Enroll and get a cutting-edge and effective teaching with TECH Relearning. Forget about memorization and get into efficient learning”

In a constantly evolving environment such as engineering, Deep Learning has become an essential tool for data processing and complex problem solving. Therefore, the Mathematical Basis of Deep Learning is used in fields as diverse as medicine, the automotive industry, fraud detection and financial analysis, among others. That is why the demand for highly qualified professionals in this area is only increasing.

In this context, this TECH program was created to respond to the needs of the market and provide students with a quality education in this discipline. This program has been specifically designed to provide students with a thorough understanding of the fundamental mathematics underlying Deep Learning, including calculus, probability theory and statistics. In addition, students will have the opportunity to acquire advanced skills in programming in Tensorflow and Deep Visual Computer, among other tools. All of this is presented in a 100% online format, which allows students to adapt their studies to their life style and access the theoretical and practical contents from anywhere and at any time.

In order to facilitate the student's learning, TECH has developed a complete program based on the Relearning methodology for the progressive and natural repetition of the fundamental concepts. In this way, the graduate will acquire the necessary competencies at their own pace and adjusted to their life style. In addition, the completely online format will allow the professional to access the theoretical and practical contents from anywhere and at any time through a device with Internet connection, focusing only on learning. In addition, they can access the theoretical and practical content from anywhere and at any time, all you need is a device with Internet connection.

With TECH you will be able to project your professional career without neglecting other areas of your life, that's why it offers you a flexible teaching adapted to your needs”

This postgraduate certificate in Mathematical Basis of 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 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 

Motivational videos, case studies, graphical and schematic content, discussion forums... Everything you need to give a boost to your professional career. Don't wait any longer"

The program's teaching staff includes professionals from the sector who bring to this training the experience of their work, as well as renowned specialists from reference 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. 

You will achieve your goals with the support of a teaching team specialized in neural network models and optimization"

A 100% online program with which you will obtain the most extensive and comprehensive knowledge about functions with multiple inputs and derivatives of functions with multiple inputs"

Through the syllabus, the graduate will develop a comprehensive knowledge of the key aspects of the Mathematical Basis of Deep Learning, which will allow them to obtain a global and up-to-date perspective and achieve the proposed objectives. As a result,  the student will acquire comprehensive skills in an essential, versatile and constantly growing field of engineering, which will lead them to achieve excellence in a booming sector. In order to ensure student satisfaction, TECH has established general and specific objectives that will guide the student towards success.

Improve your skills in the creation of new functions from existing functions with this postgraduate certificate in Mathematical Basis of Deep Learning”

General Objectives

• Lay the foundation for 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
• Lay the foundation for the key concepts and main applications of deep learning
• Implement and optimizes neural networks with Keras
• Develop expertise in the training of deep neural networks
• Analyze the optimization and regularization mechanisms necessary for deep network training

Specific Objectives

• Develop the chain rule for calculating derivatives of nested functions
• Analyze how new functions are created from existing functions and how the derivatives of these functions are computed
• Examine the concept of Backward Pass and how derivatives of vector functions are applied to learn automatically
• Learn how to use TensorFlow to build custom models
• Understand how to load and process data using TensorFlow tools
• Understand 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 to apply 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
• Analyze how linear regression works and how it can be applied to neural network models
• Lay the foundations 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

You will achieve your objectives thanks to the effective tools that TECH puts at your disposal in this complete postgraduate certificate”