Important concepts in scientific computing such as profiling and timing, parallelisation, floating-point arithmetic, complex numbers, machine epsilon.

Solution of non-linear equations with Newton-Raphson method, numerical solution of ODEs using explicit and implicit methods, some circuit simulation examples, numerical solution of Poisson`s equation, some examples of optimisation methods.

Solving linear systems of equations, singular value decomposition, condition number, and rank of a matrix.

Public-domain software tools such as Python, Octave, Maxima, useful libraries for numerical work such as BLAS and LAPACK, and their use with respect to the topics listed above.