This course involves that you would be required to spend lot of time to read. The contents of this material is very dense and will require a lot of your time. I would advise that you avail yours ...

This graduate-level course is a continuation of Mathematical Methods for Engineers I (18.085). Topics include numerical methods; initial-value problems; network flows; and optimization.

The course schedule gives the chronology of the course as taught by Prof. Alex Himonas at the University of Notre Dame in Fall 2008. The Section column refers to the sections in the course ...

The lectures are at a beginning graduate level and assume only basic familiarity with Functional Analysis and Probability Theory. Topics covered include: Random variables in Banach spaces: Gauss ...

To prepare students for a course in introductory calculus.

Course content: Limits, continuity, the derivative, rules of differentiation, implicit differentiation, parametric curves, related rates, curve sketching, optimization, linear approximations, tr ...

PED 236: Elementary Mathematics is a one semester, 2 credit course. The course consists of sixteen units which includes basic arithmetic operations in integers, indices, logarithm and surd, frac ...

Discrete Mathematics for Computer Science.....

This Unit Focuses an Probability spaces, probability measures and probability distribution for continuous random variables. It gives some basic definition and relevant working examples w ...