group starts
talking their _language_ they do not like it.

On a similar note when you look at the people complaining about khan academy
most of them are these so called _smart_ people.

Let me talk about my background I have been working as a programmer for around
11 years , no math background though thought myself math by using Khan academy
and before my layoff (now am working on my own startup ) used to make 90K (in
a southern state).

So guys you are not the center of the world we are crashing into your
fraternity you are no longer the only experts who can talk about ML , the guys
at stanford are smarter than you and know what they are doing and FYI they
don't need you its the other way around. Another interesting thing is that
mostly the current students seem to agree with the author, If you are smart
you should probably take the effort to learn more rather than asking them to
tailor the classes to what you think matters . Also ask yourself this question
if you were the Professor what do you think is more satisfying teaching 40
full time students or 20000 who are in the field already and make more impact
in the field ?.

~~~
sausagefeet
This could just be an expectation problem. I think most of these free courses
have that 'Applied' stuck infront of them, ok, fine. But for my education I
want rigor. I don't want to just know how to use something, I want to know how
the guy who came up with it figured it out and I want to be bale to prove
things about it. Not having to know what a derivative is does not fit this. I
don't think it's a matter of the elite thinking only elite people can grok
something like ML, it's a matter of that they expect the dirty details and are
annoyed when they don't get it.

~~~
noblethrasher
I know ML and have a math degree; I don't see why you'd need to know what a
derivative is. If anything, I think exposure to ML and functional programming
before differential calculus could be beneficial since you'd better appreciate
that differentiation is just one special application (no pun intended) of the
concept of higher order functions.

~~~
flatline
If I recall, solving back propagation in multiple-layer perceptrons was an
unsolved problem for some time, and the solution relies pretty much solely on
partial differentiation. I don't know much about ML but things like neural
networks were pure mathematical constructs before they were CS topics. I agree
with the GP, though, you don't need to know the actual math for most of this
stuff.

~~~
disgruntledphd2
On the point regarding the necessary knowledge of maths for ML (or indeed
statistics which is the same material but a slightly different focus), I'm
conflicted.

Coming at it from my perspective (learned a lot of math in high school, forgot
most of it until I started a PhD), i would agree that a lot of the time, you
don't need to understand the mathematical underpinnings of this stuff. That
being said, as I've learned and remembered more of the math, my capability to
understand (and debug errors) of all of this has increased tremendously.

I do think, if you intend to use ML every day, then you need to commit to
understanding everything you use within a certain time frame of you beginning
to use it (ideally immediately but that's often not possible). Anyway,
derivatives are cool, and transform the way you look at the world, so you
should definitely learn some of those.

------
clavalle
There is no reason that there could not be a graduated difficulty for these
classes.

Example: The 'level 1' or 'core' videos and assignments can be a base and
offered for free and be of a similar duration and difficulty as the class
now...

'Level 2' would either replace or augment the 'level 1' and would be more
advanced and require some knowledge of pre-requisites and more 'synthesis' or
'critical' style assignments and less hand holding. Maybe they could charge
for access to this level...

'Level 3 etc' could go deeper into the topic and perhaps offer more
mathematical rigor or dive into more advanced topics or expose students to
related current research etc. The assignments could also be tougher and more
free form. Depending on how much human interaction is needed on the
assignments and whatnot, they could justify a much higher price...

I would be very interested in a program that had this kind of format.

It would allow for exploration without too much commitment but a deep dive on
topics that are interesting and perhaps a window into a community of people
exploring the same topics...

If I were paying Stanford level tuition for the class as it stands now, I'd be
a bit disappointed too.

~~~
jmilloy
> There is no reason that there could not be a graduated difficulty for these
> classes.

Of course there is. These classes are provided for free, yet require time and
money and effort. You've likely more than tripled the required resources to
produce the class.

~~~
politician
There is no reason that the most difficult grades must be open to the public
for free. Slap a paywall on it, a "With Student ID" bypass, and call it a day.

------
phodo
I took both, the AI and the ML class, and completed them to the end. All this
with a very demanding work schedule at a startup in the valley. I've also been
a PM for a large scale ML product that is in production and used by millions
of people. I say all this because the courses were perfectly geared to someone
like me. I thought the courses were excellent and pragmatic. (of course, like
anything, there can be improvements).

I think the issue here is what we are witnessing, aside from the awesomeness
of open courseware, is the evolution and continued maturity of Computer
Science as a discipline, as it takes more and more mathematical concepts into
its fold.

Machine Learning is growing up as a foundational pattern / algorithm that has
evolved from research to applied to basic-building-blocks-everyone-should-
know. Yes, it took the Valley and Stanford to liberate it (as a poster
indicates somewhere here), but that's ok. There is as much street cred in
understanding how to implement/design practical applications using ML as there
is in pushing the frontier on new ML mathematical techniques. That's how new
commercial innovation takes place. You need both sides of the equation; the
research and the practical. The course chose a balance that favored the
latter, because prior to this little existed. You can hear it in Prof. Andrew
Ng's videos... "this is big in the valley"..."you now know how to implement
XYZ"... "if you ask these questions on an ML product, you can save your tea,
time and money" (I'm paraphrasing).

Recall that at one point, logic/truth tables, sorting algorithms, graphs, etc.
all needed to be derived mathematically with their proofs. But then they
became axioms and codified as foundational building blocks of CS that just
work, enabling us to focus on the next step in the evolution. We don't
question or even think twice today when implementing "if (X && Y)".

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denzil_correa
Simplicity is the ultimate sophistication. -- Leonardo Da Vinci

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sakura_k
It's awesome that Stanford is offering free versions of their classes and
adapting the content to the needs of those students. If Stanford is teaching
the same classes with the same adaptations to their core CS students, I'd be
worried too. Full time on-campus students likely want (and deserve) different
adaptations. That's the really concerning thing I saw in the OP's post.

Perhaps this class happened to be taught at an easier-than-usual level. But,
if professors are torn between the demands of simultaneously serving dedicated
(paying or non-paying) students and casual students, the compromises won't
always be to the benefit of the dedicated.

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bgposter
I fully understand the author's concerns, but isn't it possible to just make
the classes more rigorous for those(at Stanford and online) with a better
CS/math background? I mean it was clear that prof. Ng was giving only part of
the story, presenting the intuition and skipping the math details/proofs. What
is wrong with adding the more rigorous material as optional content for the
online learners, and non-optional for the students at Stanford? I am
unfortunatelly only able to take these exciting classes online, but would like
to see more rigour too. I am willing to pay a modest fee for the privilege.

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16s
I signed-up for the crypto class next semester. I'm looking forward to it. I
code a bit of crypto and am interested to see what they'll cover. On a
separate note, I don't think the full-time Standford students need to be
concerned about the free Internet classes. Guys like me (state A&M college
degrees) who take online Standford classes won't devalue his Standford degree
one bit. Two totally different things as he is enrolled as a degree-seeking
Standford student and I (and those like me) are not.

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th0ma5
It is my understanding from various threads on Reddit that the AI class was
meant also to be something of a talent search, as those in the top percentile
got a message saying "send us your cv" or something like that.

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UK-Al05
I haven't taken it; so I don't know what the difference is. However you might
have to separate genuine concerns from threat of students elitism being taken
away.

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jeffreymcmanus
Watch out, this guy is about to write a letter.

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absconditus
This is not reddit.

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pg_bot
I have watched a few of the online lectures offered by Stanford and I can't
help but notice that the audio and video quality of the lectures is terrible.
The video will not track the lecturer, and the audio will randomly cut in and
out for long periods of time. (If I remember correctly, one lecture was
missing half its audio) Also, I am unsure of the class sizes at Stanford but
it seems like no one can arrive on time to a lecture.

~~~
tlammens
The online lectures you are talking about are the ones on youtube. They are
not the same as the ones used in ml-class.org. The latter ones are in a
completely different format.

It is not just a recording of a "normal" lecture...

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pg_bot
I am talking about the open courseware offered here
<http://openclassroom.stanford.edu/MainFolder/HomePage.php> I am unsure if
these are the same videos offered on youtube, however by taking a glance at
the website it looks like they are the exact same classes.

~~~
tlammens
If I understood correctly, those were a predecessor of the current lectures. I
had no problems with audio missing. (but yes quality could have been better)

