Difference between revisions of "Isc3313 schedule"
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| − | ( [[isc3313_syllabus | Syllabus]] | [[isc3313_schedule | Schedule]] | [[isc3313_lectures | Lectures]] ) | + | ([[ISC-3313 | Overview]] | [[isc3313_syllabus | Syllabus]] | [[isc3313_schedule | Schedule]] | [[isc3313_lectures | Lectures]] | [[isc3313_assign | Assignments]] | [[isc3313_project | Project]] | [http://www.peterbeerli.com/classdata/ISC3313/codes Code] | [[isc3313_misc | Misc]]) |
| − | I. | + | I. Components of Scientific Computing<br> |
| + | 1. Syllabus and introduction<br> | ||
| + | 2. UNIX basics<br> | ||
II. A simple example - Using a Monte Carlo approach to approximate problems<br> | II. A simple example - Using a Monte Carlo approach to approximate problems<br> | ||
| − | 1. | + | 1. Working C++ programming projects<br> |
| − | + | 2. Introduction to C++<br> | |
| − | + | 3. Algorithm development (Monte Carlo Integration)<br> | |
| − | + | 4. Program testing and documentation<br> | |
| − | + | 5. Visualization and analysis of results<br> | |
| − | |||
| − | III. Solving | + | III. Solving non-linear equations<br> |
| − | 1.Description of problem and some simple algorithms<br> | + | 1. Description of problem and some simple algorithms<br> |
2.Iterative methods, required accuracy of result<br> | 2.Iterative methods, required accuracy of result<br> | ||
| − | 3.Implementation of the Bisection method<br> | + | 3. Implementation of the Bisection method<br> |
| − | 4.Program testing and documentation<br> | + | 4. Program testing and documentation<br> |
IV.Object oriented programming concepts in detail<br> | IV.Object oriented programming concepts in detail<br> | ||
using the non-linear equation problem and implementing more methods<br> | using the non-linear equation problem and implementing more methods<br> | ||
| − | 1.Encapsulation<br> | + | 1. Encapsulation<br> |
2.Inheritance<br> | 2.Inheritance<br> | ||
| − | 3.Polymorphism | + | 3. Polymorphism<br> |
| − | |||
| − | V. Operations on vectors and matrices<br> | + | V. Operations on vectors and matrices (February)<br> |
| − | 1.Development of general functionality that is usable in many places<br> | + | 1. Development of general functionality that is usable in many places (a class 'Rational')<br> |
| − | 2.Vector and Matrix operations<br> | + | 2. Vector and Matrix operations<br> |
| − | 3.Vector norms | + | 3. Vector norms<br> |
| − | |||
| − | VI. Polynomial interpolation of data<br> | + | VI. Polynomial interpolation of data (March) <br> |
| − | 1.Description of problems and (biological) applications<br> | + | 1. Description of problems and (biological) applications<br> |
| − | 2.Algorithms: Lagrangian interpolation in detail<br> | + | 2. Algorithms: Lagrangian and Newton interpolation in detail<br> |
| − | 3.Implementation to fit a set of data<br> | + | 3. Implementation to fit a set of data<br> |
| − | 4.Piecewise interpolation<br> | + | 4. Piecewise interpolation<br> |
| − | 5.Implementation and visualization | + | 5. Implementation and visualization of piecewise interpolation<br> |
| − | VII.Solving ordinary differential equations systems<br> | + | VII.Solving ordinary differential equations systems (April)<br> |
| − | 1.Description of | + | 1. Simple ODE solved using Euler's method |
| − | + | 2. ODE solved using Runge-Kutta method | |
| − | + | 3. Multipoint methods | |
| − | + | 4. Description of a two-equation system: Lotka-Volterra Predator-Prey system<br> | |
| − | + | 5. Algorithms and implementation<br> | |
| + | 6. Visualization of results<br> | ||
VIII. Markov chain Monte Carlo Integration<br> | VIII. Markov chain Monte Carlo Integration<br> | ||
| − | 1.Description of method<br> | + | 1. Description of method<br> |
| − | 2.Example application<br> | + | 2. Example application<br> |
| − | 3.Implementation <br> | + | 3. Implementation <br> |
| − | 4.Testing and visualization of results<br> | + | 4. Testing and visualization of results<br> |
| − | IX.Capstone project<br> | + | IX. Capstone project<br> |
Latest revision as of 13:08, 29 August 2016
( Overview | Syllabus | Schedule | Lectures | Assignments | Project | Code | Misc)
I. Components of Scientific Computing
1. Syllabus and introduction
2. UNIX basics
II. A simple example - Using a Monte Carlo approach to approximate problems
1. Working C++ programming projects
2. Introduction to C++
3. Algorithm development (Monte Carlo Integration)
4. Program testing and documentation
5. Visualization and analysis of results
III. Solving non-linear equations
1. Description of problem and some simple algorithms
2.Iterative methods, required accuracy of result
3. Implementation of the Bisection method
4. Program testing and documentation
IV.Object oriented programming concepts in detail
using the non-linear equation problem and implementing more methods
1. Encapsulation
2.Inheritance
3. Polymorphism
V. Operations on vectors and matrices (February)
1. Development of general functionality that is usable in many places (a class 'Rational')
2. Vector and Matrix operations
3. Vector norms
VI. Polynomial interpolation of data (March)
1. Description of problems and (biological) applications
2. Algorithms: Lagrangian and Newton interpolation in detail
3. Implementation to fit a set of data
4. Piecewise interpolation
5. Implementation and visualization of piecewise interpolation
VII.Solving ordinary differential equations systems (April)
1. Simple ODE solved using Euler's method
2. ODE solved using Runge-Kutta method
3. Multipoint methods
4. Description of a two-equation system: Lotka-Volterra Predator-Prey system
5. Algorithms and implementation
6. Visualization of results
VIII. Markov chain Monte Carlo Integration
1. Description of method
2. Example application
3. Implementation
4. Testing and visualization of results
IX. Capstone project
