This Postgraduate diploma will allow you to update your knowledge about Language Processors in a practical way, 100% online, without renouncing to the maximum academic rigor”

This program is aimed at those interested in achieving a higher level of knowledge in Language Processors. The main objective of this Postgraduate diploma is for students to specialize their knowledge in simulated work environments and conditions in a rigorous and realistic manner so that they can later apply it in the real world.

This Postgraduate diploma will prepare students for the professional practice of Computer Engineering, thanks to a transversal and versatile academic experience adapted to new technologies and innovations in this field. You will obtain extensive knowledge in Language Processors, from professionals in the sector.

The students will be able to take the opportunity and study this program in a 100% online format, without neglecting their obligations. Update your knowledge and obtain a Postgraduate diploma to continue growing both personally and professionally.

This program will allow you to enhance your skills and update your knowledge in Language Processors”

This Postgraduate diploma in Language Processors contains the most complete and up-to-date program on the market. The most important features include:

• Development of 100 simulated scenarios presented by experts in Language Processors
• The graphical, schematic and eminently practical content of the software provides scientific and practical information on the Language Processors
• News on the latest developments in Language Processors
• Practical exercises where self-assessment can be used to improve learning
• Interactive learning system based on the case method and its application to real practice
• All of this will be complemented by 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

Get qualified in Language Processors with this intensive program, from the comfort of your own home”

It includes in its teaching staff a team of professionals belonging to the field of Computer Engineering, who bring to this training the experience of their work, in addition to recognized specialists belonging to reference 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 an immersive program designed to train 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 throughout the program. For this purpose, the professionals will be assisted by an innovative interactive video system created by recognized experts in Information System with extensive teaching experience.

Take advantage of the latest educational technology to get up to date in Language Processors without leaving home"

Learn about the latest techniques in Language Processors from experts in the field"

The content structure has been designed by a team of Computer Engineering professionals, aware of the relevance of current training in order to deepen this area of knowledge, with the aim of humanistically enriching the student and raising the level of knowledge in Language Processors through the latest educational technologies available.

This Postgraduate diploma in Language Processors contains the most complete and up-to-date learning program on the market”

Module 1. Theoretical Computer Science

1.1. Mathematical Concepts Used

1.1.1. Introduction to Propositional Logic
1.1.2. Theory of Relations
1.1.3. Numerable and Non-Numerable Sets

1.2. Formal Languages and Grammars and Introduction to Turing Machines

1.2.1. Formal Languages and Grammars
1.2.2. Decision Problem
1.2.3. The Turing Machine

1.3. Extensions to Turing Machines, Constrained Turing Machines and Computers

1.3.1. Programming Techniques for Turing Machines
1.3.2. Extensions for Turing Machines
1.3.3. Restricted Turing Machines
1.3.4. Turing Machines and Computers

1.4. Indecibility

1.4.1. Non-Recursively Enumerable Language
1.4.2. A Recursively Enumerable Undecidable Problem

1.5. Other Undecidable Problems

1.5.1. Undecidable Problems for Turing Machines
1.5.2. Post Correspondence Problem (PCP)

1.6. Intractable Problems

1.6.1. The Classes P and NP
1.6.2. A NP-Complete Problem
1.6.3. Restricted Satisfiability Problem
1.6.4. Other NP-Complete Problems

1.7. Co-NP and PS Problems

1.7.1. Complementary to NP Languages
1.7.2. Problems Solvable in Polynomial Space
1.7.3. Complete PS Problems

1.8. Classes of Randomization-Based Languages

1.8.1. MT Model with Randomization
1.8.2. RP and ZPP Classes
1.8.3. Primality Test
1.8.4. Complexity of The Primality Test

1.9. Other Classes and Grammars

1.9.1. Probabilistic Finite Automata
1.9.2. Cellular Automata
1.9.3. McCulloch and Pitts Cells
1.9.4. Lindenmayer Grammars

1.10. Advanced Computing Systems

1.10.1. Membrane Computing: P-Systems
1.10.2. DNA Computing
1.10.3. Quantum Computing

Module 2. Automata Theory and Formal Languages

2.1. Introduction to Automata Theory

2.1.1. Why Study Automata Theory?
2.1.2. Introduction to Formal Demonstrations
2.1.3. Other Forms of Demonstration
2.1.4. Mathematical Induction
2.1.5. Alphabets, Strings and Languages

2.2. Deterministic Finite Automata

2.2.1. Introduction to Finite Automata
2.2.2. Deterministic Finite Automata
2.3. Non-Deterministic Finite Automata
2.3.1. Non-Deterministic Finite Automata
2.3.2. Equivalence Between AFD and AFN
2.3.3. Finite automata with transitions Є

2.4. Languages and Regular Expressions I

2.4.1. Languages and Regular Expressions
2.4.2. Finite Automata and Regular Expressions

2.5. Languages and Regular Expressions II

2.5.1. Conversion of Regular Expressions into Automata
2.5.2. Applications of Regular Expressions
2.5.3. Algebra of Regular Expressions

2.6. Pumping and Closure Lemma of Regular Languages

2.6.1. Pumping Lemma
2.6.2. Closure Properties of Regular Languages

2.7. Equivalence and Minimization of Automata

2.7.1. FA Equivalence
2.7.2. AF Minimization

2.8. Context-Independent Grammars (CIGs)

2.8.1. Context-Independent Grammars
2.8.2. Derivation Trees
2.8.3. GIC applications
2.8.4. Ambiguity in Grammars and Languages

2.9. Stack Automatons and GIC

2.9.1. Definition of Stack Automata
2.9.2. Languages Accepted by a Stack Automaton
2.9.3. Equivalence between Stack Automata and GICs
2.9.4. Deterministic Stack Automata

2.10. Normal Forms, Pumping Lemma of GICs and Properties of LICs

2.10.1. Normal Forms of GICs
2.10.2. Pumping Lemma
2.10.3. Closure Properties of Languages
2.10.4. Decision Properties of LICs

Module 3. Language Processors

3.1. Introduction to the Compilation Process

3.1.1. Compilation and Interpretation
3.1.2. Compiler Execution Environment
3.1.3. Analysis Process
3.1.4. Synthesis Process

3.2. Lexical Analyzer

3.2.1. What is a Lexical Analyzer?
3.2.2. Implementation of the Lexical Analyzer
3.2.3. Semantic Actions
3.2.4. Error Recovery
3.2.5. Implementation Issues

3.3. Parsing

3.3.1. What is a Parser?
3.3.2. Previous Concepts
3.3.3. Top-Down Analyzers
3.3.4. Bottom-Up Analyzers

3.4. Top-Down Parsing and Bottom-Up Parsing

3.4.1. LL Analyzer (1)
3.4.2. LR Analyzer (0)
3.4.3. Analyzer Example

3.5. Advanced Bottom-Up Parsing

3.5.1. SLR Parser
3.5.2. LR Parser (1)
3.5.3. LR Analyzer (k)
3.5.4. LALR Parser

3.6. Semantic Analysis I

3.6.1. Syntax-Driven Translation
3.6.2. Table of Symbols

3.7. Semantic Analysis II

3.7.1. Type Checking
3.7.2. The Type Subsystem
3.7.3. Type Equivalence and Conversions

3.8. Code Generation and Execution Environment

3.8.1. Design Aspects
3.8.2. Execution Environment
3.8.3. Memory Organization
3.8.4. Memory Allocation

3.9. Intermediate Code Generation

3.9.1. Synthesis-Driven Translation
3.9.2. Intermediate Representations
3.9.3. Examples of Translations

3:10. Code Optimization

3.10.1. Register Allocation
3.10.2. Elimination of Dead Assignments
3.10.3. Compile-Time Execution
3.10.4. Expression Reordering
3.10.5. Loop Optimization

A unique, key, and decisive educational experience to boost your professional development”