
- Lecturer: NZAYISENGA Marcelin
- Lecturer: Gratien TWAHANYIMPETA
This module provides a good understanding of linear algebra concepts / matrix computations by hand, practical algebraic concepts and methods that are useful in data analysis applications, links between vector space representations and matrices, and between decompositions such as eigenvalue decomposition, singular value decomposition, linear systems, least squares solutions. To provide a working understanding of matrices and vector spaces for later modules to build on and to teach students practical techniques and algorithms for fundamental matrix operations and solving linear equations.
They must also understand the equivalence of linear maps between vector spaces and matrices and be able to row reduce a matrix, compute its rank and solve systems of linear equations. The definition of a determinant in all dimensions will be given in detail, together with applications and techniques for calculating determinants. Students must know the definition of the eigenvalues and eigenvectors of a linear map or matrix, and know how to calculate them.

- Lecturer: NZAYISENGA Marcelin
- Lecturer: Gratien TWAHANYIMPETA
Calculus covers core concepts like limits, derivatives (rates of change), and integrals (areas), explaining how they analyze change, from instantaneous slopes (derivatives) using rules like the power/chain rules, to accumulation (integrals) and their applications in science and engineering, often starting with basic functions and building to multivariable calculus and series.
Key resources include cheat sheets and lecture notes from universities, detailing formulas, rules (power, product, chain), and step-by-step methods like the four-step derivative rule

- Lecturer: NZAYISENGA Marcelin
- Lecturer: Gratien TWAHANYIMPETA
- Lecturer: Kwizera Jean Pierre
- Lecturer: NZAYISENGA Marcelin
- Lecturer: RUHUMULIZA GASPARD
- Lecturer: NZAYISENGA Marcelin
- Lecturer: RUHUMULIZA GASPARD
- Lecturer: NZAYISENGA Marcelin