
CS188 Intro to AI – Course Materials - BucketSort
http://ai.berkeley.edu/lecture_videos.html
======
joelg
Lecture videos for MIT's 6.034 (Artificial Intelligence) are also freely
available online:

[http://ocw.mit.edu/courses/electrical-engineering-and-
comput...](http://ocw.mit.edu/courses/electrical-engineering-and-computer-
science/6-034-artificial-intelligence-fall-2010/lecture-videos/)

6.034 emphasizes intuition over math, which might make it an easier
alternative for those without a stats or calculus background. Also Prof.
Winston is a phenomenal speaker.

~~~
icpmacdo
Lecture 15 from it is my favourite lecture I have ever watched online. Stick
with it until the end. And I totally agree Prof. Winston is an incredible
speaker.

[https://www.youtube.com/watch?v=sh3EPjhhd40](https://www.youtube.com/watch?v=sh3EPjhhd40)

~~~
mad44
Applying Winston's Star method on itself. Meta-star if you wish:

Symbol: star is the symbol of this method, it makes the idea visual and
memorable

Slogan: With these 5-star tips, you can 5x the impact of your good ideas

Surprise: You can achieve fame and impact by packaging your ideas better
following these simple presentation tips

Salient: Having a good presentation is as important as having good ideas/work

Story: These presentation tips are told by a top MIT prof to his undergraduate
AI class as secrets to career success

~~~
phodo
Lecture was phenomenal - thanks for suggesting it. Re: meta-star, I thought
the surprise was providing a career/success framework in an AI course. That
made it stick out. It was a nice "reveal".

~~~
icpmacdo
It really blew my mind when I first watched it. A fair amount of the course
went over my head so I had been randomly skipping around the series but inted
to go back chronologically

------
brianchu
This is a popular undergrad course at Berkeley. To be clear, it's mostly
focused on GOFAI (good old fashioned AI) - things like tree/graph search,
constraint satisfaction, logic, some basic graphical models, and a bit of
RL/ML at the end. It's useful to know about (because these things sometimes
show up as components of ML systems), but also fairly disjoint from the core
machine learning field that people are undoubtedly interested in.

~~~
zerr
That's also called Symbolic AI I believe. And there are some modern
developments in this branch. I personally enjoy this more than ML - too much
statistics for me - I tend to prefer a and b over 0.00789 and 1.4500965 :)

------
pkill17
A more recent iteration of this course from Spring 2015 with better quality
all around and the entire playlist of lectures:
[https://www.youtube.com/playlist?list=PL-XXv-
cvA_iA4YSaTMfF_...](https://www.youtube.com/playlist?list=PL-XXv-
cvA_iA4YSaTMfF_K_wvrKAY2H8u)

------
Breefield
This is an awesome resource, and exactly what I've been wanting!

I've been thinking about AI a lot lately, but I skipped college and went
straight into startups, so all my knowledge on the subject is from reading
less focused materials. Reminds me of Stanford's iOS dev resources from 4-5
years ago.

[EDIT] oh god math, why can I program but I can't math unless it's
trigonometry or vectors/calculus, visually applied math makes sense, otherwise
I'm so lost.

~~~
Cyph0n
> Reminds me of Stanford's iOS dev resources from 4-5 years ago.

Believe it or not, they still release a course every year (or semester, not
sure). The latest one covers iOS 9 using Swift. You can find them all on
iTunes U.

~~~
ChicagoBoy11
Paul Hegarty is such a fantastic instructor of that class... its is hands-down
THE resource to get started with iOS dev.

------
skhavari
A little nicer format - with edited videos (1st half), HW and programming
assignments, on edx:
[https://courses.edx.org/courses/BerkeleyX/CS188x_1/1T2013/in...](https://courses.edx.org/courses/BerkeleyX/CS188x_1/1T2013/info)

~~~
dean
Same course, but this link goes to the course overview page:
[https://www.edx.org/course/artificial-intelligence-uc-
berkel...](https://www.edx.org/course/artificial-intelligence-uc-berkeleyx-
cs188-1x)

Your link took me to an internal page.

------
fitzwatermellow
After finishing CS188, if you want to "go deeper", check out Berkeley's CS
294: Deep Reinforcement Learning, Fall 2015:

[http://rll.berkeley.edu/deeprlcourse/](http://rll.berkeley.edu/deeprlcourse/)

And you should be well on your way to being able to read and comprehend the
Google DeepMind papers posted on Arxiv ;)

~~~
optimali
Any idea why only 2 out of (seemingly) 4 assignments are posted? Are the other
assignments available anywhere?

------
krat0sprakhar
Other AI courses - [https://github.com/prakhar1989/awesome-courses#artificial-
in...](https://github.com/prakhar1989/awesome-courses#artificial-intelligence)

------
kenrick95
The first half of this course was previously offered at edx during Fall 2012,
Spring 2013, and most recently Spring 2015 (CMIIW). Back in 2013, when I just
graduated from high school and waiting for uni to start, I enrolled myself in
the Spring 2013 offering and it was a great course. Just note that this is a
quite a heavy course to take (there are lectures, homework, and projects); but
the project is really fun, you're to make Pac-man more intelligent in its
environment :)

From the knowledge gained from the MOOC, later on I made this game
[http://kenrick95.github.io/c4/demo/](http://kenrick95.github.io/c4/demo/)
which I implemented a simple AI as the opponent, which is a minimax agent. It
is not perfect, but it is good enough for me :)

------
personjerry
I took a later version of this class and I couldn't get into it. I thought I'd
love AI, as the idea is extremely appealing to me, but it seemed to be mostly
probability and formulaic work. Which is fine, if that's the way AI is, but I
would've preferred if they'd explained why the algorithms chosen are what they
are, and how we got to them--and what other methods have been explored.

As it is, the class just skims over a variety of techniques and ways to
implement them, lacking depth (such as what disadvantages and advantages there
are in practice or where they have been used in the real world).

~~~
jxy
This sounds like exactly what it should be as an intro-to-* course. You are
given the names and terminologies and the ability (Math! Yes, you do need it.)
and freedom to explore any deeper materials on your own.

~~~
personjerry
Hmm, I always thought that this style of teaching was a good way to lose a lot
of students' interest. A math professor I had was insistent on showing the
thinking that led to a proof, which not only made it easier to remember, but
also made the study vastly more interesting and engaging. From what I can
gather, his technique has made him quite a popular professor amongst the
students at the University of Waterloo, so I suspect this is quite an
effective alternate style of "intro" course, although I recognize that it
limits the breadth of material.

------
IanDrake
They can code AI, but can't run their sound through audacity to clean it up?
That's a bummer.

------
NamTaf
I did the first half of this as an edX course (CS188.1x) and it covered up to
and including the reinforcement learning content. It was really fascinating
and enjoyable - definitely one of my favourite courses that I've done.

------
kriro
This is one of my favorite AI courses. It basically takes you through a good
chunk of Artificial Intelligence: A Modern Approach (warning, this is mostly
the basics and not fancy machine learning) in a very practical way
(implementing things for a pac-man game).

I tough a similar course for a while and they are doing a much better job than
I did.

------
rosstex
I just took this course at Berkeley this past semester. The latest materials
should be available on EdX for the public!

~~~
akvar
If possible, can you post a link to the same? The material on edX is currently
of the Fall 2013 offering. Not that it's an issue but it would be nice to be
more current.

------
HammadB
If you watch the lectures, I highly recommend the projects, some of the best
projects in a CS class I've had.

------
whatok
Related: how do people normally access edX on an iPad? Am I correct that there
is no dedicated app?

~~~
odesian
I believe this is the app:
[https://itunes.apple.com/us/app/edx/id945480667?mt=8#](https://itunes.apple.com/us/app/edx/id945480667?mt=8#)

iOS 8.0 and greater

------
neivin
Just signed up for the same thing on edX! Still going through the math review
though.

------
wtf_is_frp
Your thoughts on CS188 vs Udacity's Intro to AI?

~~~
skhavari
The Berkeley one is a bit slower and it has a statistics/probability
refresher. I found it much easier to follow at 1.5x speed. I'd recommend the
Udacity one if your stats/probability knowledge is fresh or if you're re-
learning the topics.

------
Philipp__
Amazing! Only if I had more free time.

