Mathematical Techniques for Computer Science Applications
CSCIGA.1180
Tuesday 6:008:20.
Warren Weaver Hall room 101.
Professor Ernest Davis
Reaching Me
 Email:
 phone: (212) 9983123
 office: 329 Warren Weaver Hall
Office hours: Wed 10:0012:00, Thu 3:004:00
Tutoring Session
An optional tutoring session will meet Fridays 56 (except July 7, since
there is no class meeting July 4). The instructor will be
Azam Asl. The tutoring session
will meet in room 101, except August 4, when it will meet in room 317.
Textbooks:
Ernest Davis,
Linear Algebra and Probability for Computer Science Applications,
CRC Press, 2012. Please note the
List of Errata .
Amos Gilat,
MATLAB: An Introduction with Applications, Wiley.
Any edition is OK. Inexpensive used copies are available online.
Course code library
Online documentation for MATLAB:
Getting Started with MATLAB
Matlab freeware clones:
GNU Octave
Scilab
Students have occasionally reported incompatibilities with Octave. I have not
received any complaints about Scilab.
You may use Python and NumPy for programming assignments if you want, but
you should make sure that you understand Matlab, since there may be problem
sets and exam questions that involve Matlab.
Class email list
You should be automatically subscribed to the
class email list
If not, go to this link, and subscribe manually.
Prerequisites:
None.
Description
This course gives an introduction to theory, computational techniques, and
applications of linear algebra, probability and statistics. These three
areas of continuous mathematics are critical in many parts of computer
science, including machine learning, scientific computing, computer vision,
computational biology, computational finance,
natural language processing, and computer graphics.
The course will teach a specialized language for mathematical computation,
such as MATLAB, and will discuss how the language can be used for
computation and for graphical output. No prior knowledge of linear algebra,
probability, or statistics is assumed.
Schedule
Date  Topic  Required Reading  Assignment 
Part I: Linear Algebra 
May 23  Matlab Vectors  Chaps 1, 2 

May 30  Matrices  Chap 3 

June 6  Linear algebra  Chap 4 part I  Prog 1 DUE

June 13  Solving linear equations  Chap 5
 Hwk 2 DUE

June 20  Geometry  Chap 6  Prog2 DUE

June 27  Change of basis Discrete Fourier transform
Singular value decomposition  Chap 7  Hwk3 DUE

July 4  INDEPENDENCE DAY NO CLASS

Part II: Probability 
July 11  Basic Probability  Chap 8  Prog3 DUE

July 18  Numerical random variables
 Chap. 9  Hwk4 DUE

July 25  Statistics Monte Carlo methods MLE
 Chap. 11, 12, 14


August 1  Information theory Markov models  Chap 10, 13
 Prog4 DUE Hwk5 DUE

August 8  FINAL EXAM

Requirements
Programming assignments (40% of the grade).
Biweekly exercises (10% of the grade).
Final exam. (50% of the grade).
Assignments
Homeworks and programming assignments are due at the start of class on their
due date. They may be submitted up to 1 week late, with a penalty of 1
point out of 10.
Exercise 1 Not to hand in.
Programming assignment 1. Due June 6
Problem Set 2 . Due June 13
Programming assignment 2. Due June 20
Problem Set 3 . Due June 27
Programming assignment 3. Due July 11
Sample Output for Programming Assignment 3
Problem Set 4 . Due July 18
Programming assignment 4. Due July 25
Problem Set 5 . Due August 1
Final Exam
The final exam will be given August 8, 6:008:20. It will be closed book and
closed notes. A sample exam is on the NYU Clases site.
List of topics for final exam
Students with Disabilities
Academic accommodations are available for students with disabilities.
Please contact the Moses Center for Students with Disabilities (2129984980
or mosescsd@nyu.edu) for further information. Students who are requesting
academic accommodations are advised to reach out to the Moses Center
as early as possible in the semester for assistance.
Cheating
You may discuss any of the assignments with your classmates (or anyone else)
but all work for all assignments must be
entirely your own. Any sharing or copying of assignments will be
considered cheating. By the rules of the Graduate School of Arts and Science,
I am required to report any incidents of cheating to the department.
My policy is that any incident of cheating will result in the
student getting a grade of F for the course.
The second incident, by GSAS rules, will result
in expulsion from the University.