Enroll now and acquire new skills in Advanced Forecasting Techniques quickly and in a 100% online modality" 

Mastering advanced forecasting techniques is essential for any engineer seeking to improve their skills and increase their value in the marketplace. The ability to predict accurate results can help make informed decisions, reduce risk and optimize efficiency on projects of any size or complexity.  

For this reason, TECH has designed a Diploma in Advanced Forecasting Techniques in order to be able to exercise their work as specialists, with the highest possible efficiency and quality. Thus, throughout this program, aspects such as the General Linear Regression Model, Parameter Estimation in a Nonlinear System, or Lasso Regression will be addressed. 

All this, through a convenient 100% online modality that allows students to organize their schedules and studies, combining them with their other day-to-day work and interests. In addition, this degree has the most complete theoretical and practical materials on the market, which facilitates the student's study process and allows them to achieve their objectives quickly and efficiently. . 

Become an expert in the General Linear Regression Model in only 6 weeks and with total freedom of organization" 

This Postgraduate certificate in Advanced Prediction Techniques contains the most complete and up-to-date program on the market. The most important features include:  

• The development of case studies presented by experts in Advanced Prediction Techniques
• The graphic, schematic and eminently practical contents of the book provide sporting and practical information on those 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 

Have access to all the content on Regression Ridge or Elasticnet from day one and with any device with internet connection, be it tablet, mobile or computer" 

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

Its 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 education programmed to learn in real situations.  

The design of this program focuses on Problem-Based Learning, by means of which the professional must try to solve the different professional practice situations that are presented throughout the academic course. For this purpose, the student will be assisted by an innovative interactive video system created by renowned experts.   

Delve into essential aspects such as statistical inference in non-linear regression, from the comfort of your home, 24 hours a day"

Achieve professional success in one of the most promising areas of Computational Statistics, thanks to TECH and the most innovative teaching materials"

The structure and all the didactic resources of this curriculum have been designed by the renowned professionals that make up TECH's team of experts in this area of engineering. These specialists have used their extensive experience and state-of-the-art knowledge to create practical and completely up-to-date content. All this, based on the most efficient pedagogical methodology, TECH Relearning. 

Improve and renew your knowledge of Computational Statistics, thanks to the most innovative teaching materials and a wide variety of additional content available on the Online Campus" 

Module 1. Advanced Prediction Techniques 

1.1. General Linear Regression Model 

1.1.1. Definition 
1.1.2. Properties  
1.1.3. Examples: 

1.2. Partial Least Squares Regression 

1.2.1. Definition 
1.2.2. Properties  
1.2.3. Examples: 

1.3. Principal Component Regression  

1.3.1. Definition 
1.3.2. Properties  
1.3.3. Examples: 

1.4. RRR Regression 

1.4.1. Definition 
1.4.2. Properties  
1.4.3. Examples: 

1.5. Ridge Regression 

1.5.1. Definition 
1.5.2. Properties  
1.5.3. Examples: 

1.6. Lasso Regression 

1.6.1. Definition 
1.6.2. Properties  
1.6.3. Examples: 

1.7. Elasticnet Regression 

1.7.1. Definition 
1.7.2. Properties  
1.7.3. Examples: 

1.8. Non-Linear Prediction Models 

1.8.1. Non-Linear Regression Models
1.8.2. Non-Linear Least Squares 
1.8.3. Conversion to a Linear Model 

1.9. Parameter Estimation in a Non-Linear System 

1.9.1. Linearization 
1.9.2. Other Parameter Estimation Methods 
1.9.3. Initial Values 
1.9.4. Computer Programs 

1.10. Statistical Inference in Non-Linear Regression 

1.10.1. Statistical Inference in Non-Linear La Regression 
1.10.2. Approximate Inference Validation 
1.10.3. Examples:

The most efficient pedagogical methodology, TECH Relearning, will allow you to acquire new knowledge in a precise and natural way, without spending too much time studying"