Theory of Computation for Beginners

FA (DFA, NFA), PDA, LBA, Turing Machine

What you'll learn
Demonstrate knowledge of basic mathematical models of computation and their relationship with formal languages.
Identify different types of Finite Automata and their capabilities.
Analyze Regular Language and Context Free Grammar.
Create push down automata for a given language.
Discuss the abstract models of Turing machine and its types.
Create modern techniques to solve P, NP, NP hard and NP complete problems.
Recognize whether a problem is decidable or undecidable.
Requirements
No previous knowledge required. Everything will be taught from scratch.
Description
The course on the theory of automata typically covers the following key topics:
Introduction to Automata: The course begins with an introduction to the basic concepts and terminology of automata theory. It explores the fundamental questions of what constitutes a computation and what kinds of problems can be solved using computational models.
Finite Automata: Finite automata are the simplest form of automata, with a finite number of states and a fixed set of input symbols. The course covers deterministic and nondeterministic finite automata, their formal definition, properties, and their ability to recognize regular languages.
Regular Languages and Regular Expressions: Regular languages play a significant role in automata theory. The course delves into regular expressions, which are concise notations for describing regular languages. It covers the relationship between regular languages and finite automata and introduces regular operations such as union, concatenation, and Kleene star.
Context-Free Grammars and Pushdown Automata: Context-free grammars provide a more expressive way to describe languages. The course explores the relationship between context-free grammars and pushdown automata, which are more powerful machines capable of recognizing context-free languages.
Turing Machines and Computability: Turing machines are hypothetical computing devices that can simulate any computer algorithm. The course covers the formal definition of Turing machines, their computational capabilities, and the notion of computability. It also introduces the concepts of decidability and undecidability.
Undecidability and Complexity Theory: This part of the course delves into advanced topics such as the halting problem, the Church-Turing thesis, and the concept of undecidable problems. It introduces complexity theory and the classification of problems into different complexity classes, such as P, NP, and NP-complete.
Throughout the course, students typically engage in problem-solving exercises, proofs, and hands-on implementation of automata models using programming languages. The theoretical knowledge gained in the theory of automata course forms a foundation for further study in various areas of computer science, including formal language theory, compiler design, algorithm analysis, and artificial intelligence.
Who this course is for:
Beginners who want to learn about TOC and more.

More Info