Course

MATH-611: Scientific programming for Engineers

Lectures in this course (15)

Scientific Programming for Engineers: Introduction to GIT

Covers the basics of scientific programming for engineers, emphasizing the importance of GIT for collaborative work and providing insights into challenges in scientific software development.

Python Basics

Covers Python basics, Git, control structures, functions, file handling, and debugging using PDB.

Design Discussions, Documentation

Explores design discussions and documentation in software development, emphasizing scientific programming and code documentation tools like Doxygen and Sphinx.

Compilation and C++ Basics

Covers the basics of compilation and C++ programming, including variables, functions, loops, and debugging.

GoogleTest, Pytest, Git Submodule/Subtree, Python os.path

Covers Google Test, Pytest, Git submodule/subtree, and Python file manipulation.

Optimization and Templates

Explores optimization in C++ code, algorithmic ideas, code profiling, and template meta-programming.

STL Essentials

Covers the essential concepts of the Standard Template Library (STL) in C++ for efficient data manipulation.

External libraries: Advanced CMake

Explores external libraries integration, advanced CMake features, and Fourier series representation of signals.

Python Complement: Numpy, Scipy, Matplotlib

Covers advanced Python topics like numpy operations, scipy linear algebra, and matplotlib for creating figures.

Object Oriented Programming in Python

Covers object-oriented programming in Python, including classes, objects, inheritance, and error handling with exceptions.

Discrete Fourier Transform and FFTW

Explores Fourier series, Discrete Fourier Transform, FFTW library, and solving differential equations using FFT algorithms.

Eigen and Pybind Libraries

Introduces Eigen and Pybind libraries for linear algebra operations and C++ function binding to Python.

Object Oriented Programming in C++

Introduces object-oriented programming in C++, covering interfaces, classes, inheritance, and polymorphism.

Design Patterns: Elements of Reusable Object-Oriented Software

Explores the principles of design patterns and their role in creating flexible object-oriented code.

Design Patterns: Composite Objects and Array Structures

Explores composite objects, array structures, and design patterns in scientific computing, emphasizing efficient data handling and compute operations.