A 100% online program that provides you with the most effective Deep Learning techniques to solve real problems and develop innovative solutions"

Deep Learning has a wide diversity of fields such as Robotics, Computer Vision and Natural Language Processing. Currently, the implementation of these advanced techniques is being increasingly demanded in different fields of work. Among them, the Marketing sector stands out, since Deep Learning tools provide these companies with multiple benefits. For example, they serve to analyze large sets of customer data to identify more precise audience segments. In this way, companies are able to personalize their strategies and messages in order to meet the specific needs of each audience. 

Given this reality, TECH creates a postgraduate diploma that will provide experts with a comprehensive knowledge on Deep Learning Applications. The curriculum is designed to equip students with the most cutting-edge and effective tools for training Neural Networks. To this end, the curriculum will delve into both neurons and recurrent layer architecture. The program will also delve intoTransformers models for natural language processing, enabling graduates to achieve superior performance in a variety of tasks such as fluent text generation. 

To achieve this update, TECH provides multiple pedagogical resources based on multimedia pills, case study simulations and specialized readings for students to enjoy dynamic learning. In addition, students will not have to invest many hours of study, since the Relearning method will help them to consolidate the most important concepts in a much simpler way. Therefore, professionals are faced with a quality academic option that is perfectly compatible with their daily responsibilities, as they can individually plan their schedules and evaluation chronograms. The only thing they will need to access the Virtual Campus is an electronic device with Internet access, and they can even use their cell phones.

You will master Hugging Face's Transformers tool for learning transfer. And in just 6 months with this postgraduate diploma!" 

This postgraduate diploma in Deep Learning Applications 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 Applications
• The graphical, schematic and practical contents with which it is conceived gather technological and practical information on those 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'll delve into sentiment analysis with Deep Learning algorithms to monitor social networks"  

The program’s teaching staff includes professionals from the sector who contribute their work experience to this 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 education programmed to learn 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 students will be assisted by an innovative interactive video system created by renowned and experienced experts.    

You will handle the construction of coding architectures and be able to automatically extract meaningful features from data"

TECH's revolutionary Relearning methodology will provide you with the flexibility to organize your study pace to suit your circumstances"

Upon completion of this university program, graduates will raise their professional horizons by becoming references in Deep Learning. By mastering the architecture of recurrent neurons and layers, students will apply these principles to Deep Learning algorithms to make machines learn automatically. In addition, they will be able to perform a practical application of natural language processing with Recurrent Neural Networks. In addition, they will implement advanced principal component analysis techniques to their projects through an incomplete linear automatic coder.  

You will acquire Deep Learning skills highly demanded to distinguish yourself in an increasingly global technology sector"

General Objectives

• Fundamentalize the key concepts of mathematical functions and their derivatives
• Apply these principles to deep learning algorithms to learn automatically
• Examine the key concepts of Supervised Learning and how they apply to neural network models
• Analyze the training, evaluation and analysis of neural network models
• Fundamentals of the key concepts and main applications of deep learning
• Implement and optimize neural networks with Keras
• Develop expertise in the training of deep neural networks
• Analyze the optimization and regularization mechanisms required for deep neural network training

Specific Objectives

Module 1. Processing sequences using RNN and CNN

• Analyze the architecture of recurrent neurons and layers
• Examine the various training algorithms for training RNN models

Module 2. NLP Natural Language Processing with RNN and Attention

• Train an encoder-decoder network to perform neural machine translation
• Develop a practical application of natural language processing with RNN and attention

Module 3. Autoencoders, GANs, and Diffusion Models

• Implementing PCA techniques with an incomplete linear autoencoder
• Use convolutional and variational autoencoders to improve the performance of autoencoders

With TECH you will be up to date with the latest technological advances and trends in the field of Neural Networks"