MATH-458: Programming concepts in scientific computing

Lectures in this course (12)

Covers the basics of scientific computing in C++, including object-oriented programming and specific techniques.

Covers the basics of GIT, including cloning, committing modifications, managing branches, and using remotes.

Explores the Eigen library for linear algebra, covering vectors, matrices, arrays, memory management, reshaping, and per-component operations.

Covers flow control concepts and file input/output operations, including loops, conditions, and handling command line arguments.

Covers the process of making scientific software and discusses rules and requirements for related projects.

Covers compilation, linking, external libraries, Doxygen documentation, and Google Test for C++ unit testing.

Covers pointers in C++, memory addresses, dynamic allocation, arrays, and memory management techniques.

Covers blocks, functions, and references in C++, including scope, variables, function usage, interfaces, pointers, and references.

Covers the fundamental concepts of classes and objects in C++.

Covers inheritance, polymorphism, and casting in object-oriented programming, emphasizing code factorization and generic object manipulation.

Introduces templates in programming, covering functions, classes, type matching, and meta-programming.

Covers the STL in C++, smart pointers, and error management including exceptions and STL exception classes.

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