DESCRIPTION
The era of big data and artificial intelligence has brought with it new ways of working that require us to be in continuous training. On the one hand, more and more difficulties arise when accessing data and dealing with large volumes of data, while on the other hand, it is increasingly essential to resort to more sophisticated programming and techniques for data analysis. This course aims to provide an introduction to the main methods of data science from a practical perspective and focused on the use of Python. It covers the fundamental aspects of basic programming using scripts and notebooks, new sources of information and forms of data retrieval, the main data processing processes and their analysis and generation of visualisations. All of this is also accompanied by recent artificial intelligence tools that offer constant support and programming support, bringing it closer than ever to all users.
STRUCTURE
Module 1 – Current context and relevance of data science
- The rise of big data and artificial intelligence.
- Current challenges in accessing and handling large volumes of data.
Module 2 – First steps with Python
- Introduction to the Python programming language.
- Basic tools: scripts and notebooks.
- Basic Python programming: structures, functions and essential libraries.
Module 3 – Sources of information and data retrieval
- Techniques and methods for data extraction.
- Introduction to data cleaning and data preprocessing.
Module 4 – Data processing and data analysis with Python
- Exploratory data analysis: descriptive statistics and analysis techniques.
- Introduction to advanced techniques.
- Assistance tools based on artificial intelligence.
Module 5 – Data visualisation
- Fundamentals of data visualisation.
- Using Python libraries to generate graphs and visualisations.