Get up-to-date on the use of an encoder-decoder network for machine translation and stand out as a high-level engineer” 

Natural Language Processing (NLP) has gained increasing importance in many fields thanks to its ability to improve efficiency and decision making through process automation. From sentiment analysis in social networks to automatic language translation, NLP has proven to be an indispensable tool today. 

Therefore, this unique program has been specifically designed to meet today's market needs, providing engineers with comprehensive instruction in natural language processing and the use of recurrent neural networks (RNN) as a tool for NLP modeling. 

In order to improve student learning, TECH has created a complete program based on its exclusive Relearning methodology, which consists of the progressive and natural repetition of the fundamental concepts so that the graduate integrates them effectively. In this way, the student will acquire the necessary skills while adjusting the pace of study to their daily life. 

In addition, the 100% online format of the program allows students to adapt their study pace to their needs and access the theoretical and practical contents from anywhere and at any time. With a practical approach and innovative methodology, this course offers students a unique opportunity to acquire skills that are highly valued in the market and contribute to the digital transformation of many companies around the world. 

Give your career a significant boost by including this Postgraduate certificate on your Resume”

This Postgraduate certificate in NLP Natural Language Processing with RNN 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 work
• Content that is accessible from any fixed or portable device with an Internet connection

Delve deeper into the Hugging Face Transformers library with this 150-hour Postgraduate certificate” 

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. This will be done with the help of an innovative system of interactive videos made by renowned experts. 

Access a content-rich syllabus, where you will find a multitude of real examples and practical analyses that contextualize the topics covered"

Get up to date on the advantages of attention mechanisms in neural networks with this complete TECH program"

This program has been designed by a team of experts in the field of Engineering, especially in Natural Language Processing with RNN. As a result, TECH has created a comprehensive and intensive syllabus that covers everything needed to master this discipline in a period of 6 weeks. In addition to the complete syllabus, hours of additional materials have been included so that the graduate can work in a personalized way and adapt to their needs and requirements. All this is presented in a convenient and flexible format, 100% online and compatible with any device that has an Internet connection. 

You will be able to download all the content directly to the electronic device of your choice, so you will be able to consult it even without an Internet connection, whenever and wherever it suits you best” 

Module 1. Natural Language Processing (NLP) with Recurrent Neural Networks (RNN) and Attention

1.1. Text Generation using RNN

1.1.1. Training an RNN for Text Generation
1.1.2. Natural Language Generation with RNN
1.1.3. Text Generation Applications with RNN

1.2. Creation of the Training Dataset

1.2.1. Preparation of the Data for RNN Training
1.2.2. Storage of the Training Dataset
1.2.3. Data Cleaning and Transformation

1.3. Sentiment Analysis

1.3.1. Classification of Opinions with RNN
1.3.2. Detection of Topics in Comments
1.3.3. Sentiment Analysis with Deep Learning Algorithms

1.4. Encoder-Decoder Network for Neural Machine Translation

1.4.1. Training a RNN for Machine Translation
1.4.2. Use of an Encoder-Decoder Network for Machine Translation
1.4.3. Improving the Accuracy of Machine Translation with a RNN

1.5. Attention Mechanisms

1.5.1. Application of Attention Mechanisms in RNN
1.5.2. Use of Attention Mechanisms to Improve the Accuracy of the Models
1.5.3. Advantages of Attention Mechanisms in Neural Networks

1.6. Transformer Models

1.6.1. Use of Transformers Models for Natural Language Processing
1.6.2. Application of Transformers Models for Vision
1.6.3. Advantages of Transformers Models

1.7. Transformers for Vision

1.7.1. Use of Transformers Models for Vision
1.7.2. Image Data Pre-Processing
1.7.3. Transformer Model Training for Vision

1.8. Hugging Face Transformer Library

1.8.1. Use of the Hugging Face Transformers Library
1.8.2. Application of the Hugging Face Transformers Library
1.8.3. Advantages of the Hugging Face Transformers Library

1.9. Other Transformers Libraries. Comparison

1.9.1. Comparison of the Different Transformers Libraries
1.9.2. Use of the Other Transformers Libraries
1.9.3. Advantages of Other Transformers Libraries

1.10. Development of an NLP Application with RNN and Attention. Practical Application

1.10.1. Development of a Natural Language Processing Application with RNN and Attention
1.10.2. Use of RNN, Attention Mechanisms and Transformers Models in the Application
1.10.3. Assessment of the Practical Application

A university qualification developed by renowned experts with the objective of acquiring advanced skills in Natural Language Processing NLP with RNN”