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USC vs NYU ------------------- Below is a comparison between the two universities (University of Southern California and New York University) covering the major points. If there are some additional points you want to discuss, please mention and I can write more about them. DISCLAIMER - The below mentioned details is an extract from all the interactions I had with students studying in both the universities, reading articles, forums and watching videos over Internet. I am not inclined to any university and will appreciate any extra points that you can bring on to the table. 1. NYU is really a good school for all the people who have AI/ML as their study and research area. With less head count you may able to get better understanding. On the other hand, USC provides more diverse CS courses and specializations than NYU. Like NYU in east coast, USC is also popular for AI/ML over the west. Additionally it provides other specialized courses in Game Development, Computer Networks, Computer Security, High Performance Computing, Data Science and Intelligent Robotics to name a few. Many of you will be thinking about the rising Data Science program at NYU. Yes, it is also good but as far as I have judged, for a student admitted to CS department it is not so easy to opt Data Science courses as it's all together a separate program and they have dedicated set of students working on that field. Whereas USC gives a lot more flexibility for CS (General) admitted student. 2. Jobs and Internships - Both universities will provide you excellent opportunities however we need to concentrate on the probability of the type of job you end up with. NYC has the financial sector in its pocket and it is more likely that a graduate from NYU will get settled in a financial firm. The firms will pay you more and give you loads of work and experience but in the end as a CS graduate you may end up as a support function to their business. I <u>doubt</u> that there will be many opportunities to work on new technologies and research experience. However, California provides you high probability for job and internship opportunities in a tech firm where you work in the core competency fields. 3. Mind Trick - While I was struggling through all comparisons between NYU and USC, there were two reasons which were very sticky to the mind. Let's read about them and try to analyze the same. Again, I am just trying to analyze and I am not speaking "for" or "against" any university: (a) Student intake in NYU is less compare to USC. ( NYU has the brand. Now analyzing both, (a) Yes, student intake in NYU is less which <b>may</b> give some advantage to studies. The reason I say "may" is because it all comes down to professor and TA's helping you in the course and strength doesn't affect much. But when it comes to jobs and internships you may face similar competition as USC. There are mainly three reasons for this. One is NYU-Poly merger which takes good number of students. Second is the competition from other universities like Columbia University. Third is demand in NYC. As I understand, Cali has more demand than NYC to consume the graduates offered by universities. USC has a huge batch size (700 approx students) but wait a second, all what matters is how diversified the students are. Considering the amount of courses offered, class size in USC may touch 50 easily (which is very high compare to NYU) but what I have read from their website, they manage it well. Depending on the class size, they have good number of TA's helping you to solve your doubts. ( Okay, now the brand is more inclined to MBA program than CS. NYU Stern school is very much reputed and is in Top 10 in the US. As I have heard, the Courant School doesn't have more reputation than USC over the west coast where it matters the most. (Appreciate any inputs on this). If you have your interests inclined towards AI, ML or any specialization which uses Applied Mathematics and good to settle in a job from financial/technical (Probability (as per my understanding): 80% - financial; 20% - technical) firm, NYU is the school for you! However, if your thoughts vary in any of the above things then I recommend you to give a second thought and decide. In the end it's you and your decision that matters.