Improve your skills on Metric Setting or Loss Function, thanks to the best online university in the world according to Forbes, thanks to TECH”

As Deep Learning becomes more popular and accessible, neural networks have become a powerful tool for solving complex machine learning problems. One of the many advantages of this system is its ability to learn and improve with data. 

TECH has designed a Postgraduate certificate in Neural Networks in Deep Learning with the aim of providing students with the necessary skills and competencies to be able to work as specialists with the highest possible efficiency and quality. In this program, aspects such as Optimizer Selection, Model Training,  Learning Rate  or Weight Adjustment will be addressed. 

All this, through a convenient 100% online modality that allows students to organize their schedules and studies, combining them with their other day-to-day work and interests. Moreover, this degree has the most complete theoretical and practical materials on the market, which facilitates the student's study process and allows them to achieve their objectives quickly and efficiently.

Become an expert in Deep Learning in only 6 weeks and with total freedom of organization”

This Postgraduate certificate in Neural Networks 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 neural network in deep learning 
• The graphic, schematic and practical contents of the program provide Rehabilitation 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 work
• Content that is accessible from any fixed or portable device with an Internet connection

Enhance your professional profile in one of the most promising areas of the IT sector thanks to TECH and the most innovative materials”

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.  

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

Access all the content on Deep Learning Types from your Tablet, mobile or computer”

Delve into the Layer Connection and Network Training from the comfort of your home at any time of the day”

The structure and all the didactic resources of this curriculum have been designed by the renowned professionals that make up TECH's team of experts in the area of Deep Learning. These specialists have used their extensive experience and state-of-the-art knowledge to create practical and completely up-to-date content. All this, based on the most efficient pedagogical methodology, TECH  Relearning.

The most comprehensive and up-to-date view of Network Training can be found in this syllabus”

Module 1. Neural networks, the basis of Deep Learning

1.1. Deep Learning 

1.1.1. Types of Learning Foundations 
1.1.2. Applications of Foundations Learning 
1.1.3. Advantages and Disadvantages of Foundations Learning 

1.2. Surgery 

1.2.1. Sum 
1.2.2. Product 
1.2.3. Transfer 

1.3. Layers 

1.3.1. Input layer 
1.3.2. Hidden layer 
1.3.3. Output layer 

1.4. Layer Bonding and Operations 

1.4.1. Architecture Design 
1.4.2. Connection between layers 
1.4.3. Forward propagation 

1.5. Construction of the first neural network 

1.5.1. Network Design 
1.5.2. Establish weights 
1.5.3. Training the Networks 

1.6. Trainer and Optimizer 

1.6.1. Optimizer Selection 
1.6.2. Establishment of a loss function 
1.6.3. Establishment of a metric 

1.7. Application of Neural Network Principles 

1.7.1. Activation Functions 
1.7.2. Backward propagation 
1.7.3. Parameter Estimation 

1.8. From biological to artificial neurons 

1.8.1. Functioning of a biological neuron 
1.8.2. Transfer of knowledge to artificial neurons 
1.8.3. Establish relationships between the two 

1.9. Implementation of MLP (Multilayer Perceptron) with Keras 

1.9.1. Definition of the Structure of Networks 
1.9.2. Model compilation 
1.9.3. Model Training 

1.10. Fine tuning  Hyperparameters of Neural Networks

1.10.1. Selection of the activation function 
1.10.2. Setting learning rate 
1.10.3. Weight adjustment 

150 hours separate you from becoming the expert in Neural Networks demanded by the schools of this sport”