Developing and perfecting intelligent systems is essential to automate in-company information analysis” 

This Postgraduate certificate will develop student analytical skills in order to move from unstructured data models to automating the data mining process. To this end, a distinction will be made between the different learning techniques used in developing intelligent systems, such as machine learning, classification and regression algorithms.  

As the program progresses, the theory of neural networks, a computational system composed of a large number of simple and interconnected elements that help to process information by means of their dynamic state, will be studied in depth. The result will be a computational model evolved to adapt to the needs of current computer engineering. 

The entire program is comprised of a series of case studies that will help computer engineers who are looking to advance their careers and challenge themselves to achieve excellence.  

Find an innovative solution to a company's problems by automating tedious processes” 

This Postgraduate certificate in Design and Development of Intelligent Systems in Data Science contains the most complete and up-to-date academic program on the market. The most important features include:  

• Practical cases studies are presented by experts in Engineering in data analysis
• The graphic, schematic, and eminently practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice
• Practical exercises where self-assessment can be used to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

Gain specialized knowledge about different machine learning techniques to automate tasks” 

The program’s teaching staff includes professionals from the sector who contribute their work experience to this training program, as well as renowned specialists from leading societies and prestigious universities.   

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive training programmed to train in real situations.   

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year. For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts. 

Learn about the different algorithms that help form neural models in intelligent systems"

This program is available in an online format, which facilitates student training"

It is essential for computer engineers to have the most updated knowledge of the Design and Development of New Intelligent Data Science Systems and, for that purpose, this Postgraduate certificate has been designed to provide all the relevant information on this topic, such as becoming familiar with the different types of learning, algorithms and mining processes. Thus will the objectives of the program to train professional, integral and prestigious engineers be fulfilled. 

It's time to take your career a step further and develop a program that suits the company's big data”

Module 1. Design and Development of Intelligent Systems

1.1. Data Pre-Processing

1.1.1. Data Pre-Processing
1.1.2. Data Transformation
1.1.3. Data Mining

1.2. Machine Learning

1.2.1. Supervised and Unsupervised Learning
1.2.2. Reinforcement Learning
1.2.3. Other Learning Paradigms

1.3. Classification Algorithms

1.3.1. Inductive Machine Learning
1.3.2. SVM and KNN
1.3.3. Metrics and Scores for Ranking

1.4. Regression Algorithms

1.4.1. Lineal Regression, Logistical Regressiona and Non-Lineal Models
1.4.2. Time Series
1.4.3. Metrics and Scores for Regression

1.5. Clustering Algorithms

1.5.1. Hierarchical Clustering Techniques
1.5.2. Partitional Clustering Techniques
1.5.3. Metrics and Scores for Clustering

1.6. Association Rules Techniques

1.6.1. Methods for Rule Extraction
1.6.2. Metrics and Scores for Association Rule Algorithms

1.7. Advanced Classification Techniques. Multiclassifiers

1.7.1. Bagging Algorithms
1.7.2. Random “Forests Sorter”
1.7.3. “Boosting” for Decision Trees

1.8. Probabilistic Graphical Models

1.8.1. Probabilistic Models
1.8.2. Bayesian Networks. Properties, Representation and Parameterization
1.8.3. Other Probabilistic Graphical Models

1.9. Neural Networks

1.9.1. Machine Learning with Artificial Neural Networks
1.9.2.  Feedforward Networks

1.10. Deep Learning

1.10.1. Deep Feedforward Networks
1.10.2. Convolutional Neural Networks and Sequence Models
1.10.3. Tools for Implementing Deep Neural Networks

Discover all the possible applications and the great impact Intelligent Systems can have on a company”