Introduction to the Program

Da un paso al frente con esta Postgraduate diploma en Distributed Computing y adéntrate en las técnicas más vanguardistas de la informática” 

Cuando se habla de la proliferación de los smartphones en la vida diaria o la llegada del 5G como el nuevo estándar de comunicación, se está abriendo un nuevo campo de posibilidades para todos los informáticos expertos en la Distributed Computing. Los grados de procesamiento y velocidad de procesado aumentarán conforme avance el tiempo, por lo que los profesionales de la informática debe estar preparado para poder programar a un nivel superior. 

Aquí entra en juego esesta Postgraduate diploma, que recopila precisamente los conocimientos más importantes y esenciales de la llamada Computación Distribuida. Gracias a un equipo docente que acumula una amplia experiencia en la gestión y dirección de proyectos informáticos de este tipo, los alumnos recibirán una enseñanza completa en todo lo que concierne a la Distributed Computing, adaptándola a las demandas del mercado actual. 

Además, la titulación se ofrece en un programa completamente online, lo que facilita su compaginación con otras actividades personales o profesionales. No existen ni clases presenciales ni horarios prefijados, sino que son los propios informáticos quienes tienen la libertad de descargarse todo el temario para distribuir las horas de estudio como mejor les convengan. 

Consigue un ascenso notorio en tu trayectoria profesional demostrando tus altas capacidades de programación y gestión distribuida en esta Postgraduate diploma”

Esta Postgraduate diploma en Distributed Computing contiene el programa educativo más completo y actualizado del mercado. Sus características más destacadas son: 

  • El desarrollo de casos prácticos presentados por expertos en Computación Paralela y Distribuida 
  • Los contenidos gráficos, esquemáticos y eminentemente prácticos con los que está concebido recogen una información práctica sobre aquellas disciplinas indispensables para el ejercicio profesional 
  • Los ejercicios prácticos donde realizar el proceso de autoevaluación para mejorar el aprendizaje 
  • Su especial hincapié en metodologías innovadoras 
  • Las lecciones teóricas, preguntas al experto y trabajos de reflexión individual 
  • La disponibilidad de acceso a los contenidos desde cualquier dispositivo fijo o portátil con conexión a internet 

Obtén los consejos y secretos de profesionales con un amplio éxito laboral, líderes de desarrollo en proyectos internacionales” 

El programa incluye, en su cuadro docente, a profesionales del sector que vierten en esta capacitación la experiencia de su trabajo, además de reconocidos especialistas de sociedades de referencia y universidades de prestigio.

Su contenido multimedia, elaborado con la última tecnología educativa, permitirá a los profesionales un aprendizaje situado y contextual, es decir, un entorno simulado que proporcionará una capacitación inmersiva programada para entrenarse ante situaciones reales.

El diseño de este programa se centra en el Aprendizaje Basado en Problemas, mediante el cual los profesionales deberán tratar de resolver las distintas situaciones de práctica profesional que se les planteen a lo largo del curso académico. Para ello, contarán con la ayuda de un novedoso sistema de vídeo interactivo realizado por reconocidos expertos. 

Podrás acceder al aula virtual las 24 horas del día y elegir donde, cuando y como estudiar todo el material didáctico"

TECH te dará el empujón que necesitas para alcanzar tus metas profesionales más ambiciosas"

Syllabus

The structure and content of this Postgraduate diploma have been meticulously designed to provide students with maximum comfort and efficiency. The program consists of three modules, each of which is further divided into 10 different topics. These topics cover a wide range of areas, including the characteristics and design of Distributed Systems, Distributed Computing oriented programming, and the applications of Distributed Computing in the current landscape. 

You will have access to a wide range of multimedia resources which include summary videos, detailed instructional videos, and motivational videos created by the teachers”

Module 1. Distributed Systems in Computing

1.1. Distributed Systems 

1.1.1. Distributed Systems (SD) 
1.1.2. Proof of the CAP Theorem (or Brewer's Conjecture) 
1.1.3. Fallacies of Distributed Systems Programming 
1.1.4. Ubiquitous Computing 

1.2. Distributed Systems Features 

1.2.1. Heterogeneity 
1.2.2. Extensibility 
1.2.3. Security/Safety 
1.2.4. Scales 
1.2.5. Fault Tolerance 
1.2.6. Concurrency 
1.2.7. Transparency 

1.3. Networks and Interconnection of Distributed Networks 

1.3.1. Networks and Distributed Systems.  
1.3.2. Networks Available to Create a Distributed System. Typology 
1.3.3. Network Protocols Distributed vs. Centralized 
1.3.4. Interconnection of Networks. Internet 

1.4. Communication Between Distributed Processes 

1.4.1. Communication between nodes of a D.S. Problems and failures 
1.4.2. Mechanisms to Implement Over RPC and RDMA to Avoid Failures 
1.4.3. Mechanisms to Implement in the Software to Avoid Failures. 

1.5. Distributed Systems Design 

1.5.1. Efficient Design of Distributed Systems (SD) 
1.5.2. Patterns for Distributed Systems (SD) Programming 
1.5.3. Service Oriented Architecture SOA
1.5.4. Service Orchestration and Microservices Data Management 

1.6. Distributed Systems Operation 

1.6.1. Systems Monitoring 
1.6.2. Implementing an Efficient Logging System in a DS
1.6.3. Monitoring in Distributed Networks 
1.6.4. Use of a Monitoring Tool for an SD Prometheus and Grafana Prometheus y Grafana 

1.7. System Replication 

1.7.1. System Replication Typology 
1.7.2. Immutable Architecture 
1.7.3. Container Systems and Virtualizing Systems as Distributed Systems
1.7.4. Blockchain Networks as Distributed Systems 

1.8. Distributed Multimedia Systems 

1.8.1. Distributed Exchange of Images and Videos. Problems 
1.8.2. Multimedia Object Servers 
1.8.3. Network Topology for a Multimedia System 
1.8.4. Analysis of Distributed Multimedia Systems: Netflix, Amazon, Spotify, etc. 
1.8.5. Distributed Multimedia Systems in Education 

1.9. Distributed File Systems 

1.9.1. Distributed File Sharing. Problems 
1.9.2. Applicability of the CAP Theory to Databases
1.9.3. Distributed Web File Systems: Akamai 
1.9.4. IPFS Distributed Document File Systems 
1.9.5. Distributed Database Systems 

1.10. Security Approaches in Distributed Systems 

1.10.1. Security in Distributed Systems 
1.10.2. Known Attacks on Distributed Systems 
1.10.3. Tools for Testing the Security of a DS 

Module 2. Models and Formal Semantics. Programming oriented to distributed computing 

2.1. Semantics Data Model 

2.1.1. Semantics Data Model 
2.1.2. Semantics Data Model. Purposes 
2.1.3. Semantics Data Model. Applications 

2.2. Semantic Model of Programming Languages 

2.2.1. Language Processing 
2.2.2. Translation and Interpretation 
2.2.3. Hybrid Languages 

2.3. Models of Computation 

2.3.1. Monolithic Computing 
2.3.2. Parallel Computing 
2.3.3. Distributed Computing 
2.3.4. Cooperative Computing (P2P) 

2.4. Parallel Computing 

2.4.1. Parallel Architecture 
2.4.2. Hardware 
2.4.3. Software 

2.5. Distribution Models Grid Computing 

2.5.1. Grid Computing Architecture 
2.5.2. Grid Computing Architecture. Analysis 
2.5.3. Grid Computing Architecture Applications 

2.6. Distribution Models Cluster Computing 

2.6.1. Cluster Computing Architecture 
2.6.2. Cluster Computing Architecture Analysis 
2.6.3. Cluster Computing Architecture Applications 

2.7. Cluster Computing Current Tools to Implement Cluster Computing. Hypervisors 

2.7.1. Market Competitors 
2.7.2. VMware Hypervisor 
2.7.3. Hyper-V 

2.8. Distribution Models Cloud Computing 

2.8.1. Architecture Cloud Computing 
2.8.2. Cloud Computing Architecture. Analysis 
2.8.3. Cloud Computing Architecture. Applications 

2.9. Distribution Models Amazon Cloud Computing 

2.9.1.  Amazon Cloud Computing Functional Criteria 
2.9.2. Amazon Cloud Computing Licensing 
2.9.3. Amazon Cloud Computing Reference Architectures 

2.10. Distribution Models Microsoft Cloud Computing 

2.10.1. Microsoft Cloud Computing Functional Criteria 
2.10.2. Microsoft Cloud Computing Licensing 
2.10.3. Microsoft Cloud Computing Reference Architectures 

Module 3. Parallel and Distributed Computing Applications 

3.1. Parallel and Distributed Computing in Today's Applications 

3.1.1. Hardware 
3.1.2. Software 
3.1.3. Importance of Timing 

3.2. Climate. Climate Change. 

3.2.1. Climate Applications. Data Sources 
3.2.2. Climate Applications. Data Volumes 
3.2.3. Climate Applications. Real Time 

3.3. GPU Parallel Computing 

3.3.1. GPU Parallel Computing 
3.3.2. AIH vs. CPU. GPU Usage 
3.3.3. GPU. Examples: 

3.4. Smart Grid. Computing in Power Grids 

3.4.1. Smart Grid 
3.4.2. Conceptual Models. Examples: 
3.4.3. Smart Grid. Example 

3.5. Distributed Engine. ElasticSearch 

3.5.1. Distributed Engine. ElasticSearch 
3.5.2. Architecture with ElasticSearch. Examples: 
3.5.3. Distributed Engine. Case Uses 

3.6. Big Data Framework 

3.6.1. Big Data Framework 
3.6.2. Architecture of Advanced Tools 
3.6.3. Big Data in Distributed Computing 

3.7. Memory Database 

3.7.1. Memory Database 
3.7.2. Redis Solution. Case Study 
3.7.3. Deployment of Solutions With In-Memory Database 

3.8. Blockchain. 

3.8.1. Blockchain Architecture. Components 
3.8.2. Collaboration Between Nodes and Consensus. 
3.8.3. Blockchain Solutions. Implementations 

3.9. Distributed Systems in Medicine 

3.9.1. Architecture Components 
3.9.2. Distributed Systems in Medicine. Operation 
3.9.3. Distributed Systems in Medicine. Applications 

3.10. Distributed Systems in the Aviation Sector 

3.10.1. Architecture Design 
3.10.2. Distributed Systems in the Aviation Sector. Component Functionalities 
3.10.3. Distributed Systems in the Aviation Sector. Applications 

You will be able to better contextualize the theory taught through the numerous exercises provided for each topic”

Postgraduate Diploma in Distributed Computing.

Distributed computing is a field of computer science that focuses on the use of multiple interconnected computing systems to work together as if they were a single entity. In distributed computing, the resources of interconnected computing systems, such as processing, storage, and memory, are used together to perform specific tasks.

The development of distributed computing involves the use of techniques to coordinate and manage the resources of interconnected systems. Distributed systems use communication protocols to coordinate data exchange, control access to resources, and manage load balancing between different systems.

Applications that use distributed computing.

Web search: search engines use distributed computing to index and search for information on the web.

Scientific research: scientists use distributed computing to handle large data sets and process complex simulations.

Social networking: social networking systems use distributed computing to support large numbers of users and handle large amounts of information.

To develop distributed computing applications, it is necessary to have a wide knowledge of the fundamental principles of distributed computing. This includes knowledge of communication protocols such as TCP and UDP, distributed system architectures, distributed storage systems such as Hadoop, and distributed database systems. Experience in programming languages such as Java, Python, C++ and Ruby, which are commonly used in distributed computing application development, as well as tools and technologies specific to different distributed systems, such as Apache Spark and Kafka for Apache Hadoop, is also required.

Distributed computing is a field of computer science that focuses on the use of multiple interconnected systems to work together as if they were a single entity. The development of distributed computing involves the use of techniques to coordinate and manage the resources of interconnected systems, and requires knowledge in communication protocols, distributed system architectures, programming languages and tools specific to different distributed systems.