My undergraduate degree (from The University of Edinburgh) is Artificial Intelligence. I remember when I was visiting different universities in the UK back in 2000, Edinburgh was the only one I saw which offered AI as a "real" degree. Everywhere else it was a specialization which was tacked on in the final year of a computer science degree.
That seemed really odd to me then. Seems even odder now.
For those who might not know, the University of Edinburgh had a department of artificial intelligence in the 1970s. They were very forward thinking at the time -- it later got folded into the School of Informatics, but Edinburgh remains one of the best places to work on AI/ML work.
edit: slightly awkward phrasing in my original comment above. Amended: They were (and still are!) very forward thinking.
I'm curious to hear about your experience. In my mind, artificial intelligence can't be separated from computer science. In fact, I feel like you need a full Comp Sci degree before you can effectively apply your skills to real world AI challenges.
I am currently studying this degree at the same university. A few AI concepts (NLP and Formal Language Processing) are introduced in the 2nd year. Other than that, all courses are CS/Maths. Keep in mind that at Scottish Universities, students apply directly to their degree and besides one or two courses per year (some like Medicine or Law often have no electives), students take only courses within their degree. This way, with most AI courses in 3rd and 4th year, students tend to have a strong enough grounding in CS principles and Maths for this material. That's not to say that the degree is perfect, or providing "real/production" AI, but it is certainly well done.
It's a little more complicated than I made it sound above. 50% of my curriculum was courses from CS department, the other 50% courses from the AI department. It was actually possible to do AI without doing CS at all, though. There were AI and Linguistics, and AI and Phycology degrees, for example. There was basically no crossover in languages used in the courses taught by the two departments. CS was mostly Java with some C++ and C. AI was Matlab, Prolog, a little bit of Python for NLP, and few other esoteric things. Some AI-side courses involved basically no programming at all ("Introduction to Cognitive Science" springs to mind).
That said: some of the AI students who didn't have to take any CS courses chose not to take the suggested ones... then had a really hard time in a few of the later courses. Computer Vision was brutal for them.
The situation is slightly different now. Edinburgh has a foundational "Informatics" (being the combination of CS, AI and Cognitive Science) curriculum. Students in those disciplines start with that, and then fully specialize in the later years of the course.
As a more or less completely unrelated side note: Sethu Vijayakumar, one of the judges for the last couple of seasons of Robot Wars UK, was my dissertation examiner.
Back in the 2000s - it was AI & CS (or SE) Joint Honours.
In 1st and 2nd year, you would do the same Maths and CS course as CS/SE; you didn't get an elective it was a separate AI course, which covered the basics.
In 3rd/4th year (honours years as they're called here) - IIRC you'd have to take 8 courses in 3rd (plus an individual project and a team project) and 6 in 4th and your dissertation. Depending on the degree specialisation; you had to take some mandatory courses (CS only had to do Compiling Techniques and Algorithms, AI/CS didn't have to do CT - but they had to do Algorithms and Computability and Intractability). So, the two departments were very closely aligned and then were brought together into a new department/school within the Science and Engineering faculty.
They also offer a single AI honours degree now, but the structure seems very similar to what I experienced, with perhaps a bit more freedom in 3rd and 4th year.
Interestingly, while the majority of students were AI/CS or AI/SE - they also had joint honour programmes outside the faculty - so there were a few students who were AI and Psychology as well as AI and Linguistics. I don't believe they offer this combination anymore.
CMU seems to agree with that. Upthread bertjk posted:
"AI majors will receive the same solid grounding in computer science and math courses as other computer science students. In addition, they will have additional course work in AI-related subjects such as statistics and probability, computational modeling, machine learning, and symbolic computation."
I am from the United States, next year I am probably going to attend the the University of Edinburgh for The Computer Science and Artificial intelligence course. Something I have been wondering is how US employers view the university, particularly with the somewhat strange (at least in the US) course title - "Artificial intelligence?"
Are you considering doing a foreign year, or your whole degree in Edinburgh?
I can only speak for my current employer (Google), who look very favourably on degrees from Edinburgh. It's one of the four UK universities we recruit from directly.
As for the course title, there's also "Computer Science" in it, which people can latch on to if they need that. When people asked about the AI part of my course I would say "Software Engineering is 'This is what works', Computer Science is 'This is why this works', and Artificial Intelligence is 'I wonder if this works'".
Thanks, that is good to know. I am doing a whole degree there. I am not sure how recruiting works at Google but when you say Google do you mean London or US based offices? Obviously I don't know what I will want to do in 4 years but I anticipate moving back to the US after I graduate.
Me too. I'm guessing they'll hear the word "perceptron" less than I did. Probably less Matlab and Prolog will be taught as well. I can't remember whether the Semantic Web course was CS or AI, but I suspect that won't come up, either. Fashions have probably changed enough that their probably won't be that much crossover.
For me at least, it depends almost as much on who's doing the teaching than it does what's being taught. Generally for me, the highlights were any course taught by Barbara Webb or Jon Oberlander.
Back then perceptrons (single neurons with engineered feature inputs) were a lot closer to cutting edge than they are now.
As for why Matlab was used a lot: because it comes "batteries included", I suspect. Probably the same reasons that Andrew Ng used it as the teaching language for his Stanford/Coursera Machine Learning course. Plus a lot of my lecturers had maths backgrounds.
That seemed really odd to me then. Seems even odder now.