Those who acquire knowledge now in quantum technologies will be the leaders in programming in the near-term future"

Quantum Computing has advanced rapidly in both theory and practice in recent years and with it the hope of potential impact on real applications. Quantum Computing are able to naturally solve certain problems with complex correlations between inputs that can be incredibly difficult for traditional computers. This postgraduate certificate Analyzes in which situations a quantum advantage could be achieved ”, in the context of advanced analytics and artificial intelligence in the industrial field."

Learning models developed on quantum computers are much more powerful for applications in the search for an optimal solution, both at the level of the best selection of hyperparameters in machine learning algorithms, as well as in cases of scenario optimization. This is because they allow much faster computation, better generalization with less data, or both. Those the computer scientists who acquire knowledge now in quantum technologies will be the leaders in programming in the near-term future."

Additionally, the student has the best study methodology 100% online, which eliminates the need to attend classes in person or have to comply with a predetermined schedule. To this end, in only 6 weeks will delve into the scope of application of Quantum Computing, understanding the competitive advantages they provide, so they will be positioned at the technological forefront and will be able to lead ambitious projects in the present and in the future.

A historic technological revolution associated with the development of new quantum platforms is underway"

This postgraduate certificate in Quantum Computing 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 Computing quantum
• 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 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 

Quantum sensors and actuators will enable computer scientists to navigate the nanoscale world with remarkable precision and sensitivity"

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.

Its multimedia content, developed with the latest educational technology, will allow professionals to learn in a contextual and situated learning environment, i.e., a simulated environment that will provide immersive education programmed to prepare in real situations.

The design of this program focuses on Problem-Based Learning, by means of which professionals must try to solve the different professional practice situations that arise during the academic course. For this purpose, the student will be assisted by an innovative interactive video system created by renowned and experienced experts.

The quantum revolution is already underway, and the possibilities ahead of you are limitless"

Determine the main quantum operators and develop operational circuits"

The goal of this postgraduate certificate is to show what benefits current and future quantum technologies can provide to machine learning, focusing on algorithms such as Kernel-based models, optimization and convolutional networks. The direct application of the knowledge acquired on Quantum Computing in real projects is an added professional value that very few computer scientists specialized in Information and Communication Technologies can offer.

Examines the applications of Quantum Computing, its pros and cons, to find out in which situations a quantum advantage could be achieved"

General Objectives

• Demonstrate the differences between quantum computing and classical computing.
• Analyze the mathematical foundations of quantum computing.
• Determine the main quantum operators and develop operational quantum circuits.
• Analyze the advantages of quantum computing in examples of quantum "type" problem solving.
• Develop and demonstrate the advantages of quantum computing in application solving examples (games, examples, programs)
• Demonstrate the different types of projects achievable with classical Machine Learning techniques and the state of the art in quantum computing.
• Develop the key concepts of quantum states as a generalization of classical probability distributions, and thus to be , able to describe quantum systems of many states
• Analyze how to encode classical information in quantum systems.
• Determine the concept of "Kernel Methods" used in classic Machine Learning algorithms.
• Develop and implement learning algorithms for classical ML models in quantum models, such as PCA, SVM, neural networks, etc.
• Implement DL model learning algorithms on quantum models, such as GANs

Specific Objectives

• Analyze the need for quantum computing and identify the different types of quantum computers currently available.
• Specify the fundamentals of quantum computing and its characteristics.
• Examine the applications of quantum computing, advantages and disadvantages.
• Determine the basic fundamentals of quantum algorithms and their internal mathematics.
• Examine Hilbert space of dimension 2n, n-Qubits, states, quantum gates and their reversibility.
• Demonstrating Quantum Teleportation
• Analyze Deutsch's Algorithm, Shor's Algorithm and Grover's Algorithm.
• Develop examples of applications with quantum algorithms.
• Analyze quantum computing paradigms relevant to machine learning.
• Examine the various ML algorithms available in quantum computing, both supervised and unsupervised
• Determine the different DL algorithms available in quantum computing.
• Understand the use of the quantum Fourier Transform in indicator integration for quantum ML models, as well as for feature selection.
• Develop pure quantum algorithms for solving optimization problems optimization problems
• Generate specialized knowledge on hybrid algorithms to solve learning problems.

Analyze the need for Quantum Computing and identify the different types of quantum computers in the market currently available”