MACHINE LEARNING
While business intelligence provides advanced tools for the analysis of large volumes of information, data mining techniques go one step further and automatically allow the discovery of interesting information hidden in the enormous labyrinth that data has become.
This is why companies increasingly need professionals specialised in this area, capable of detecting patterns in the data that help them make intelligent decisions about complex problems.
With this course, students will be able to understand how data mining works, understanding how it applies algorithms to predict trends, identify hidden patterns, create rules, detect anomalies or find dependencies between different variables.
Discover the key modules and concepts
INTRODUCTION AND GENERAL CONCEPTS
- Concept of Data Mining.
- Types of data exploited.
- Application tasks.
- Relationship with other disciplines.
- Data Mining Methodologies.
- Data Mining Techniques.
- Case studies.
PREDICTION TECHNIQUES
- Introduction.
- Classification.
- Regression.
GROUPING TECHNIQUES
- Introduction.
- Measures of distance and similarity.
- Different approaches to clustering.
- Methods based on partitioning.
- Hierarchical methods.
ASSOCIATION TECHNIQUES
- Introduction.
- Association rules.
- A priori algorithm.
- Measures of interest.
admission process
Description
In today's world, the proliferation of data has become invaluable to companies. This Course in Data Mining and Machine Learning is an essential opportunity to understand and take advantage of this resource to achieve better results in the company.
With more than 2.5 quintillion bytes of data generated daily, the ability to extract meaningful insights has become imperative for organisations. Therefore, this programme provides you with the necessary skills to explore patterns, predict trends and make informed decisions.
Indeed, the applicability of Data Mining and Machine Learning is ubiquitous. With more than 70% of companies considering that data analytics significantly improves decision making, this course will equip you with the tools to excel in today's business world, where the ability to extract knowledge from data is a key differentiator.
Objectives
- Master the basic concepts of Data Mining and its relationship with other systems or concepts such as Data Warehouse, Business Intelligence, Big Data, etc.
- Apply the main methodologies and techniques of knowledge extraction to different problems: classification, regression, clustering, association rules...
- Use Data Mining software in a basic way.
- Contextualise the technological tools and advanced methods available to us to improve customer relations at all stages: acquisition, pre-sales, sales and post-sales relations.
- Take advantage of effective and modern ways of collecting data, advanced information analysis, segmentation and other advanced marketing techniques.
Methodology
ENAE uses an active and participative methodology, ‘learning by doing’, which alternates the presentation of concepts, techniques and methods of analysis with the development of practical cases reflecting real business situations.
By promoting teamwork, the aim is to achieve the integration of all members and to resolve the cases presented more effectively, through the exchange of different points of view, opinions and experiences. Students will learn from the trainers but also from the professional experiences of their classmates.
