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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Advisors
    Copyright FAQ Quick Links Data Science Institute IGERT From Data to Solutions ASCENT Program Faculty Job Opportunities Academic Advisors Associate Chair for Undergraduate Education Adam Cannon Director of Undergraduate Studies for BS Programs Paul Blaer Director of Undergraduate Studies for BA Programs Jae Woo Lee Information Science Advisor Adam Cannon 3 2 Combined Program Advisor Stephen Edwards CS Math Joint Program Advisor Jae Woo Lee CS Stat Joint Program Advisor

    Original URL path: http://www.cs.columbia.edu/education/undergrad/advisors (2016-02-17)
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  • CS Research Opportunities @ CU
    professor introduce yourself and ask if you can work for the project You can also browse available projects and network with faculty to find the project that s right for you at the Undergraduate and MS Project Fair Come to the CS Lounge 450 Mudd Friday January 22 2016 at 11 00AM 12 30PM and be sure to bring your resume and a copy of your official transcript Register for the project as though it were a course before the last day to add a class using the appropriate course number Masters students Register for E6901 You can count up to 12 points of project courses toward your degree Undergraduates Register for COMS W3998 for your first project For your second project register for W4901 You can count up to 6 points of project courses toward your CS degree Need Help Contact the Research Project Liaisons project at lists dot cs dot columbia dot edu or email them directly Yuan J Kang first name middle initial last initial at cs dot columbia dot edu Asynchronous Circuits and Systems Group Autonomous Agents Lab Columbia Automated Vision Environment Columbia Vision and Graphics Center Computational Biology Computer Graphics Group Center for Computational Learning

    Original URL path: http://www.cs.columbia.edu/%7Eproject/ (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | FAQ for Prospective Undergraduate Students
    graduates of the computer science program at Columbia step directly into career positions in computer science with industry or government or continue their education in graduate degree programs Many choose to combine computer science with a second career interest by taking additional programs in business administration medicine or other professional studies Students graduating from Columbia s Computer Science Department find themselves well suited to continue study at the graduate level in top name institutions However all students who complete the program have the knowledge requisite to pursue a variety of careers either within the computer industry or elsewhere What makes your Computer Science program stand out compared to other top programs and institutions Due to our relatively small undergraduate population and the department s research orientation many C S undergraduate students at Columbia work with faculty on research projects in their junior and senior years Students find these research opportunities very rewarding in terms of their exposure to cutting edge research introduction to the academic research environment and enhancement of their overall education Many of the C S teaching faculty are leaders in their research field and or have extensive experience in industry and private sector research labs C S majors at Columbia have the opportunity to be taught and advised by world renowned computer scientists who have well developed collaborative relationships with companies such as Bell Labs IBM Lucent and Microsoft as well as other leaders in the field Finally Columbia s location allows students to take advantage of the proximity to many potential future employers based in New York City as well as the many cultural attractions the city offers What opportunities are there to get involved in Computer Science research as an undergraduate at Columbia There are many research opportunities in the computer science department during the academic year Many of the faculty sponsor undergraduate and masters students for research projects in their groups Typically the faculty sponsor the students for credit but in some cases projects also provide a stipend Please see the list of departmental research areas What research internship and fellowships opportunities exist during the summer months and how do I participate Faculty members post summer research opportunities directly to students via email These can be for credit pay or both Opportunities are also advertised through the Center for Career Education CCE What kinds of career opportunities would this major concentration prepare me for In addition to graduate study our students have gone on to a variety of careers either within the computer industry or elsewhere Generally the majority of our graduates have found positions at established computer software companies e g Microsoft Google research labs e g IBM or Wall Street firms e g Morgan Stanley and Goldman Sachs Other graduates have found positions at smaller companies or startups e g foursquare A few students have gone on to work or study outside of the field of computer science applying their knowledge of the discipline to another field such as business medicine or

    Original URL path: http://www.cs.columbia.edu/education/undergrad/prospectivefaq (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Academic Honesty
    web pages The Academic Committee maintains for instructor reference a secure list of academic honesty violators which records their academic penalties and also when permitted by the student s school their disciplinary penalties Among other penalties students found in violation of academic honesty rules by the deans may be prohibited from serving as departmental Teaching Assistants from receiving departmental financial support and from being recognized with departmental awards However instructors who wish to refer to such a violation in a letter of recommendation requested by such a student must first ask for the student s permission to disclose the violation Instructors must not mention the violation if permission is denied As always writing letters of recommendation is the prerogative of the instructor PROCEDURES AND PENALTIES If an instructor suspects academic dishonesty the instructor contacts the student or students involved and asks for explanations The instructor can request a meeting with the student or students who may be seen individually or as a group and with or without witnesses If the explanations appear inadequate the instructor informs the student or students that academic dishonesty is suspected applies the appropriate academic penalties and registers the penalties with the Academic Committee and reports the incident to the appropriate dean or deans together with a written summary of the investigation An instructor may also choose to defer the academic penalty until the investigation has been completed in some cases this may result in a course grade of INC until the matter is resolved In general the academic penalty for a first offense of academic dishonesty within the Department is a grade of zero on the assignment project or exam or reduction of the course grade at the discretion of the instructor In general the academic penalty for second and subsequent offenses across all courses within the Department is failure in the course An instructor may immediately fail a student for sufficiently severe infractions The appendix to this policy gives examples Students may appeal academic penalties in writing to the Academic Committee within 10 business days or in those cases investigated by the deans within 10 business days of the deans decision The committee solicits from the instructor and from witnesses additional written statements The committee then forwards its recommendations to the instructor The deans may pursue a separate investigation This helps expose any pattern of academic dishonesty that occurs across the university s courses The deans follow the rules and procedures of their schools available on their web sites or in their bulletins In general they conduct a hearing with the students and if appropriate with the instructor and determine the appropriate disciplinary action The disciplinary penalty may include suspension or expulsion The deans inform the instructor of their decision this may further influence any academic penalty and in particular may resolve a temporary course grade of INC The appeals process for disciplinary penalties is specified by each school and is available in each school s publications AUTHORIZATION This document has been approved by

    Original URL path: http://www.cs.columbia.edu/education/honesty (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Breadth Requirement
    Faculty Job Opportunities Breadth Requirement All students must complete the Breadth Requirement To fulfill this requirement take 1 course from Group 1 Systems 1 course from Group 2 Theory 1 course from Group 3 AI and Apps and 1 more course from any of the three groups for a total of 4 courses Required track and track elective courses at Columbia can satisfy breadth requirements if they also appear on

    Original URL path: http://www.cs.columbia.edu/education/ms/breadthRequirement (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | MS Requirements prior to Fall 13
    required to complete 9 credits out of the following list excluding courses already taken at least 6 credits must be at the 6000 level COURSE ID TITLE COMS W4203 Graph Theory COMS W4205 Combinatorial Theory COMS W4241 Numerical Algorithms and Complexity COMS W4252 Introduction to Computational Learning Theory COMS W4261 Introduction to Cryptography COMS W4281 Introduction to Quantum Computing COMS W4995 Crypto Financial Processes CSEE E6180 Modeling and Performance COMS E6204 Topics in Graph Theory COMS E6232 Analysis of Algorithms II COMS E6253 Computational Learning Theory II COMS E6261 Advanced Cryptography COMS E6291 Theoretical Topics in Computer Science COMS E6901 Projects in Computer Science COMS E6998 Advanced Topics in Computational Geometry COMS E6998 Advanced Topics in Complexity Theory COMS E6998 Network Theory COMS E6998 Algorithmic Game Theory COMS E6998 Advanced Topics in Comp Geometry COMS E6998 Advanced Topics in Complexity Theory COMS E6998 Network Theory COMS E6998 Algorithmic Game Theory COMS E6998 Advanced Topics in Machine Learning COMS E6998 Formal Verification COMS E6998 Algorithmic Game Theory COMS E6998 Algorithms for Dealing with Massive Data COMS E6998 Algorithmic Graph Theory COMS E6998 Advanced topics in Programming Language Compilers COMS E6998 Randomness in Computing COMS E6998 Econ of Social Networks COMS E6998 Lower Bounds of Theoretical CS CSPH G4802 Incompleteness Results in Logic SIEO W4150 Intro to Probability and Statistics IEOR E4407 Game Theoretic Models of Operation IEOR E6400 Scheduling Deterministic Models IEOR E6603 Combinatorial Optimization IEOR E6606 Advanced Topics in Network Flows IEOR E6608 Integer Programming IEOR E6610 Approximation Algorithms IEOR E6613 Optimization I IEOR E6614 Optimization II IEOR E6711 Stochastic Models I IEOR E6712 Stochastic motels II IEOR E8100 Doctoral Seminar on Convex Optimization ELEN E6718 Algebraic Coding Theory ELEN E6970 Resource Allocation and Networking Games Computer Science course descriptions are available here SECTION 5 GENERAL ELECTIVES Remaining credits from any qualifying Computer Science graduate course 4000 and 6000 level Students may take up to 3 credits of non technical course approved by the advisor Please complete a non technical approval form and once it is signed forward it to or Known non technical courses IEOR E4550y Entrepreneurial business creation for engineers SECTION 6 GRADUATION Candidates preparing for graduation should submit a completed application for degree to the Registrar s Office and submit a track graduation form to C S Student Services an example of a completed form is available here SECTION 7 CONTACT Please direct all questions concerning the Foundations of Computer Science Track to Note that these course offerings are listed on a provisional basis only and may change from what is listed here The Machine Learning Track The Machine Learning track is intended for students who wish to develop their knowledge of machine learning techniques and applications Machine learning is a rapidly expanding field with many applications in diverse areas such as bioinformatics fraud detection intelligent systems perception finance information retrieval and other areas SECTION 1 REQUIREMENTS OVERVIEW REQUIRED ELECTIVES CORE TRACK TRACK GENERAL MINIMUM REQUIRED CREDITS 12 6 6 6 COURSES SEE SECTION 2 SEE SECTION 3 SEE SECTION 4 SEE SECTION 5 TOTAL MINIMUM REQUIRED CREDITS 18 12 30 COURSE AND CREDIT REQUIREMENTS FOR THE MACHINE LEARNING TRACK Students must complete at least 30 credits and of those 30 credits minimum of 6 elective credits must be at the 6000 level At least 3 of the track elective credits Section 4 must be a 6000 level course Students who waive core or required track elective using previous courses may take other Computer Science courses in lieu of waived ones SECTION 2 CORE COURSES The following is a list of Computer Science core courses COMS W4115 Programming Languages Translators COMS W4118 Operating Systems COMS W4156 Advanced Software Engineering CSOR W4231 Analysis of Algorithms COMS W4701 Artificial Intelligence CSEE W4824 Computer Architecture SECTION 3 REQUIRED TRACK COURSES Candidates are required to complete two 2 of the following courses COURSE ID TITLE COMS W4252 Introduction to Computational Learning Theory COMS W4771 Machine Learning COMS W4772 Advanced Machine Learning SECTION 4 ELECTIVE TRACK COURSES Students are required to take two courses from the following list at least one of which must be a 6000 level course Other courses on this list may be used as general electives or to replace core or required track courses when the student has received a waiver COURSE ID TITLE COMS W4111 Introduction to Databases COMS W4252 Introduction to Computational Learning Theory COMS W4705 Introduction to Natural Language Processing COMS W4731 Computer Vision COMS W4737 Biometrics CBMF W4761 Computational Genomics COMS W4771 Machine Learning COMS W4772 Advanced Machine Learning COMS W4995 Intro Social Networks COMS E6111 Advanced Database Systems COMS E6253 Advanced Topics in Computational Learning Theory COMS E6735 Visual Databases COMS E6737 Biometrics COMS E6901 Projects in Computer Science COMS E6998 Search Engine Technology COMS E6998 Network Theory COMS E6998 Algorithmic Game Theory COMS E6998 Statistical Methods for NLP COMS E6998 NLP for the Web COMS E6998 Advanced Topics in Machine Learning COMS E6998 Machine Translation COMS E6998 Machine Learning for NLP COMS E6998 Intro Distributed Data Mining COMS E6998 Analysis of Social Info Nets COMS E6998 Algorithms Deal Massive Data COMS E6998 Large Scale Machine Learning COMS E6998 Sparse Signal Modeling COMS E6998 Econ of Social Networks COMS E6998 CV and ML on Mobile Platforms COMS E6998 Data Science Entrepreneurship COMS E6998 Fund of Speaker Recognition COMS E6998 Bayesian Analysis for NLP IEOR E6613 Optimization I IEOR E8100 Optimization Methods in Machine Learning SIEO W4150 OR STAT W4201 Probability and Statistics OR Advanced Data Analysis STAT W4240 Data Mining STAT G6101 Statistical Modeling and Data Analysis I Computer Science course descriptions are available here SECTION 5 GENERAL ELECTIVES Candidates are required to complete at least 6 additional graduate credits at or above the 4000 level at least 3 of these credits must be CS the other 3 credits may be a technical or non technical elective approved by the track advisor Please complete a non technical approval form and once it is signed forward it to or At most 3 credits overall of the 30 graduate credits required for the MS degree may be non technical SECTION 6 GRADUATION Candidates preparing for graduation should submit a completed application for degree to the Registrar s Office and submit a track graduation form to C S Student Services an example of a completed form is available here SECTION 7 CONTACT Please direct all questions concerning the Machine Learning Track to and Please note that these course offerings are listed on a provisional basis only and may change from what is listed Check the registrar s website for definitive information ELEN E4810 Students who took it in Fall 06 or earlier can use it as an elective IEOR E6613 Students who took it in Fall 06 or earlier can use it as an elective The Natural Language Processing Track The Natural Language Processing NLP track is intended for students who wish to gain expertise in NLP technologies and applications NLP technologies are of central importance in automating the analysis of text and speech databases and in enabling man machine interactions through natural language This track will help you develop leading edge knowledge of these technologies SECTION 1 REQUIREMENTS OVERVIEW REQUIRED ELECTIVES CORE TRACK TRACK GENERAL MINIMUM REQUIRED CREDITS 12 9 6 3 COURSES COMS W4701 SEE SECTION 3 SEE SECTION 4 SEE SECTION 5 TOTAL MINIMUM REQUIRED CREDITS 21 9 30 COURSE AND CREDIT REQUIREMENTS FOR THE NATURAL LANGUAGE PROCESSING TRACK Students must complete at least 30 credits and of those 30 credits minimum of 6 elective credits must be at the 6000 level At least 3 of the track elective credits Section 4 must be a 6000 level course The Natural Language Processing track has one required core course COMS W4701 Artificial Intelligence Students who waive core or required track elective using previous courses may take other Computer Science courses in lieu of waived ones SECTION 2 CORE COURSES The following is a list of Computer Science core courses COMS W4115 Programming Languages Translators COMS W4118 Operating Systems COMS W4156 Advanced Software Engineering CSOR W4231 Analysis of Algorithms COMS W4701 Artificial Intelligence CSEE W4824 Computer Architecture SECTION 3 REQUIRED TRACK COURSES Candidates are required to complete the following three courses COURSE ID TITLE COMS W4705 Natural Language Processing COMS W4706 Spoken Language Processing COMS E6998 Topic Courses that focus on NLP Students who have completed equivalent courses with grades of at least 3 0 may apply these courses to satisfy these requirements and devote more credits to pursue elective courses SECTION 4 ELECTIVE TRACK COURSES Candidates are required to complete two 2 courses out of the following list at least one course must be a 6000 level CS course Since other departments vary their offerings considerably from year to year it is possible to count such courses toward the M S degree please propose courses you think might be suitable to the track advisor COURSE ID TITLE COMS W4170 User Interface Design COMS W4172 3D User Interfaces Augmented Reality COMS W4252 Introduction to Computational Learning Theory COMS W4771 Machine Learning COMS E6901 Projects in Computer Science COMS E6998 Search Engine Technology COMS E6998 Network Theory COMS E6998 NLP for the Web COMS E6998 Statistical Methods for NLP COMS E6998 Machine Learning for NLP COMS E6998 Advanced Topics in Machine Learning COMS E6998 Machine Translation COMS E6998 Fundamentals Speaker Recognition COMS E6998 Semantic Tech in IBM Watson COMS E6998 Bayesian Analysis for NLP SIEO W4150 Probability and Statistics ELEN E4810 Digital Signal Processing ELEN E6820 Speech Audio Processing Recognition PSYC G4232 Production and Perception of Language PSYC G4275 Contemporary Topics in Language and Communication PSYC G4205 Models of Cognition PSYC G4470 Psychology and Neuropsychology of Language PSYC G6006 Introduction to Statistical Modeling in Psychology Computer Science course descriptions are available here SECTION 5 GENERAL ELECTIVES Candidates are required to complete at least one general elective graduate CS course 3 credits at 4000 level or above approved by the Track Advisor Please complete a non technical approval form and once it is signed forward it to or At most 3 credits overall of the 30 graduate credits required for the MS degree may be non technical SECTION 6 GRADUATION Candidates preparing for graduation should submit a completed application for degree to the Registrar s Office and submit a track graduation form to C S Student Services an example of a completed form is available here SECTION 7 CONTACT Please direct all questions concerning the NLP Track to Please note that these course offerings are listed on a provisional basis only and may change from what is listed Check the registrar s website for definitive information The Network Systems Track The Network Systems track is intended for students who wish to develop state of the art knowledge of network systems technologies and the underlying principles protocols and algorithms Networking technologies play a central driving role in shaping the directions of both the IT and communication industries This track will help you develop leading edge knowledge of these technologies SECTION 1 REQUIREMENTS OVERVIEW REQUIRED ELECTIVES CORE TRACK TRACK GENERAL MINIMUM REQUIRED CREDITS 12 3 12 3 COURSES COMS W4115 SEE SECTION 3 SEE SECTION 4 SEE SECTION 5 COMS W4118 TOTAL MINIMUM REQUIRED CREDITS 15 15 30 COURSE AND CREDIT REQUIREMENTS FOR THE NETWORK SYSTEMS TRACK Students must complete at least 30 credits and minimum of 6 elective credits Section 4 must be at the 6000 level The Networking Systems track has two required core courses COMS W4115 Programming Language and Translators and COMS W4118 Operating Systems Students who waive core or required track elective using previous courses may take other Computer Science courses in lieu of waived ones SECTION 2 CORE COURSES The following is a list of Computer Science core courses COMS W4115 Programming Languages Translators COMS W4118 Operating Systems COMS W4156 Advanced Software Engineering CSOR W4231 Analysis of Algorithms COMS W4701 Artificial Intelligence CSEE W4824 Computer Architecture SECTION 3 REQUIRED TRACK COURSES Candidates are required to complete the following course COURSE ID TITLE CSEE W4119 Computer Networks Students who have completed equivalent courses with grades of at least 3 0 may apply these courses to satisfy these requirements and devote more credits to pursue elective courses SECTION 4 ELECTIVE TRACK COURSES Candidates are required to complete four 4 courses out of the following list at least two courses must be 6000 level CS courses COURSE ID TITLE CSEE W4140 Networking Laboratory COMS W4180 Introduction to Network Security COMS W4261 Introduction to Cryptography COMS W4737 Biometrics COMS W4995 VoIP Security COMS W4995 Introduction to Semantic Web COMS W4995 Social Information Networks COMS W4995 Fundamentals of Distributed Systems COMS W4995 Business of Software Delivery COMS E6118 Operating Systems II COMS E6125 Web Enhanced Information Management CSEE E6180 Modeling Performance COMS E6181 Advanced Internet Services COMS E6184 Seminar on Anonymity Privacy COMS E6185 Intrusion and Anomaly Detection Systems COMS E6737 Biometrics COMS E6901 Projects in Computer Science COMS E6998 Practical Cryptography COMS E6998 Challenges in Cloud and Mobile Computing COMS E6998 Web Application Servers Arch Design COMS E6998 Advanced Internet Routing COMS E6998 Search Engine Technology COMS E6998 Content Networking COMS E6998 Network Theory COMS E6998 Virtual Machines COMS E6998 Algorithmic Game Theory COMS E6998 Mobile Computing with iPhone and Android COMS E6998 Next Generation Network Arch COMS E6998 Internet Economics COMS E6998 Network Systems Implementation COMS E6998 Practical Cryptography COMS E6998 Cloud Computing COMS E6998 Content Distribution COMS E6998 Analysis of Social Info Nets COMS E6998 Social Networks Systems Point of View COMS E6998 Cellular Networks Mobile Computation COMS E6998 Econ of Social Networks COMS E6998 Mobile Computing COMS E6998 Data Science Entrepreneurship COMS E6998 Cloud and Mobile Challenges COMS E6998 Cellular Networks Mobile Computing COMS E6998 Software Defined Networking ELEN E4703 Wireless Communications ELEN E6761 Computer Communication Networks ELEN E6770 Next Generation IP Networks ELEN E6771 Next Generation Networks ELEN E6950 Wireless Mobile Nets I ELEN E6951 Wireless Mobile Nets II STAT W4606 Elementary Stochastic Processes ELEN E6771 Next Generation Networks OR substitute with IEOR W4106 IEOR E6704 Queueing Theory and Applications IEOR E6801 Monte Carlo Discrete Event Simulation IEOR E4406 Facilities Location Routing Network Design Computer Science course descriptions are available here SECTION 5 GENERAL ELECTIVES Remaining credits from any qualifying Computer Science graduate course 4000 and 6000 level Students may take up to 3 credits of non technical course approved by the advisor Please complete a non technical approval form and once it is signed forward it to or SECTION 6 GRADUATION Candidates preparing for graduation should submit a completed application for degree to the Registrar s Office and submit a track graduation form to C S Student Services an example of a completed form is available here SECTION 7 CONTACT Please direct all questions concerning the Network System Track to Please note that these course offerings are listed on a provisional basis only and may change from what is listed Check the registrar s website for definitive information The Software Systems Track The Software Systems track is for students who want to pursue knowledge of software development and software systems methodologies and technologies Software plays the key role in practical real world computing systems and applications This track enables students to understand and master classic and current software systems and provides the fundamentals for later self study of future software systems SECTION 1 REQUIREMENTS OVERVIEW REQUIRED ELECTIVES CORE TRACK TRACK GENERAL MINIMUM REQUIRED CREDITS 12 6 6 6 COURSES COMS W4115 SEE SECTION 3 SEE SECTION 4 SEE SECTION 5 COMS W4118 COMS W4156 TOTAL MINIMUM REQUIRED CREDITS 18 12 30 COURSE AND CREDIT REQUIREMENTS FOR THE SOFTWARE SYSTEMS TRACK Students must complete at least 30 credits and out of those 30 credits 6 elective credits Section 4 must be at the 6000 level The Software Systems track has three required core courses COMS W4115 Programming Language and Translators COMS W4118 Operating Systems and COMS W4156 Advanced Software Engineering Students who waive a core course using previous courses may take other Computer Science courses in lieu of waived ones If a required track elective is waived another required track elective must be substituted for a total of 6 points taken at Columbia in required track electives SECTION 2 CORE COURSES The following is a list of Computer Science core courses COMS W4115 Programming Languages Translators COMS W4118 Operating Systems COMS W4156 Advanced Software Engineering CSOR W4231 Analysis of Algorithms COMS W4701 Artificial Intelligence CSEE W4824 Computer Architecture SECTION 3 REQUIRED TRACK COURSES Candidates are required to complete at least two 4000 level courses 6 points selected from the following list of track courses COURSE ID TITLE COMS W4111 Introduction to Databases COMS W4112 Database System Implementation COMS W4117 Compilers and Interpreters COMS W4130 Principles and Practice of Parallel Programming COMS W4170 User Interface Design COMS W4187 Security Architecture and Engineering COMS W4444 Programming and Problem Solving COMS W4460 Principles of Innovation and Entrepreneurship COMS W4995 Topics in Computer Science Fall 13 Distributed Systems Fundamentals Topics in Computer Science 4995 sections must be approved as qualifying software systems track courses by your Software Systems Track Advisor Typically this would mean topics offered by a software systems faculty member or by an affiliated adjunct COMS W4995 Business of Software Delivery is not a technical course thus cannot be taken to satisfy Section 3 SECTION 4 ELECTIVE TRACK COURSES Candidates are required to complete at least two 6000 level courses 6 points selected from the following list of track courses COURSE ID TITLE COMS E6111 Advanced Database Systems COMS E6117 Topics in Programming Languages and Translators COMS E6118 Operating Systems II COMS E6121 Reliable Software COMS E6125 Web Enhanced Information Management COMS E6901 Projects in Computer Science COMS E6998 Topics in Computer Science Fall 13 Search Engine Technology Cloud Computing Concepts Practice Projects in Computer Science 6901 and Topics in Computer Science 6998 courses must be approved as qualifying software systems electives by your Software Systems Track Advisor Typically this would mean topics projects offered by a software systems faculty member or by an affiliated adjunct

    Original URL path: http://www.cs.columbia.edu/education/ms/oldrequirements (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | advisors
    after CS CU Bulletin In The Press News Newsletters Highlights Distinguished Lectures Resources A to Z Adjunct Teaching Computing Jobs Technical Reports Webmail Directions Wiki Copyright FAQ Quick Links Data Science Institute IGERT From Data to Solutions ASCENT Program Faculty Job Opportunities MS Track Advisors 2015 2016 Computational Biology Itsik Pe er Computer Security Steve Bellovin Foundations of Computer Science Xi Chen Machine Learning David Blei Machine Learning Daniel Hsu

    Original URL path: http://www.cs.columbia.edu/education/ms/advisors (2016-02-17)
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  • field is being used for creating static contents. --> Department of Computer Science, Columbia University | Requirements
    can take up to 6 points of COMS E9910 per semester Students who registered for E9910 during the Spring 2007 semester or earlier may however receive credit towards the degree with the advisor s approval Registration I am a US citizen Can I be a part time student If you are a US citizen or a permanent resident of the US it is possible to obtain all or a substantial part of the credit requirement for the master s degree through part time study You must register for at least 3 points each semester How can I find out which courses are offered this Fall and Spring semesters The Registrar s Directory of Classes lists the most updated course information I want to drop a course after the Change of Program period Is that possible A US citizen or a permanent resident can drop a course until the drop deadline late November for Fall and late March for Spring Please keep in mind that even though it is still possible to drop a course you will not get a refund for the course you are dropping after the Change of Program Period If you want to avoid financial penalty for dropping a course please finalize your schedule during the regular registration period or the Change of Program Period This rule also applies to MSGRAs who are funded by the department If you decide to drop a course after the Change of Program period you are personally responsible for the tuition of the course that you are dropping If you have any questions please contact Student Financial Services Kent Hall or If you are an international student you may not be able to drop a course due to the full time registration requirement Please consult Should I register for COMS W4901 or COMS E6901 They are both graduate project courses so I am not sure for which one I should register All MS students should register for COMS E6901 If you have been chosen to work on a project please email and cc your project supervisor She will give you the information you need for registration Can I take on campus courses in the summer The official line for the MS program is that no summer courses are guaranteed to be offered but some are occasionally If the course that you want to take is offered you are allowed to register for it Please visit the Summer Sessions website for more information Credit Transfer Can I transfer graduate credits for courses taken at another university No but you can waive required courses if you have taken similar courses at another institution In order for the waiver to be approved the previous course must be equivalent to what we offer here at Columbia and the grade that you received must be B or higher Waiver requests are submitted through MICE Forms are electronically transferred to the relevant course instructors for approval and you will be notified by email of their decisions If

    Original URL path: http://www.cs.columbia.edu/education/ms/regfaq (2016-02-17)
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