Launch the main phases in data science processes: graphical representation for exploratory analysis” 

This postgraduate certificate will analyze the theoretical bases that help computer engineers to make the most appropriate graphical representations when using Data Science as an analytical technique. Therefore, special emphasis will be placed on the correct way to represent and interpret data in order to identify past errors or inefficient tactics to anticipate the future.

The entire program is composed of a series of case studies that will favor the learning of students who seek to further advance their professional careers and challenge themselves to achieve excellence. Consequently, there will be examples of new technologies for data visualization, such as intelligent systems or reality visualization systems.  

All this will be feasible thanks to a 100% online program, which adapts to the daily needs of its students. You will only need a device with an Internet connection to start developing a complete professional profile with international projection.

Establish the most used graphic representations  in different fields” 

This postgraduate certificate in Stochastic Phenomena Predictability and Analysis 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  
• Access to content from any fixed or portable device with an Internet connection  

The online format will enable the program to adapt to you. Choose the best time to watch a class and continue training in your field of interest” 

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.  

The design of this program focuses on Problem-Based Learning, which means the student must try to solve the different real-life situations of that arise throughout the academic program. This will be done with the help of an innovative, interactive video system developed by renowned experts with extensive personal training experience.

This program will develop the formulation and basic properties of univariate time series models"

It includes a series of case studies to perfectly understand univariate models"

The knowledge provided on this program will help computer engineers gain specialized knowledge of time series models, which will facilitate the analysis of stochastic phenomena that develop over time and hinder the company work. To that end, TECH has established the following general and specific objectives:  

Apply dynamic regression models and the methodology used to build such models from observed series”

General Objectives

• Analyze the benefits of applying data analytic techniques in every company department  
• Develop the basis for understanding the needs and applications of each department  
• Generate specialized knowledge to select the right tool 
• Propose techniques and objectives in order to be as productive as possible according to the department 

Specific Objectives

• Analyze time series 
• Develop the formulation and basic properties of univariate time series models 
• Examine the methodology of modeling and prediction of real time series 
• Assess univariate models including outliers 
• Apply dynamic regression models and apply the methodology for the construction of such models from observed series 
• Address the spectral analysis of univariate time series, as well as the fundamentals related to periodogram-based inference and interpretation 
• Estimate the probability and trend in time series for a given time horizon  

Univariate models will help you build a simple model for data analysis”