While there are many applied mathematics techniques and concepts that are useful (and used) in Data Science, this course focus on the basics of those based on linear algebra and calculus, as they underlie many of the most important applications and algorithms: Matrix algebra, Matrix decompositions.
Basic competences:
To acquire and understand the knowledges that provide the chance of being original in developing or applying ideas, in particular in a research environment.
The students to acquire the learning skills that allow them to keep learning in a self-oriented and autonomous way.
General competences:
To apply the basic theory, techniques, and tools from information research, including data collect, data storage and data analysis, specially for big data, as a basis to apply and develop such techniques to particular problems.