Learn, in depth, how convolutional neural networks work and apply them to computer vision, analyzing and classifying all types of images" 

The field of Computer Vision is growing, and new tools and knowledge are continually being incorporated to develop it. Therefore, convolutional neural networks are one of the most relevant advances in this field, since, following the operation of neural networks, they provide numerous solutions in this field, especially in image classification. 

This postgraduate certificate, therefore, offers the professional the most recent advances in this field, so that they can apply them to their work immediately. In this way, the program will delve into issues such as data analysis, metrics, types of CNN layers, the image classification process or model training, among many others. 

All this is done following an online teaching methodology that adapts to each student, since it allows them to choose the time and place to study. In addition, students will study under the guidance of a high-level teaching staff composed of working professionals who will teach them, using a range of multimedia resources, everything they need to develop computer vision projects using convolutional neural networks. 

Computer vision is the present and the future of artificial intelligence and this postgraduate certificate will help you to face all its current challenges"   

This postgraduate certificate in Convolutional Neural Networks and Image Classification in Computer Vision contains the most complete and up-to-date educational program on the market. The most important features include:  

• Case studies presented by experts in Deep Learning, computer science and computer vision
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the 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  

TECH Technological University's innovative teaching methodology includes numerous multimedia teaching resources to make the learning process quicker and more effective" 

The program’s teaching staff includes professionals from the 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. For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts. 

The use of convolutional neural networks is fundamental in the field of computer vision. Enroll now and specialize in this booming field"

Large technology companies are looking for professionals specialized in convolutional neural networks. Don't keep them waiting"  

The main objective of this postgraduate certificate in Convolutional Neural Networks and Image Classification in Computer Vision is to provide students with up-to-date knowledge so that they are familiar with the latest developments in this complex and exciting technological field. Therefore, at the end of the program, they will be in possession of new tools and knowledge in this field to exercise their professional work according to the mo st recent advances. 

Get up to date and integrate the latest advances in image classification using convolutional neural networks into your professional work"

General Objectives

• Cover convolutional neural networks
• Analyze existing metrics and tools 
• Examine the pipeline of an image classification network 
• Propose inference methods 

Specific Objectives 

• Generate specialized knowledge on convolutional neural networks 
• Establish evaluation metrics 
• Analyze the performance of CNNs for image classification 
• Assess Data Augmentation 
• Propose techniques to avoid Overfitting 
• Examine different architectures 
• Compile inference methods 

The career boost you are looking for is now within your reach. Don't let it go”