Fundamentals of Data Science
| Module title | Fundamentals of Data Science |
|---|---|
| Module code | ECMM444 |
| Academic year | 2020/1 |
| Credits | 15 |
| Module staff | Dr Fabrizio Costa () |
Module description
Data science depends on a solid grounding in mathematics and programming. In this module, you will learn essential mathematical techniques from linear algebra and probability. You will also develop programming skills specific to data analysis, including how to apply the mathematical techniques you have learned as part of computational data analysis procedures. Other computational methods with direct relevance to data science and processing of large datasets will also be included, such as data analysis packages for Python, and optimisation techniques for speeding up large computations.
Overall, this module will ensure you have the core skills and background knowledge that underpin many central topics in data science, including machine learning, statistical modelling, network analysis and computer vision
Module aims - intentions of the module
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
ILO: Personal and key skills
On successfully completing the module you will be able to...
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|
| Credit value | 15 |
|---|---|
| Available as distance learning? | Yes |
