Learn from the best, the essential data analysis techniques to bring to your company the capabilities of this type of work"

This postgraduate diploma will give the student a complete vision of the latest technologies used in Data Science and Artificial Intelligence. A very complete compilation of advances, novelties and work tools that will take students through the most intensive path, to prepare them for the current star profile.

Throughout this program you will learn everything necessary to analyze data, with the development of the various existing techniques. In addition, TECH will show how to capture the information and how to store it properly in each case.

Learn from the best with the most innovative educational system and with the security and solvency of the best online university right now. 

A complete update that will provide you with the working capacity of a specialist in the field”

This postgraduate diploma in Data Analysis Techniques  contains the most complete and up-to-date educational program on the market. The most important features of the program include:

• Practical case studies presented by experts 
• The graphic, schematic, and 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

All aspects necessary to use data visualiazation techniques, in a high quality training course" 

The program’s teaching staff includes professionals from 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 an immersive training program designed 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 professional will be assisted by an innovative interactive video system created by renowned and experienced experts.  

This training has the best teaching material available online or downloadable, to facilitate your study and effort management"

A very complete program, created with a strong focus on quality and bringing our students to the highest level of skill"

The objectives of this postgraduate diploma were established with a basis on realistic and necessary goals for a professional in the sector. Gradually, students will be able to verify their learning and progress in the mastery of the contents so that, at the end, they will have finished a complete process of professional growth.

Realistic, achievable and high-impact goals for your professional training"

General Objectives

• Analyze the data produced and draw conclusions using statistical tools to make the most appropriate decisions at all times 
• Learn the introductory concepts of statistics; statistical reasoning; represent relationships between different variables, among others 
• Delve deep into the principles of probability that are the basis for inferential statistics, which will allow you to contrast conjectures (hypothesis contrasts) on how a certain population is 
  Understand information sources and the value they bring to the creation of new innovative business models 
• Know and use statistical tools to solve problems in the field of Big Data
• Know how the combination of all the data flowing through the Internet can be combined to define new strategies applicable to different industrial, business, financial sectors, etc., in different areas, such as energy, health, economy or communication 
• Learn the different techniques for the analysis and exploitation of data, visualization and interaction techniques, all closely linked to the role of the Data Scientist and their contribution in the
• anticipation and vision for the execution of innovation processes that allow managing changes efficiently in organizations 
• Assimilate concepts, techniques, methodologies and knowledge of languages that will be useful to apply them in big data mining 
• Delve deep into Artificial Intelligence algorithms and techniques such as decision trees, classification and association rules, neural networks or Deep Learning
• Apply data mining tools to solve learning problems, interpreting the results obtained, as well as the ability to design an intelligent system capable of inferring new knowledge 
• Get to know databases, from traditional to unstructured, where data requiring other types of processing, such as audio or video streams, will be stored 
• Learn the importance of having cloud computing for processing large volumes of data and how all this Big Data can be ingested into tools that allow us to obtain and infer patterns in seemingly unrelated data 
• Delve deep into the Hadoop framework and its file system HDFS (Hadoop Distributed File System), which provides systems and techniques for distributed storage and processing of large amounts of data 
• Know how to apply the tools for parallel processing: MapReduce, devised by Google, or Spark, now under the auspices of the Apache Software Foundation
• Understand how high-performance, low-latency platforms work for real-time manipulation of data sources that need to respond to service demands operating in the millisecond range 

Specific Objectives

Module 1. Data Analysis and Interpretation

• Know the different theories for data analysis and interpretation
• Identify the most common descriptors for a dataset
• Understand and evaluate the applicability of different descriptors to an existing dataset
• Learn about hypothesis testing and its applicability to the world of data analysis
• Learn how to interpret the different existing regression techniques

Module 2. Data and AI Analysis Techniques

• Know the different techniques for data analysis
• Design the joint strategy of statistical and artificial intelligence techniques for the development of descriptive and predictive systems applied to the reality of a dataset
• Understand the operation and characteristics of common mass data processing techniques
• Identify techniques oriented to statistical analysis, artificial intelligence and massive data processing

Module 3. Data Analysis Tools

• Know the environments most used by Data Scientists
• Know how to process data in different formats from different sources
• Learn from the need to guarantee the veracity of the data as a prior step to its processing
• Identify new technologies as pedagogical tools in the communication of the different business realities
• Know the latest trends in the creation of intelligent entities based on deep learning and neural networks

Module 4. Database Management and Data Parallelization Systems

• Know the artificial intelligence techniques applicable for massively parallelized data processing on a given data set and according to previously defined requirements
• Know how to manage large volumes of data in a distributed manner
• Understand the operation and characteristics of common mass data processing techniques
• Identify commercial and free software tools oriented to statistical analysis, artificial intelligence and massive data processing

A stimulating journey of professional growth designed to keep you interested and motivated throughout the program”