NUMERICAL MATHEMATICS FOR DATA SCIENCE
- Course
- DASC550 - NUMERICAL MATHEMATICS FOR DATA SCIENCE
- Department
- Data Science - English - Master
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 8
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- -
- Prerequisite
- -
Course Description
This course provides an understanding of numerical mathematic applications in data science. The floating-point representation of real numbers, truncation and round off errors, iterative approaches, and convergence are some of the main points in numerical mathematics that are covered in this course. Students will study the most basic and crucial algorithms for the fundamental numerical mathematics problems, such as the solution of algebraic equations, numerical estimation of derivatives and integrals, solution of differential equations, approximation of functions by polynomials and Fourier series and solution of systems of linear algebraic equations. Upon completion of this course, students will be able to formulate and solve problems using mathematical methods and tools, identify, understand, and solve algebraic equations and develop experience with numerical and symbolic mathematical software.
NUMERICAL MATHEMATICS FOR DATA SCIENCE
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