5/15/2019
Automata, Computability, And Complexity Training - Edukite
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Automata, Computability, And Complexity Training ( 9 REVIEWS )
893 STUDENTS
This course provides a challenging introduction to the central ideas of theoretical computer science. Beginning in antiquity, it will progress …
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1 YEAR LEVEL 2 - CERTIFICATE COURSE BADGE COURSE CERTIFICATE
25
NUMBER OF UNITS
0
NUMBER OF QUIZZES
1 DAY, 5 HOURS
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This course provides a challenging introduction to the central ideas of theoretical computer science. Beginning in antiquity, it will progress through nite automata, circuits and decision trees, Turing machines and computability and the P versus NP problem. It examines the classes of problems that can and cannot be solved by machines. It tries to explain the key differences between computational models that affect their power.
Assessment This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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Automata, Computability, And Complexity Training - Edukite
Course Credit: MIT
COURSE CURRICULUM
Module 01
Introduction
00:10:00
Logic circuits and gates
00:12:00
Deterministic nite automata (DFAs) and nondeterministic nite automata (NFAs)
03:00:00
NFAs and regular expressions
00:10:00
Non-regular languages and the pumping lemma
02:00:00
Turing machines
03:00:00
Decidability
03:00:00
Undecidable problems and Post correspondence problem (PCP)
03:00:00
Mapping reducibility and Rice’s theorem
00:10:00
Self-reference and the recursion theorem
00:20:00
Introduction to cryptography
03:00:00
Complexity theory
00:10:00
01:30:00
Module 02
Pseudorandom generators and one-way functions
https://edukite.org/course/automata-computability-and-complexity-training/
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Automata, Computability, And Complexity Training - Edukite
Public-key cryptography
00:15:00
More complexity theory
00:20:00
More NP-completeness
02:00:00
Probabilistic Turing machines and complexity classes
01:30:00
Trapdoor one-way functions and zero-knowledge proofs
03:00:00
Probably approximately correct (PAC) learning
01:30:00
More PAC learning
00:20:00
Introduction to quantum
00:10:00
Quantum mechanics and BQP
00:15:00
Quantum algorithms
00:10:00
Assessment
Submit Your Assignment
00:00:00
Certi cation
00:00:00
COURSE REVIEWS
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