Course Schedule

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• CSCI-GA.2110-​001
  (1007) Programming Languages  Cory Plock T 5:10-7:30PM Additional information: 05/26/2020 - 08/16/2020 (Session One through Two)
  

  Discusses the design, use, and implementation of imperative, object-oriented, and functional programming languages. The topics covered include scoping, type systems, control structures, functions, modules, object orientation, exception handling, and concurrency. A variety of languages are studied, including C++, Java, Ada, Lisp, and ML, and concepts are reinforced by programming exercises.

  
  
  Prerequisites: Students taking this class should already have substantial programming experience.
• CSCI-GA.2340-​001
  MATH-GA 2050
  (1009) Elements Of Discrete Mathematics *  Matthew Harper Langston T 6:00-8:20PM Additional information: 05/26/2020 - 08/16/2020 (Session One through Two)
  Introduction to the central mathematical concepts that arise in computer science. Emphasis is on proof and abstraction. Topics include proof techniques; combinatorics; sets, functions, and relations; discrete structures; order of magnitude analysis; formal logic; formal languages and automata.
  
  Prerequisites: May not be taken by students who have received a grade of B or better in CSCI-GA 1170.
• CSCI-UA.0002-​001
  (2539) Intro To Computer Programming (No Prior Experience)  Amos Bloomberg MTWR 11:10-1:15PM Additional information: 05/26/2020 - 07/5/2020 (Session One)
  

  An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0002-​002
  (2267) Intro To Computer Programming (No Prior Experience)  Nathan Hull MTWR 11:10-1:15PM Additional information: 07/6/2020 - 08/16/2020 (Session Two)
  

  An introduction to the fundamentals of computer programming, which is the foundation of computer science. Students design, write, and debug computer programs. No knowledge of programming is assumed.

  
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with any programming experience should consult with the department before registering. Students who have taken or are taking Introduction to Computer Science (CSCI-UA 101) will not receive credit for this course. Does not count toward the computer science major; serves as the prerequisite for students with no previous programming experience who want to continue into CSCI-UA 101 and pursue the major.
• CSCI-UA.0004-​001
  (2451) Intro to Web Design & Computer Principles  Amos Bloomberg MTWR 2:10-4:15PM Additional information: 05/26/2020 - 07/5/2020 (Session One)
  Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
• CSCI-UA.0004-​002
  (2268) Intro to Web Design & Computer Principles  Nathan Hull MTWR 2:10-4:15PM Additional information: 07/6/2020 - 08/16/2020 (Session Two)
  Introduces students to both the practice of web design and the basic principles of computer science. The practice component covers not only web design but also current graphics and software tools. The principles section includes an overview of hardware and software, the history of computers, and a discussion of the impact of computers and the Internet.
  
  Prerequisites: Three years of high school mathematics or equivalent. No prior computing experience is assumed. Students with computing experience should consult with the department before registering.
• CSCI-UA.0101-​001
  (2502) Intro To Computer Science  Douglas Moody TR 2:10-4:15PM Additional information: 05/26/2020 - 08/16/2020 (Session One through Two)
  How to design algorithms to solve problems and how to translate these algorithms into working computer programs. Experience is acquired through projects in a high-level programming language. Intended primarily for computer science majors but also suitable for students of other scientific disciplines. Programming assignments.
  
  Prerequisites: Introduction to Computer Programming (CSCI-UA 2) or departmental permission assessed by placement exam.
• CSCI-UA.0102-​001
  (2527) Data Structures  Douglas Moody TR 5:45-7:50PM Additional information: 05/26/2020 - 08/16/2020 (Session One through Two)
  Use and design of data structures, which organize information in computer memory. Stacks, queues, linked lists, binary trees: how to implement them in a high-level language, how to analyze their effect on algorithm efficiency, and how to modify them. Programming assignments.
  
  Prerequisites: Introduction to Computer Science (CSCI-UA 101).
• CSCI-UA.0475-​001
  (5911) Predictive Analytics  Anasse Bari TR 5:45-7:50PM Additional information: 05/26/2020 - 08/16/2020 (Session One through Two)
  

  Predictive analytics is the art and science of extracting useful information from historical data and present data for the purpose of predicting future trends. In this course, students will be introduced to the phases of the analytics life-cycle and will gain an understanding of a variety of tools and machine learning algorithms for analyzing data and discovering forward insights. Several techniques will be introduced including: data preprocessing techniques, data reduction algorithms, data clustering algorithms, data classification algorithms, uplifting algorithms, association rules, data mining algorithms, recommender systems, and more. This course aims to provide students with skills of the new generation of data scientists that will allow them to structure, analyze and derive useful insights from data that could help make better decisions.

  
  
  Prerequisites: Computer Systems Organization (CSCI-UA 201), Basic Algorithms (CSCI-UA 310), and Linear Algebra (MATH-UA 140) or Honors Linear Algebra (MATH-UA 148).

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  Indicates controlled enrollment (permission number required for registration). Contact your program advisor.
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  Indicates controlled enrollment (permission number required for registration). Contact Santiago Pizzini (pizzini@cs.nyu.edu).
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  Indicates controlled enrollment (permission number required for registration). Contact the instructor.