You will master the principles of Deep Learning and generate the most accurate predictions with this 100% online postgraduate diploma"

Neural Networks are the fundamental basis of Deep Learning. Inspired by the functioning of the human brain and composed of neurons, these systems provide the computational foundation for machines to learn from data efficiently and automatically. In this way, they perform complex tasks with similar or even better performance than humans in multiple tasks such as machine translation or the analysis of large data sets. However, these tools still face several challenges that limit their effectiveness and applicability in certain areas. It is therefore the responsibility of experts to update their knowledge frequently in order to keep abreast of all developments in this field and to incorporate them into their practice in order to optimize their procedures. 

In this context, TECH creates a postgraduate diploma that will offer a solid understanding of how Deep Learning works, as well as the most advanced tools to build Neural Networks. The curriculum will range from key mathematical fundamentals (such as functions or derivatives) to the principles of Supervised Learning (including different models, evaluation metrics and hyperparameter selection). The syllabus will also focus on the numerous utilities of Deep Learning, so that graduates will be aware of the current situation of the labor market and multiply their chances of success in fields such as automotive, computer science, biology or finance. It should be noted that the university degree will include the analysis of real cases in simulated learning environments. Students will learn valuable lessons that they will incorporate into their procedures to ensure their viability.  

To consolidate all these contents, TECH uses the innovative methodology of Relearning. This is based on constant feedback and adaptation to the individual needs of the students based on targeted repetition. With any electronic device with Internet access, students will be able to access the Virtual Campus and get the most complete didactic contents in the educational market.  

Do you want to specialize in the use of Supervised Learning Machines? Get it through 450 hours of the best digital teaching"

This postgraduate diploma in Deep Learning 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 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 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

You will delve into the world of deep learning algorithms and acquire technical knowledge that will allow you to excel in the area of Social Sciences"

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 delve into the architecture of Neural Networks and their different types to solve everyday problems through Deep Learning"

A complete syllabus that incorporates all the knowledge you need to take a step towards the highest quality in Computer Vision"

The postgraduate diploma  will turn graduates into true references in Deep Learning. At the end of the academic pathway, they will have gained solid knowledge of the subject and acquired new skills that will significantly improve their chances of progression in the technology industry. In addition, they will be highly prepared to successfully tackle any obstacle that may arise in the course of their activities. Experts will even be able to develop projects linked to Artificial Intelligence to offer the most prestigious companies in their environment highly innovative and creative solutions.

Get the keys to optimize Backward Pass parameters thanks to this postgraduate diploma" 

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 program, 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. Mathematical Basis of Deep Learning

• Develop the chain rule for calculating derivatives of nested functions
• Analyze how to create new functions from existing functions and how to compute the derivatives of these functions
• Examine the concept of Backward Pass and how derivatives of vector functions are applied to automatic learning
• Learn how to use TensorFlow to build custom models
• Understand how to load and process data using TensorFlow tools
• Fundamentalize the key concepts of NLP natural language processing with RNN and attention mechanisms
• Explore the functionality of Hugging Face transformer libraries and other natural language processing tools for application to vision problems
• Learn how to build and train autoencoder models, GANs, and diffusion models
• Understand how autoencoders can be used to efficiently encode data

Module 2. Deep Learning Principles

• Analyze how linear regression works and how it can be applied to neural network models
• Understand the rationale for optimizing hyperparameters to improve the performance of neural network models
• Determine how the performance of neural network models can be evaluated using the training set and the test set

Module 3. Neural Networks, the Basis of Deep Learning

• Analyze the architecture of neural networks and their principles of operation
• Determine how neural networks can be applied to a variety of problems
• Establish how to optimize the performance of deep learning models by tuning hyperparameters

A contextual and realistic educational experience that will immerse you in the reality of a profession full of challenges”