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Artificial Intelligence (AI)

Artificial Intelligence (AI)


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8.1/10 (Our Score)
Product is rated as #81 in category Artificial Intelligence

What do self–driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common? They are all complex real world problems being solved with applications of intelligence (AI). This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems. You will learn about the history of AI, intelligent agents, state–space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems. Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.

Instructor Details

Ansaf is a Lecturer in discipline of the Computer Science Department at the School of Engineering and Applied Science at Columbia University. She received her her BS in Computer Science in 1996 from the University of Science and Technology (USTHB), Algeria. She earned her masters and Ph.D. degrees in Computer Science from the University of Orleans (France) in 1999 and 2003 respectively.

Specification: Artificial Intelligence (AI)


108 hours









8 reviews for Artificial Intelligence (AI)

4.8 out of 5
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  1. Dissipate

    I can’t say much as to the content of the course since I dropped it in Week 2. The content in Week 1 was merely introductory, and not too easy nor difficult.

    The problem was that the lecturer speaks way too fast in the videos. At first I thought that I had accidentally set the video to run at 1.5x. But, the video showed that it was running at 1.0x and I thought edX might be broken. Upon refreshing a few times, I found out that nothing was broken. There was the option of 0.5x, but that was too slow mo, I do not think an accurate 0.5x.

    There are subtitles, but it just means that you have to read at a fast speed as well. You can read the subtitles without watching the video, but you may miss the slide that it is paired with, and what the lecturer is writing on the slide.

    Since it was highly unlikely that the videos would be redone with the lecturer speaking at a pace that everyone can follow comfortably, I dropped out. More trouble than worth it.

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  2. Anonymous

    I at least found the speed of her talking ok. She does get mixed up sometimes but the subtitles are there to make up for that. Quizzes I feel are a bit of a pain but the projects you have to do are on point. They are the perfect amount of challenging to keep you interested. Still taking the course.

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  3. Dolly Ye

    Taking right now,not as rigorous and intellectually challenging as the UC Berkeley version (CS188) on edX or other MIT computer science courses. Given that the instructor for CS188 (Dan Klein) is a star (thus unfair comparison) and that the course is archived, her presentation of the materials is ok.You still learn a lot about AI basics.However,there is no staff support and no answer to quiz question.Don’t take it for a certificate.Nevertheless,the programming assignments are fun and doable. I definitely recommend you take BerkeleyX: CS188x 1 Artificial Intelligence.It’s by far the best academic experience I have so far.

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  4. Gacko

    The quizzes are so painful. Can anyone help me? I love this course. But I confused by quiz of every week. My mail:

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  5. Anonymous

    The highlight of the course is the content: good lectures and five very interesting and informative programming assignments. I put about 20 hrs/week into the course and learned quite a bit. The weak part of the course is the TA engagement; they weren’t very responsive or helpful. Course materials, including quizzes, contain numerous grammatical errors that hopefully will be cleaned up before the next session.

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  6. Malolan Vasu

    This is a great course. I would highly recommend this course to anyone wanting an introduction to AI. The course itself was quite challenging and definitely worth the verified certificate. Although the quizzes were just a bit tough, the programming assignments were extremely hard (in a good way). The projects were fun and interesting. Do however note that they might suck up a lot of your time (20 25 hrs on average)

    Also, this course has quite a bit of math in it. I took this course when I didn’t know much of linear algebra and calculus and in some parts of the course, my mind was totally blank. Now , after finishing the course and after learning some of that math, I just went through those videos which had previously left me totally blank and I was able to easily comprehend the material. I also managed to pass quite easily even without the math ( I even left out a programming assignment and still got a 82%) so if you don’t have the math knowledge, don’t worry.

    Coming to the involvement of the staff and TAs, it wasn’t great. At the start of this course (around week 1 4), the staff was extremely responsive and helped out tons of students. However, as the course progressed, involvement went down. Technical problems would go uncorrected for days and questions would be left unanswered for weeks(Note that quiz errors were still getting corrected throughout the course if those errors were reported quickly). Even with those problems, the course and its contents, engaged me. Fortunately, the staff realized the problem and became active in the last few weeks, with even the course lecturer, who is truly an amazing professor :), helping us out.

    All in all, a great course totally worth paying for the certificate. I unfortunately couldn’t get the money ( 🙁 300$ is a lot in my country ) to pay for it but I truly enjoyed learning.

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  7. Davide Mariani

    I think this course is extremely interesting and well done in terms of contents and assignments. I am at the third project right now and I found the first two challenging and useful (I recommend taking this course with the requirements they specify in the description, like linear algebra, some coding, statistic). The only weak point is the quality of the lessons in my opinion: the speaker is often too fast and not clear enough, but the structure of the content is absolutely great. I haven’t tried BerkeleyX’s one (mentioned above here), but I consider this AI course as the best so far.

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  8. Anonymous

    I loved this course despite its inconvenient quirks. It covers everything it says on the label and more. Expect to put a not insignificant amount of effort into the programming assignments which at times are on the challenging side. I would recommend that you have the text book available at your side as you work through the lectures as a resource it is second to none. There are some caveats for this course though. Queries about the grader and platform take an age to get answered by the assistants and some get plane ignored. The quiz questions can be a bit on the tedious side testing reading comprehension skills rather than ability to apply the concepts. The programming assignments were in a way the best part of the course. But for this run of the course they decided to limit the number of tries ,a number they stuck to like glue without any room for manouvre. In addition on some of the assignment they specified time limits on how long the code could run for on the grading platform exceed the threshold and get zero points as I understand it this is completely new. A major glitch on this run of the course was that all quiz material and project material were removed unexpectedly for viewing at the beginning of the final week when a majority of students were revising for the final exam unexplicable really. What is more if you have not backed up your quiz answers and the project details all are lost forever. For people who paid $300 for the micromasters certificate this must be bitter pill to swallow although I haven’t seen any complaints on the comments board yet .

    On the positive side this is a great survey of modern AI. The course encompasses most of the major topics apart from bayesian networks. The professor is very engaging and her lectures are a joy to watch and learn from.

    Overall I strongly recommend this course to anyone who wants a broad thorough introduction to AI at the masters level.

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