1. Computer Sciences at NYU Open House January 2004 l Graduate Study at New York University l The MS in Computer Sciences l The MS in Information Systems l The MS in Scientific Programming l The PhD in Computer Science l Questions and answers l Reception with faculty

2. Why study at NYU l Largest C.S. department in the area l Many areas of strength l High caliber, high quality program l All courses taught by faculty (regular, visiting, or industrial adjuncts) l Possibility to get involved in research -- biocomputing, graphics, algorithms…. l Great campus location!

3. Why study Computer Science l Monetary: media, finance, communications, information technology, new industries. l Intellectual: Improve skills and ability to acquire new skills l Personal: It’s fun.

4. Subject Matter of the M.S. program l BAs program; M.S. s design; PhDs do research. (Note: Most profs also program.) l You learn not only languages, you learn how to design languages, similarly for databases, operating systems etc. l Programming in the large (by small groups) l Research environment l Evening classes to accommodate working professionals

5. Deeper Understanding l “...Everything is on the surface, you don’t read the rule book, you do it by tinkering. The danger is that this sort of tinkering becomes a model for all understanding” (Sherry Turkle, Sci.Am. April 1998) l An MS allows you to understand the details under the hood (and build your own engines when needed).

6. The field of Computer Science l Foundations – basic sciences (algorithms, programming languages, operating systems, compilers) l Advanced technology –staying current (cryptography, Java/XML, distributed computing, networking, animation, verification, visualization, biocomputing...)

7. Foundation Subjects The scientific bases of computing: – Algorithms (also complexity and theory of computation) –Programming Languages –Operating Systems –Compilers

8. Technological Subjects l Software design methodologies l Graphics, animation, and visualization l Artificial Intelligence, NLP, Pattern Rec l Numerical computing, Time Series Anal l Secure file systems/Cryptography l Databases, Distributed systems l Internet programming & Multimedia

9. Requirements of MS in CS l 36 credits (12 courses) –typically 2-3 years (must be completed in five) l Core Examination on Foundations l Specialization Area l Possibility of internships/independent studies/interdisciplinary courses.

10. Privileges of Grad students l Numerous seminars (10 a week) l Libraries l Coles Sports facility l Meeting future colleagues

11. Some Research Projects l Multimedia and user interfaces l Robust distributed computation l Performance of parallel systems l Image recognition in industry and medicine l Computational genomics l Fluid dynamics and airfoils l Motion capture/Query by humming.

12. The PAC Program l For students with some professional experience (power user) but no undergraduate degree in CS l Reasonable math background l Begins each Fall semester l Adds 1 year, 8 credits

13. Some Entry Stats l General GREs > 700 in quantitative and 4.0 or better in analytic. l Strong grades l Strong specific recommendations (from work and/or academia) l Relevant experience, knowledge and desires.

14. Master’s in Information Systems l The MS in Information Systems –with the Stern School of Business l Roughly half computer science and half business courses + capstone projects course l Aim is to train Chief Information Officers.

15. The Project course l Centerpiece of MSIS program. l Offers students real-world experience l Recent projects with The Gertrude Stein Repertory Theatre and Bell Labs, HBO, ILX Systems, Inc., InterWorld, The Hypertext Neurological Knowledgebase (THyNK), etc.

16. Master’s in Scientific Computing l The MS in Scientific Computing is a joint program with the Courant Math Department l Goal is to train designers of mathematical programs in science and finance.

17. The Ph.D. Program l 72 Credits (24 courses) – Normally, 2 to 4 years more than M.S. l Certification of practical and theoretical skill. l Oral preliminary exams l Thesis – Proposal – Submission – Defense

18. QUESTIONS ???????????? check also www.cs.nyu.edu or write to dgs@cs.nyu.edu

19. Some choices:Applications Programming –Graphics –Data Communications & Networks –Advanced topics in data communications –Advanced topics in Operating Systems –User Interfaces –Real-Time programming –Unix tools –Groupware

20. Staying Current l Quick-learning from fad to fad is not enough (“No, but I’ve heard of it…”) l Needs solid scientific / technical basis to recognize and adapt to innovation. l How: foundation courses + timely courses from leading researchers and practitioners.

21. Some Areas of Specialization –Software Engineering –Applications Programming –Databases and distributed Computing –Numerical Analysis –Artificial Intelligence –Computer Architecture –Graphics –Internet technologies and Multimedia