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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 finite 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.


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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Course Credit: MIT

Course Curriculum

Module 01
Introduction 00:10:00
Logic circuits and gates 00:12:00
Deterministic finite automata (DFAs) and nondeterministic finite 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
Module 02
Pseudorandom generators and one-way functions 01:30:00
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
Submit Your Assignment 00:00:00
Certification 00:00:00

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