131–140 of 362 posts
I love the ethics requirements. My current uni doesn't have this and I'm so glad I took it at the college I attended as an underclassmen. The different ethical theories apply so well to a lot of work being done in computer science.
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.
"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."
And it will still look less beneficial than a standard comp Sci degree unfortunately. The only good part is that the school is pretty prestigious, so not as bad. Hopefully we don't have another AI winter.
Most core CS work can be completed by the end of your sophomore year. There's not a lot of fundamentals. After that you can go for breadth of topic matter (embedded systems, networks, AI, cryptography/security, distributed systems, etc), as was the case for me. This degree seems to give more depth in regard to ML.
You're right about the prestige of the school. 15 years after getting my degrees I still get fast-tracked for interviews. So I feel the coursework matters very little when it comes to being recruited. That being said, the majority of the material I learned hasn't been used in my career. It's largely the way they teach you how to think and solve problems that companies familiar with CMU value.
>include a strong emphasis on ethics and social responsibility
If you are an undergraduate in computer science these days, it is very hard to get into advanced AI/ML classes, which are typically reserved for graduate students. Back before the ML goldrush, a strong CS undergrad interested in AI could elect to take advanced coursework beyond the introductory AI class. Nowadays, good luck getting off the waitlist! Having an official "AI major" does at least tell students, "Hey, we…
While there may be a lot of demand for AI/ML, I’m concerned to whether there are enough students with the proper foundations in math and stats to do well. New classes such as Data Science seem to just instruct students how to use algorithms and not why.
Carnegie Mellon was the first university to offer a PhD in Machine Learning (via the Machine Learning Department which, again, I think is relatively unique in its existence). Regardless of how you feel about the hype, they made an early bet on the field and adding an undergraduate degree seems consistent. Source: https://www.ml.cmu.edu/about/index.html
Edit: years to decades
Earlier quoted context omitted.
Expanding even more upon a reply to a sibling comment: I think it's possible (but not necessarily so) that AI and "data science" are emerging as academic fields and practical disciplines dependent on, but distinct from, computer science. I think this is similar to how computer science emerged as a distinct discipline from both electrical engineering and math. Electrical engineering and hardware design didn't go away…
I think that the way computer science emerged from EE is totally distinct to what’s happening right now. CS eventually abstracted away all of the electrical engineering aspects of the discipline and as a result you need no knowledge of digital logic design to study computer science. AI/ML I don’t think will ever be this way; you will always need CS knowledge in order to experiment/run/optimize your algorithms.
Engineering Science - Machine Intelligence Option
http://engsci.utoronto.ca/explore_our_program/majors/machine...
What is the difference between the Machine Intelligence major in Engineering Science, and an undergraduate degree in Computer Science?
While there are some commonalities between the Machine Intelligence major and what is offered through Computer Science, engineering offers a unique perspective.
First, graduates will have a systems perspective on machine intelligence, which integrates computer hardware and software with mathematics and reasoning. This enables a focus on algorithm development and the relationship between machine intelligence with computer architecture and digital signal processing.
Secondly, graduates will benefit from an approach that encourages problem framing and design thinking. Design thinking is a method for the practical and creative resolution of problems, which encourages divergent thinking to ideate many solutions, and convergent thinking to realize the best one. Students will be able to frame and solve problems in the MI field, and apply MI tools to problems in many application areas. These include finance, education, advanced manufacturing, healthcare and transportation. This field is in a phase of rapid development, and engineers are well equipped to contribute as a shaping force.