
Deeplearning.ai: Announcing New Deep Learning Courses on Coursera - npalli
https://medium.com/@andrewng/deeplearning-ai-announcing-new-deep-learning-courses-on-coursera-43af0a368116
======
seycombi
For those who are unfamiliar with coursera or interested in just the videos
(and NO certificate) you can enroll in "AUDIT" mode:

AUDIT MODE:
[http://image.ibb.co/iwm0xF/ng.png](http://image.ibb.co/iwm0xF/ng.png)

The deep-learning course consist of 5 subcourses:

[https://www.coursera.org/learn/neural-networks-deep-
learning](https://www.coursera.org/learn/neural-networks-deep-learning)

[https://www.coursera.org/learn/deep-neural-
network](https://www.coursera.org/learn/deep-neural-network)

[https://www.coursera.org/learn/machine-learning-
projects](https://www.coursera.org/learn/machine-learning-projects)

[https://www.coursera.org/learn/convolutional-neural-
networks](https://www.coursera.org/learn/convolutional-neural-networks)

[https://www.coursera.org/learn/nlp-sequence-
models](https://www.coursera.org/learn/nlp-sequence-models)

The deep-learning course is a different course than the prerequisite machine-
learning course:

[https://www.coursera.org/learn/machine-
learning](https://www.coursera.org/learn/machine-learning)

~~~
ryanschneider
BTW, if you want to audit, you need to search for each course individually (or
click seycombi's links above) and click the Enroll button there, there's no
Audit option if you click Enroll on the full Specialization.

~~~
jjuel
Thank you for pointing this out! Was looking for the way to just audit it and
could not figure it out.

------
sumitgt
I like this pricing model compared to udacity's new nanodegrees. This works
better for people who want to rush through the course as quickly as possible.
It essentially encourages faster completion.

You pay $49 per month and finish at your own pace. On Udacity you pay a fixed
price of approximately $800 per semester with a trial period of 7 days. Since
you are paying for the entire course upfront, you might realize after a few
weeks that you don't like it. On Coursera, you can stop anytime and you've
only paid $49 x number of months you tried.

~~~
lucasverra
Udacity has a 50% tuition back policy if you finish < 12 month (very
reasonable). I've finished a ND, and asked for my money back (still waiting
tough, its a 8 wks standard period )

~~~
zacharyz
That unfortunately doesn't apply to all their NDs. Some of their newer ones
(like the self driving car ND) doesn't offer any sort of tuition back.

------
carlosgg
Georgia Tech is also starting a few MOOCs on edX.org, starting 8/21/17, if
anyone is interested.

[https://www.edx.org/course/machine-learning-gtx-
cs7641x](https://www.edx.org/course/machine-learning-gtx-cs7641x)

[https://www.edx.org/course/statistical-modeling-
regression-a...](https://www.edx.org/course/statistical-modeling-regression-
analysis-gtx-isye6414x#)!

[https://www.edx.org/course/big-data-analytics-healthcare-
gtx...](https://www.edx.org/course/big-data-analytics-healthcare-gtx-
cse6250x#)!

[https://www.edx.org/course/database-systems-concepts-
design-...](https://www.edx.org/course/database-systems-concepts-design-gtx-
cs6400x#)!

------
m00x
If you take a Coursera course, be prepared for it being exactly like a
university class. About 45 minute of monologue per section, the odd quiz, then
2-3 exams.

From the 4 Coursera courses I've taken, I've gotten some good info, but I
learned nothing practical. Udacity on the other hand, has ~5-10 min videos,
frequent quizzes and practical projects.

~~~
2_listerine_pls
I dislike Udacity, they interrupt every minute to ask stupid non-useful
questions and some of their courses have very low quality.

~~~
tu7001
Except is Peter Norvig:)

~~~
2_listerine_pls
I wasn't referring to any particular course.

------
altonzheng
Any idea on how this compares to the deep learning course here:
[http://course.fast.ai/](http://course.fast.ai/)?

Very interested in taking a course, but there are so many offerings available.
I have high level ML understanding from classes I took in college, but wanted
to dive deeper into it.

~~~
plusepsilon
Ya it seems like just another deep learning course.

I can vouch for fast.ai though. They're the best if you're just starting.

~~~
mino
+1

fast.ai is probably the best MOOC I've ever followed. As its name says, it is
"for coders" and 100% applied. It is perfect for getting started, quickly.

Please read this blog post, in particular regarding the comment on _" Hacker
News contributors regularly give such awful advice on machine learning"_.

[http://www.fast.ai/2017/03/17/not-commoditized-no-
phd/](http://www.fast.ai/2017/03/17/not-commoditized-no-phd/)

and:

[http://www.fast.ai/2017/03/23/focus-on-
coding/](http://www.fast.ai/2017/03/23/focus-on-coding/)

------
bradleyjg
I'm glad these courses use python. I had a lot of trouble with Ng's machine
learning course because I was trying to learn MATLAB language, remember long
disused linear algebra, and trying understand the substance of the lessons all
at the same time.

~~~
jokoon
Yeah I have nothing against algebra or math, I like math, and I know some
algebra, but he was constantly using mathematical notation instead of
algorithms. It was not accessible.

I got into many arguments about how computer science is math and so on, but
machine learning is a set of techniques, there is no need for it to use math
when it's not really needed.

So I gave up. I did not even manage to properly understand his explanation of
linear regression, as I would have liked to implement my own. When I look
online it's a myriad of equations, and no pseudo code.

I love mathematics, but when I'm programming I really prefer to use data, and
not math.

~~~
inimino
ML is a set of techniques derived from math.

Instead of giving up you should push through that. Use what you know to get
familiar with what you don't, rather than asking for things to be made
accessible to you. Math is much older and bigger than computer science and
refusing to learn it is over-specialization.

~~~
jokoon
Well if it's derived from math, give the techniques, not the math.

I don't care if it's accessible for me or not, it seems the guy is saying ML
is the new electricity, lowering the bar won't only benefit me, but many other
people who know programming and don't benefit from knowing the math.

Just my opinion. Many people and hackers learn by practice, not by theory.

~~~
inimino
We need both electrical engineers and licensed electricians. If you want to be
an electrician, don't sign up for an engineering class taught by a pioneer in
the field of electricity and then complain that there is too much theory.
Coding bootcamps and vocational schools already exist to meet the needs of
those who only want to be practitioners.

Everyone learns by practice, but that applies to math just as well as
programming. If you don't practice it, you won't learn it.

~~~
jokoon
> Everyone learns by practice, but that applies to math just as well as
> programming. If you don't practice it, you won't learn it.

I don't see machine learning as a theoretical field of math, I see machine
learning as a set of tools.

To me computers are the tool you use to practice math, and you don't really
need to use mathematical notation anymore, unless you really dive into a very
abstract subject. ML consists of applied methods. I don't think people want to
learn the theory of machine learning, they just want to know the methods that
works now, and maybe dive into more complex stuff later.

------
binarymax
So awesome. I just completed Andrew's excellent 2011 Machine Learning coursera
course, and was looking where to go next. I am trying to go through the
courses on fast.ai, but I don't enjoy them nearly as much compared to Andrew's
teaching style and structure. Will be signing up for this!

------
dhawalhs
The courses are not yet live. Meanwhile, here is a list of 23 Deep Learning
online courses aggregated (aggregated by my company): [https://www.class-
central.com/report/deep-learning-online-co...](https://www.class-
central.com/report/deep-learning-online-courses/)

Also, link to Andrew Ng's original ML class:
[https://www.coursera.org/learn/machine-
learning](https://www.coursera.org/learn/machine-learning)

~~~
flor1s
For the first three courses the first week is already accessible.

------
js09
After having taken Udacity's ND, the only way I would consider taking this
course is if they go in-depth with the theory so that I can clear interviews
and work on projects from scratch. There's just too many resources for DL now.
It's getting ridiculous. Had Udacity gone in better details with their ND I
would glady have paid double for them.

Coursera does not having proper support systems like good quality forums/any
mentorship/project reviews. Although, been a while since I took a Coursera
specialization, would rate Udacity higher on that front even though their ND
was too basic (I can't even talk about what I did in a project clearly because
of so much lack of stuff).

Let's see how this specialization holds up.

------
bitL
Wonderful! Thank you Andrew!

Now alongside Udacity, another set of classes with certificates - does anyone
know if they hold any value to prospective employers? Last I've heard was that
a recent PhD in ML was a must.

~~~
eanzenberg
> does anyone know if they hold any value to prospective employers?

Sure they do. It's not a free pass but it is very very very helpful to have a
strong foundation in classic ML and statistics.

> Last I've heard was that a recent PhD in ML was a must.

Not really unless you are looking to jump into a pure research lab. Generally
you need publications in the field.

~~~
edanm
"Sure they do. It's not a free pass but it is very very very helpful to have a
strong foundation in classic ML and statistics."

I think the poster was asking specifically about the credentials of the
course, not taking the course itself. And I'd argue that it's probably _not_
that interesting to most prospective employers, since they'll care more about
things you've actually accomplished (example projects, etc).

------
BrianMingus
Latently (SUS17) also provides a more self-directed path to learning deep
learning focused exclusively on implementing research papers and conducting
original research:
[https://github.com/Latently/DeepLearningCertificate](https://github.com/Latently/DeepLearningCertificate)

~~~
pault
The wording in the linked GitHub page makes it sound like you are looking for
people that are already ML practitioners. Are you able to support developers
with no ML background that are interested in making a career change?

~~~
BrianMingus
Definitely, we help folks pick papers that are appropriate for their skill
level.

------
Dowwie
I hope that AI scientists will one day solve the problems with message forums.
Message forums aren't designed to engage this many people. A popular MOOC gets
tens of thousands of daily posts from students.

Maybe Andrew will make a practical class project out of trying to improve
mass-collaboration using his MOOC as the test subject?

------
mleonard
Will the content for the courses be released all at once? I'd like to complete
the 5 courses in approx 1 month.

~~~
flor1s
Seems like the first three courses are opening on August 15th (but you can
already preview the first week), the other two do not seem to have a start
date available yet.

------
nnd
So it appears, that you can still take this course for free, and you only get
a "digital certificate" of dubious value if you purchase the course. Am I
missing something here?

~~~
delta1
Is it not $49 / mo ?

[http://i.imgur.com/UNOvVMU.png](http://i.imgur.com/UNOvVMU.png)

~~~
NoPiece
You can audit the classes for free, which lets you watch the videos, and take
the quizzes but not submit them (which is annoying).

------
tmaly
What would be a good prerequisite for these courses?

~~~
nnd
From the FAQ on the course's page:

"Programming (expected): intermediate Python programming skills: work
effectively with loops, control flows, data structures, files, functions and
OO programming. Prior experience with PyData libraries is also recommended
(e.g. Numpy, Pandas, Matplotlib)Mathematics (recommended): Matrix vector
operations and notation.

Machine Learning (recommended): understand how to frame a machine learning
problem including how data is represented, how models are evaluated on the
task and against each other, and how to optimize model performance for the
best evaluation."

------
stablemap
Many weeks end with an interview that might be interesting independent of the
course -- the first is a long one with Hinton.

[https://www.coursera.org/learn/neural-networks-deep-
learning...](https://www.coursera.org/learn/neural-networks-deep-
learning/lecture/dcm5r/geoffrey-hinton-interview)

------
jonbarker
Transition to python is a great improvement! Took his previous course but the
MATLAB part of it was no fun and virtually guaranteed that my work would be
hard to implement in any real job setting. His advocacy of Octave probably
predated quite a few of the python libraries that have since arrived.

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wodenokoto
Is Andrew Ng still with Baidu? Thought it was curious that it uses tensorflow.

~~~
sumitgt
He left Baidu to start deeplearning.ai.

~~~
adfm
He also started Coursera, which brings us full circle :)

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nyxtom
This is really exciting to hear. Andrew is absolutely a fantastic teacher!

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smithsmith
This specialization contains 5 courses. Does this mean one has to pay 245
dollars(49 * 5) + 49 dollars for the first month.

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alistproducer2
I took his course up until the back propagation lesson and then lost interest.
Credit to him as a teacher though because the basic of ML are still with me. I
just didn't have any interest in going very deep with it.

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SoMisanthrope
Feels like marketing, not really a news story. Anyone else feel the same?

~~~
smithsmith
Exactly what is being marketed ?

~~~
SoMisanthrope
Coursera

