MATH-250 / 5 credits

Teacher: Kressner Daniel

Language: English


Summary

Construction and analysis of numerical methods for the solution of problems from linear algebra, integration, approximation, and differentiation.

Content

Representation of numbers on computers
Interpolation, numerical integration, and differentiation
Direct and iterative methods for the solution of large systems of equations
Fourier transform and data compression

 

Keywords

numerical algorithms
numerical linear algebra

 

Learning Prerequisites

Required courses

Analysis I and II
Linear Algebra

 

Recommended courses

Elements of scientific programming

 

Learning Outcomes

By the end of the course, the student must be able to:

  • Choose a convenient method to solve a specific problem
  • Interpret the computational results in view of the existing theory
  • Estimate numerical errors
  • Apply numerical algorithms to solve specific problems

Transversal skills

  • Use a work methodology appropriate to the task.
  • Give feedback (critique) in an appropriate fashion.
  • Use both general and domain specific IT resources and tools
  • Access and evaluate appropriate sources of information.

Teaching methods

Ex cathedra lectures and exercises in the classroom and on the computer

 

Expected student activities

Attendance of lectures
Doing exercises and homeworks
Implementing simple programming tools
Solving basic applied mathematics problems

 

Assessment methods

Form of examination:
17% project or homework. 83% exam.

 

Resources

Bibliography

Detailed lecture notes accompanying the course will be provided.

Moodle Link

In the programs

  • Semester: Spring
  • Exam form: Written (summer session)
  • Subject examined: Advanced numerical analysis I
  • Courses: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Type: mandatory

Reference week

Thursday, 14h - 16h: Lecture CE15

Friday, 10h - 12h: Exercise, TP CO020
CO021

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