Quantum Computing has arrived to revolutionize the communication sector. Specialize in this constantly evolving industry and achieve success"

Knowledge and specialization in Quantum Computing is a winning bet. It is today and will undoubtedly be even more so in the future. Quantum theory can be applied to various sciences and factors, such as Artificial Intelligence, cryptography, cybersecurity, machine learning, Blockchain, error correction, IoT, biotechnology, medicine, among other areas. 

A key area of interest and where Quantum Computing is proving to be most efficient is in the field of Machine Learning. This Postgraduate certificate shows its application in real proactive, predictive and prescriptive problems. Students who acquire knowledge now, in quantum technologies, will be the leaders in programming in the near-term future. 

In the course of 6 weeks, the graduates will deepen their understanding of the field of application of Quantum Computing, understanding the industrial benefits it brings, so they will be positioned at the technological forefront and will be able to lead ambitious projects in the present and in the future. In addition, they will have the best study methodology 100% online, which eliminates the need to attend classes in person or to have a predetermined schedule.

Completion of this Postgraduate certificate will place Engineering and Industry 4.0 professionals at the forefront of the latest developments in the sector"

This Postgraduate certificate in Quantum Computing contains the most complete and up-to-date program on the market. The most important features include:

• 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

You are facing an emerging market where, due to its complexity and immaturity, obtaining the right knowledge and advice will give you a competitive advantage in the labor market"

The program includes, in its teaching staff, professionals from the sector who bring to this program the experience of their work, in addition to recognized specialists from prestigious reference societies and 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 course. For this purpose, students will be assisted by an innovative interactive video system created by renowned and experienced experts.  

Knowledge and specialization in Quantum Computing at TECH is a winning bet"

You will observe the latest advances in Quantum Computing and you will be able to put them into practice"

The curriculum offered by this training covers a broad perspective on Quantum Computing, a technology that has advanced rapidly in both theory and practice in recent years and with it, the hope for potential impact on real-world applications. This Postgraduate certificate explores in depth, both at a theoretical and practical level, the conception, development and applications, focusing on quantum machine learning. 

This Postgraduate certificate will give you the necessary concepts and tools to get into this exciting technology"

Module 1. Quantum Computing. A New Model of Computing

1.1. Quantum Computing

1.1.1. Differences with Classical Computing
1.1.2. Need for Quantum Computing
1.1.3. Quantum Computers Available: Nature and Technology

1.2. Applications of Quantum Computing

1.2.1. Quantum Computing vs. Classical La Computing Applications
1.2.2. Contexts of Use
1.2.3. Application in Real Cases

1.3. Mathematical Foundations of Quantum Computing

1.3.1. Computational Complexity
1.3.2. Double Slit Experiment. Particles and Waves
1.3.3. Intertwining

1.4. Geometric Foundations of Quantum Computing

1.4.1. Qubit and Complex Two-Dimensional Hilbert Space
1.4.2. Dirac's General Formalism
1.4.3. N-Qubits States and Hilbert Space of Dimension 2n

1.5. Mathematical Fundamentals of Linear from Algebra

1.5.1. The Domestic Product
1.5.2. Hermitian Operators
1.5.3. Eigenvalues and Eigenvectors

1.6. Quantum Circuits

1.6.1. Bell States and Pauli Matrices
1.6.2. Quantum Logic Gates
1.6.3. Quantum Control Gates

1.7. Quantum Algorithms

1.7.1. Reversible Quantum Gates
1.7.2. Quantum Fourier Transform
1.7.3. Quantum Teleportation

1.8. Algorithms Demonstrating Quantum Supremacy

1.8.1. Deutsch´s Algorithm
1.8.2. Shor´s Algorithm
1.8.3. Grover´s Algorithm

1.9. Quantum Computer Programming

1.9.1. My First Program on Qiskit (IBM)
1.9.2. My First Program on Ocean (Dwave)
1.9.3. My First Program on Cirq (Google)

1.10. Application on Quantum Computers

1.10.1. Creation of Logical Gates

    1.10.1.1. Creation of a Quantum Digital “Adder”

1.10.2. Creation of Quantum Games
1.10.3. Secret Key Communication between Bob and Alice

Module 2. Quantum Machine Learning. Future Artificial Intelligence

2.1. Classical Machine Learning Algorithms

2.1.1. Descriptive, Predictive, Proactive and Prescriptive Models
2.1.2. Supervised and Unsupervised Models
2.1.3. Feature Reduction, PCA, Covariance Matrix, SVM, Neural Networks
2.1.4. ML Optimization: Gradient Descent

2.2. Classical Deep Learning Algorithms

2.2.1. Boltzmann Networks. The Machine Learning Revolution
2.2.2. Deep Learning Models. CNN, LSTM, GANs
2.2.3. Encoder-Decoder Models
2.2.4. Signal Analysis Models. Fourier Analysis

2.3. Quantum Classifiers

2.3.1. Quantum Classifier Generation
2.3.2. Amplitude Coding of Data in Quantum States
2.3.3. Encoding of Data in Quantum States by Phase/Angle
2.3.4. High-Level Coding

2.4. Optimization Algorithms

2.4.1. Quantum Approximate Optimization Algorithm (QAOA)
2.4.2. Variational Quantum Eigensolvers (VQE)
2.4.3. Quadratic Unconstrained Binary Optimization (QUBO)

2.5. Optimization Algorithms Examples:

2.5.1. PCA with Quantum Circuits
2.5.2. Optimization of Stock Packages
2.5.3. Optimization of logistics routes

2.6. Quantum Kernels Machine Learning

2.6.1. Variational Quantum Classifiers. QKA
2.6.2. Quantum Kernels Machine Learning
2.6.3. Classification Based on Quantum Kernel
2.6.4. Clustering Based on Quantum Kernel

2.7. Quantum Neural Networks

2.7.1. Classical Neural Networks and “Perceptron”
2.7.2. Quantum Neural Networks and “Perceptron”
2.7.3. Quantum Convolutional Neural Networks

2.8. Advanced Deep Learning (DL) Algorithms

2.8.1. Quantum Boltzmann Machines
2.8.2. General Adversarial Networks
2.8.3. Quantum Fourier Transformation, Quantum Phase Estimation and Quantum Matrix

2.9. Machine Learning Use Case

2.9.1. Experimentation with VQC (Variational Quantum Classifier)
2.9.2. Experimentation with Quantum Neural Networks
2.9.3. Experimentation with qGANS

2.10. Quantum Computing and Artificial Intelligence

2.10.1. Quantum Capacity in ML Models
2.10.2. Quantum Knowledge Graphs
2.10.3. The Future of Quantum Artificial Intelligence

Through the professional approach of this Postgraduate certificate, you will be able to put into practice the knowledge acquired in a company”