| Educational guide School of Engineering |
english |
| Biomedical Data Science (2022) |
 Subjects |
| SCIENTIFIC PROGRAMMING |
| Contents |
| IDENTIFYING DATA | 2023_24 |
| Subject | SCIENTIFIC PROGRAMMING | Code | 17705105 | |||||
| Study programme |
|
Cycle | 2nd | |||||
| Descriptors | Credits | Type | Year | Period | ||||
| 4.5 | Compulsory | First | 1Q |
|||||
| Competences | Learning outcomes | Contents |
| Planning | Methodologies | Personalized attention |
| Assessment | Sources of information | Recommendations |
| Topic | Sub-topic |
| Introduction and basic tools | Environment for scientific computing. Introduction to Operating Systems and unix shell. Code management, collaborative coding, revision control and documentation. Application deployment and OS-level virtualization through containerization |
| Statistical Programming and tidy data | Introduction to statistical programming. Introduction to R. Data management in R. Advanced data manipulation, R programming with tidyverse. |
| Tools for visualization | Statistical Visualization. Grammar-based visualization and reactive visualization. |
| Introduction to functional programming and high performance programming. | Introduction to functional programming for scientific computation. Introduction to python. Introduction to numerical calculus through Numpy. Introduction to Scientific Python (SciPy). Introduction to Pandas. Data visualization, Grammar-based visualization and reactive visualization in python. |
| Application challenges | Application challenges. Creation and analysis of biomedical data dashboards. Introduction to multivariate data, and application to EDA, introduction to dimensionality reduction techniques. |
