Master, through this qualification, the interpretation of the time series analysis results allowing the optimization of component and relationship analysis”

Deep Learning Processing Sequences has acquired great importance in solving complex problems, especially in natural language processing and understanding patterns in temporal data. Therefore, the increasing importance of data sequence processing has led to a greater demand for highly qualified professionals in the area. 

For this reason, TECH's Postgraduate certificate in Deep Learning Processing Sequences provides the opportunity to acquire highly demanded skills and contribute to the solution of complex problems in a variety of fields. In this way, it has been designed to address current market needs and provide students with a multidisciplinary teaching in the processing of data streams through the use of Deep Learning techniques. Students will learn to implement advanced techniques, such as recurrent and convolutional neural networks, to address practical problems. 

TECH uses in all its academic programs the effective Relearning methodology, based on the progressive and natural repetition of the fundamental concepts so that the graduate integrates them in an effective way. In this way, students acquire the necessary skills by adjusting their pace of study to their personal life. In addition, the up-to-date and practical contents of the program, in combination with this methodology, guarantee a complete and rigorous didactic experience in the processing of data sequences. 

In addition, the program is available in a 100% online format, which allows students to adjust their study pace according to their needs and to access the theoretical and practical contents at any time and place. This way, they will be able to access the theoretical and practical resources from anywhere and at any time, all they need is a device with Internet connection. For all of the above reasons, it is a program that guarantees a flexible learning experience adapted to the individual needs of each student. 

This Postgraduate certificate will allow you to learn about statistical models for forecasting, as well as evaluation metrics” 

This Postgraduate certificate in Deep Learning Processing Sequences 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 Deep Learning 
• The graphic, schematic, and practical contents with which they are created, provide 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

You will learn through a 100% online methodology that will allow you to study without the need to make uncomfortable trips to an academic center” 

The program’s teaching staff includes professionals from 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. 

Combine this excellent learning with your professional and personal duties thanks to the teaching tools that TECH offers"

Throughout this academic program, you will delve into the management of long sequences and you will be able to perform cluster analysis"

A team of experts in Engineering, particularly in Deep Learning, has been in charge of designing the syllabus for this program. As a result, TECHhas created a rigorous and intensive program that covers all the information needed to master this discipline in just 6 weeks of specialization. In addition to the complete syllabus, hours of additional diverse materials have been included so that graduates can work in a personalized manner according to their needs and requirements. All this is presented in a 100% online, convenient and flexible format, compatible with any device with Internet connection.

Improve your Deep Learning skills through the most complete syllabus on the market and achieve the career boost you've been longing for”

Module 1. Processing Sequences using RNNs (Recurrent Neural Networks) and CNNs (Convolutional Neural Networks)

1.1. Recurrent Neurons and Layers

1.1.1. Types of Recurrent Neurons 
1.1.2. Architecture of a Recurrent Layer 
1.1.3. Applications of Recurrent Layers 

1.2. Recurrent Neural Network (RNN) Training 

1.2.1. Backpropagation Over Time (BPTT) 
1.2.2. Stochastic Downward Gradient 
1.2.3. Regularization in RNN Training 

1.3. Evaluation of RNN Models 

1.3.1. Evaluation Metrics 
1.3.2. Cross Validation 
1.3.3. Hyperparameters Adjustment 

1.4. Prerenal RNNs 

1.4.1. Prenetrated Networks 
1.4.2. Transfer of Learning 
1.4.3. Fine Tuning 

1.5. Time Series Forecasting 

1.5.1. Statistical Models for Forecasting 
1.5.2. Time Series Models 
1.5.3. Neural Network-Based Models 

1.6. Interpretation of the Time Series Analysis Results 

1.6.1. Main Component Analysis 
1.6.2. Cluster Analysis 
1.6.3. Correlation Analysis 

1.7. Management of Long Sequences 

1.7.1. Long Short-Term Memory (LSTM) 
1.7.2. Gated Recurrent Units (GRU) 
1.7.3. 1D Convolutional 

1.8. Partial Sequence Learning 

1.8.1. Deep Learning Methods 
1.8.2. Generative Models 
1.8.3. Reinforcement Learning 

1.9. Practical Application of RNN and CNN 

1.9.1. Natural Language Processing 
1.9.2. Pattern Recognition 
1.9.3. Computer Vision 

1.10. Differences in Classic Results 

1.10.1. Classic vs. RNN Methods 
1.10.2. Classic vs. CNN Methods 
1.10.3. Difference in Training Time 
1.10.3. AI Scenario: Chat Bot

A Postgraduate certificate designed by professionals for you to obtain a deep knowledge in Deep Learning Processing Sequences”