Intro to Artificial Intelligence

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This course will introduce you to the basics of AI.

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1 posts • 118 mentions • top 20 shown below

r/RedditDayOf • post
9 points • PhillipBrandon
Intro to Artificial Intelligence - a free four month course on Udacity
r/artificial • comment
8 points • river-wind

That's Sebastian Thrun teaching, the guy who started the Google self-driving car project. He does videos like this for, which he founded originally to give free AI lessons via the internet. This seems to be from the original Intro to AI class, taught by Thrun and Peter Norvig; unit 9, video 35, as suggested by the video name above.

The entire lecture series, along with quizes and programming exercises, is available for free here:

r/cscareerquestions • post
3 points • FireBoilol
How do I get from newbie to working in A.I?

Hey there everyone.

Artificial Intelligence has always been a fascination of mine. I was one of those kids that thought cleverbot was the shit and made my own rudimentary chatbot. I used to play around with bots for video games that people had made as well.

I'm currently studying IT and will be going for a CS degree next year. I have messed around with the barebones of C#, and dabbled in python, but for practical purposes I am completely new to programming beyond basic variables.

I have a year of free time more or less, and with A.I becoming more relevant and more of an established field alongside my going to uni next year and such it seems like the perfect opportunity to start.

So, which language is good for A.I and are there any specific resources a complete noob can use for that language(s) or A.I in general?

I posted to learnprogramming already without much response.

Also, is any good?

Thanks in advance.

r/UWMadison • post
39 points • roumenguha
CS 540 (Intro to AI) Summer 2017 Petition

As some of you know, CS 540 (Introduction to Artificial Intelligence) this summer is not being taught by Prof. Dyer or Prof. Shavlik as both retired this last semester.

The class, as it is right now, doesn't seem to require any programming. The class seems more like a sociology, history or psychology class than a computer science class. I feel cheated because this was the reason I took classes over the summer at all. My emails have been "heard" and my feedback has been "noted" but I haven't heard of any action being taken yet. We have just 8 lectures left in the class, some of which have to be used for presentations and exams, so really only about 6 periods of lecture-time left. Changes are time-critical.

I've been trying to contact the CS department to try and get them to intervene and make some improvements, but it's not been easy so far. I think it would help if I had more people who feel the same way also send emails (and I know there are more than a few in the class who do). I'm speaking with them again on Monday, so I have the weekend to get enough responses to show that I'm not the only one dissatisfied with the class.

I made a Google Form survey to get some numbers to back me up. The first half is required but easy to answer. The second half is optional but long-answer. If you have changes you'd like me to make, I can do so. And if you want, I can post the results too.

Please send this to friends you have in the class.

Here's the link to the Google Form:

Edit: I forgot to mention this earlier, but some classmates of mine stayed back in Madison over the summer just for this class alone. According to this, they paid 4.1k to take this class. That, to me, is the worst part.

Edit 2: as someone pointed out to me, it doesn't need to have programming to be a CS course. I think that's true, but there should be some discussion of the algorithms, data structures and other such common and technical things that we should me learning.

Edit 3: 22 responses! That's almost 30% of the class! Keep it coming!

Edit 4: 36 responses! Slightly more than 10% of the class has dropped, and the survey is at around a 50% response rate. Here are the results:

You all asked to be kept updated, so here it is.

I spoke to the CS adviser on Monday morning, and she took my points and directed me to Prof Remzi.

Professor Remzi, who is an associate chair of the CS department, has expressed interest in helping out our class. I sent him an email asking if we could meet sometime to talk about the class (because he wasn't present at the meeting). I also sent him the document outlining some of the issues we're having with this class, and some possible solutions here:

I also contacted one of my friends who has TAed CS 540 twice in the past for 2 different professors. He's offered to sit in on our class and report the differences to the CS department, in case they don't believe us. In the mean time, he's suggested we do the AI course on Udacity so that we learn the necessary material.

If you have anything to add, just let me know. If you'd like to be present for the next meeting, also let me know.

Edit 5: Another update. Prof Remzi emailed me last night, around 00:30am (Tuesday), saying he had to leave town suddenly, so he had to cancel our meeting today. He referred me to Prof Michael Swift instead.

Prof Swift has been busy today with meetings, and so he'd like to take the time to read the emails I've sent the CS department, as well as ask our professor about her course plan. Basically get a better perspective. I've asked for a meeting today, given how urgent this is, but now it's up to him. I've also sent him an email mentioning that our midterm is this Thursday.

He hasn't gotten back to me in writing (my emails to him haven't been replied to yet) but all the stuff I said he said is from a phone conversation.

Edit 6: One more update (Tuesday). I spoke to Prof Swift. He's forwarded the survey results and the list of issues and recommendations (attached above) to other professors and is meeting to see how best to make changes.

He's promised to keep me updated, and it turns out he's been reading this post. fingers crossed

Edit 7: No news yet, but our midterm is today (Thursday). Here is the review sheet of topics that will be on the exam:

Edit 8: Midterm exam came and went (I think I failed), it covered no algorithms, but it did ask me to name some contributors to the field of AI. The department has looked into it and seems satisfied with the course content as it is right now. As it stands, they see no reason to take action. But I've got a few more ideas, so stay tuned.

Edit 9: Spoke to Prof Remzi today (Monday, July 24th) and he basically said that there's nothing the CS department can do now, and to try to maximize this time anyway, maybe by finding some projects to do ourselves. In that spirit, here are some resources for you to help yourselves:

Other professors at UW-Madison:

Jerry Zhu's CS 540:

Jude Shavlik's CS 540:

Chuck Dyer's CS 540:

Massive open online courses (MOOCs):

edX's CSMM.101x:

Udacity's CS 271:

MIT OCW's 6.034:

If anyone wants to start a study group to help us motivate each other, I'm in.

Prof Remzi also might be looking for volunteers to help start a feedback process for early on in courses, to help steer them in the right direction to ensure this doesn't happen again.

I highly encourage you to send some emails yourself! I can't do this alone. Especially grad students. (Please don't bother Prof Dyer right now because he has personal matters to attend to.)

Nikki Lemmon (Advisor) - [email protected]

Guri Sohi (Chair) - [email protected]

Remzi Arpaci-Dusseau (Associate Chair) - [email protected]

AnHai Doan (Associate Chair) - [email protected]

Michael Swift (Associate Chair) - [email protected]

r/artificial • comment
2 points • Amazon-SageMaker

I really liked this course and have found concepts I learned in it coming up in other areas I am exploring.

r/artificial • post
5 points • CluelessGoals
Has anyone took these courses on Udacity/Edx to learn AI? Which one would you recommend?


r/artificial • comment
3 points • pubg_ranked

r/computerscience • comment
1 points • HO-COOH This is the one my class is using for additional resource and I think it's pretty high quality.

r/compsci • comment
2 points • MeoMao555

I haven't taken the specific online course, but Intro to AI at Udacity looks like a decent start. Norvig & Thrun are both star professors.

As for books, AI Modern Approach (by Norvig & Russell) is a decent one (I have an earlier edition, can recommend).

r/OMSCS • comment
2 points • gcoladon

Ahh I just thought of a good tip. Go through this class as fast as you can, before the course officially starts: There's a big overlap between that MOOC and 6601.

r/ArtificialInteligence • comment
1 points • TomasMSM


This is the way to go. Do this free online course through Udacity.

And then dive deeper in the topics you liked the most.

Best of luck.

r/ArtificialInteligence • comment
1 points • cmoradiaz

I'm agree with EdX, Udacity , Udemy (have some free material) and microsoft school for free

Hope helps

r/robotics • comment
1 points • cr0sh

I took the "AI for Robotics" class, back when it was first called something like "CS373 - How to Build Your Own Self-Driving Car"; that was, IIRC, early 2012.

Prior to that, I had taken the proto-MOOCs that begat Udacity and Coursera - the Stanford sponsored "AI Class" and "ML Class" respectively. I had to drop out of the AI Class offering (broke my heart to do so), but I stayed in the ML Class and completed it.

When Udacity started up, Thrun wasn't able to release the material for AI Class as a course for some reason (I don't know why - I suspect licensing or similar issues held it up); so instead, he came up with the CS373 course (which I jumped on immediately - beta testing be damned!). In time, though, Udacity did release the AI Class as a course:

I don't know if it changed from the original course, though.

ML Class was taught by Andrew Ng - and I found it exceedingly and thoroughly entertaining and enlightening. It stayed pretty much as-is as a Coursera offering:

When ML Class was running, one of the students learned enough from it (and was inspired by the material presented) to make his own version (albeit at a smaller scale) of the old CMU ALVINN self-driving vehicle:

Today, it's kinda "old hat" in a way - but back then, in late 2011 (really not that long back) it was a major coup. It really showed the practical side of what we were learning.

Between all of these courses, I've come away with a greater knowledge base and appreciation of the complexity for AI/ML - and there's still a ton I need more education on, if I can find the time to sink into it (I badly need to learn basic calculus; primarily derivatives and integrals - along with getting a solid foundation in probabilities and stats).

For the OP - something to keep in mind is if you really want this to be your career. Is it something you think you could do day in and day out, and not get bored by it (in an employment fashion)? Because there's a ton you can do on your own in robotics, at a hobby level, and pursue something else for your career.

Unless your plan is to be a researcher, founder, or similar to advance the field; you don't want to find yourself deep in debt and still having to work a job which doesn't exercise those skills (that's kinda the problem I have; I took all those courses, but none of my employers have wanted to let me use those skills - probably a good thing, as I don't really have the level of education I need to possible make a good contribution, but at the same time its a bit frustrating - even so, it's helpful from a hobbyist perspective I guess).

You might also find yourself with all those skills, but scant offerings for employment; there are tons of people out there with advanced degrees who go to work coding e-commerce websites in WordPress. You don't want that to happen to you if that isn't your goal.

You might instead want to approach it simply for learning's sake; get the degrees and level of knowledge and understanding you want, and don't worry about how it fits in to an employment strategy. Let that part happen naturally after you've completed your education, so to speak.

r/learnprogramming • comment
1 points • swigganicks

Probably AI -> machine learning -> Deep Learning

Intro to AI

Intro to ML

Intro to DL

They're not necessarily sequential things and sort of build off each other both ways i.e. you use deep learning for advanced AI but you don't want to do DL without knowing ML first which is similar to basic AI etc.

r/Udacity • comment
1 points • elias_ronin

Computer Vision is a part of Neural Networks.

You've learned Algorithms from the ML course. If you know everything about NN AND if you know PyTorch then it's not for you. But if you don't then give it a try.

There is not much on this course about Computer Vision but you need good fundamentals in order to go for it. PyTorch is more pythonic (for me) than TensorFlow, so you'll need it.

Now I'm in the Intel Edge scholarship and it's all about Computer Vision. It's easy (let's say!) for me because I had good fundamentals.

My advice is to do this course and then take some other from the Free courses that are available on Udacity, like:

r/artificial • comment
1 points • CyberByte

Not interactive, but AIMA has Python Code.

I'm not sure anymore if it uses Python, but Udacity offers a free Intro to AI course by Sebastian Thrun and AIMA co-author Peter Norvig.

Udacity also has a free AI course by Georgia Tech that definitely uses Python.

You can also check out /r/artificial's wiki for Getting Started with AI.

r/ArtificialInteligence • comment
1 points • HelenKandelaki

I think it's a great idea to start thinking about leveraging AI for your business from the beginning.

Here are some resources that can help you get familiar with AI:

  • McKinsey’s guide to AI for executives: in simple language explains AI, machine learning and deep learning.
  • AI for Everyone course by Andrew Ng, the co-creator of Coursera and a founding lead of Google Brain.
  • Google AI: tech giants’ artificial intelligence research and development branch that provides stories, courses and publications on AI and its advances.
  • Accenture’s AI Explained guide for executives: aims to provide a comprehensive overview of AI capabilities and implications.
  • Udacity’s Intro to Artificial Intelligence course: teaches the fundamentals of AI and its potential applications.

I work for an AI consulting firm and we've recently started a blog that aims to educate and demystify AI and its implications for business owners. Our most recent post actually talks about ways to successfully integrate AI into a business.

r/OMSCS • comment
1 points • fluff12321

Sure, here's a few I'd recommend that were a good combination of fun/interesting & well explained:

Intro to Python: I took several short/interactive tutorials to get the basics down: - -

Introductory CS: - -

AI: -

Machine Learning: -

Algorithms: - -

More intermediate/advanced, but really excellent:

After the introductory stuff, you can take AI, ML, or Algorithms in any order you find appealing. Enjoy!

r/OMSCS • comment
2 points • kj02156

For self path study, I prefer to watch free lecture videos on youtube / Udacity and do some projects.

If you want to refresh data structure, I recommend you to try UCBerkeley CS61B, one of the famous class there

It's open for everyone, I have been working on their course work/ projects since last month. Very good explanation on the topics, also allow us submit the homework and projects for autograding.




Intro to Machine Learning: (beginner to intermediate level)

Intro to AI:

r/learnprogramming • comment
1 points • beyond-antares

This is a popular topic but I don't often see a comprehensive answer. I'm by no means an expert and currently learning myself.

There's two key stepping stones before jumping into AI, that being learning Python and data science. Python has wide support and a host of libraries reflecting the latest research on AI development.

There is also R, Octave and Java depending on the libraries you're looking to use, but they aren't nearly as popular as python. Note that if you want to embed your AI scripts into web apps or apps, then you'll need to learn javascript and java respectively.

The best resources for Python are

  1. Automate the Boring stuff - Al Sweigert

  2. Hitch hikers guide to Python

  3. Dive into python

Great resources can be found here:

The next step is to get a brief grasp of data science. You can learn these from:

  1. for Python and R

  2. Coursera course on data science

  3. Udemy courses in Python and R (Note these would most likely be paid courses so wait for the monthly discounts to kick in to purchase them for $10-$15)

I wouldn't recommend codeacadmy since it's dated written in Python v2.x whereas Python 3.6x is more widely used

Then I would consider AI Specific courses found online. Theres two routes again here, there's the heavily academic route that delves into the theory and mathematics then there;s the practical route. Depends on the speed and pace you want to learn at because it's a massive field.


  1. Udacity - Introduction to Artificial Intelligence (standford course)

  2. Coursera - Andrew Ng's Deep Learning specialization course. Note the course uses octave which is similar to Matlab style programming. The courses when accessed individually are for free or you can pay for a certification.

  3. Various lectures on youtube for MIT and Stanford's Artificial Intelligence courses.

  4. A really good text book to check out is Artificial Intelligence - A modern Approach. AI was traditionally scripted in Lisp or prolog. This has been coverted into Python over here


  1. Krill Ermenko - AI, Machine Learning and DEEP Learning from A-Z

  2. Dives into keras a top level library