Determine the characteristics of a Dataset, analyzing it and interpreting the necessary preprocessing to be performed” 

This Postgraduate certificate will present specialized knowledge about the tools used in Data Science to extract and analyze company information. This work is essential for the professional development of computer engineers who wish to provide realistic solutions to daily problems in their work environment.

Moreover, upon completing the program, students will be able to develop a critical thinking in face of the applied strategies, being able to discern in each case the most appropriate solution and explain, in a reasoned way, the results obtained in the different metrics.

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.

Transform data into information, adding value and enabling the generation of new knowledge” 

This Postgraduate certificate in Tools in Data Science contains the most complete and up-to-date academic program on the market. The most important features of the program 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 the self-assessment process can be carried out 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

Generate hypotheses to solve practical cases and validate them using metrics in a critical and reasoned manner”

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. This will be done with the help of an innovative, interactive video system developed by renowned experts with extensive experience using the Tools in Data Science.

Analyze the most appropriate techniques for each data set and examine the results obtained"

Develop the skills to convert data into information from which knowledge can be extracted"

The syllabus provides a theoretical perspective on the most advanced techniques that have served as a basis for analyzing, visualizing and extracting important company data. This will be made possible by means of a series of case studies that will illustrate the course contents. Consequently, the objectives of the program to train professional, integral and prestigious engineers will be fulfilled.

Evaluate the results in an analytical way, understanding the impact of the chosen strategy on the various metrics”

Module 1. Data Science Tools

1.1. Data Science

1.1.1. Data Science
1.1.2. Advanced Tools for Data Scientists  

1.2. Data, Information and Knowledge

1.2.1. Data, Information and Knowledge 
1.2.2. Types of Data
1.2.3. Data Sources

1.3. From Data to Information 

1.3.1. Data Analysis
1.3.2. Types of Analysis
1.3.3. Extraction of Information from a Dataset 

1.4. Extraction of Information Through Visualization

1.4.1. Visualization as an Analysis Tool
1.4.2. Visualization Methods 
1.4.3. Visualization of a Data Set

1.5. Data Quality

1.5.1. Quality Data
1.5.2. Data Cleaning 
1.5.3. Basic Data Pre-Processing

1.6. Dataset

1.6.1. Dataset Enrichment
1.6.2. The Curse of Dimensionality
1.6.3. Modification of Our Data Set

1.7. Unbalance 

1.7.1. Classes of Unbalance
1.7.2. Unbalance Mitigation Techniques
1.7.3. Balancing a Dataset

1.8. Unsupervised Models 

1.8.1. Unsupervised Model
1.8.2. Methods
1.8.3. Classification with Unsupervised Models

1.9. Supervised Models

1.9.1. Supervised Model
1.9.2. Methods
1.9.3. Classification with Supervised Models

1.10. Tools and Good Practices

1.10.1. Good Practices for Data Scientists
1.10.2. The Best Model 
1.10.3. Useful Tools

With this program, you will be able to develop a series of indispensable skills for industrial engineers specialized in this field”