Quantum computing is a multidisciplinary field comprising aspects of computer science, physics, and mathematics that utilizes quantum mechanics to solve complex problems faster than on classical computers. The field of quantum computing includes hardware research and application development. Quantum computers can solve certain types of problems faster than classical computers by taking advantage of quantum mechanical effects, such as superposition and quantum interference. Some applications where quantum computers can provide such a speed boost include machine learning (ML), optimization, and simulation of physical systems.
Course Key learnings:
- Quantum Computing
- Quantum Programming
- Qiskit
- Python
- Quantum Computers
Module 1: Introduction to Quantum Computing
- What is Quantum Computing?
- Quantum Mechanics
- Qubits and Quantum Memory
- Elementary Gates
Module 2: Overview of Circuit Model and Deutsch-Jozsa
- Classical Circuits
- Quantum Circuits
- Universality of Various Sets of Elementary Gates
- Quantum Parallelism
- Early Algorithms
Module 3: Simon’s Algorithm and Fourier Transform
- Simon’s Algorithm
- Problem
- Quantum Algorithm
- Classical Algorithms for Simon’s Problem
Module 4: Fast Fourier Transform
- Classical Discrete Fourier Transform
- Fast Fourier Transform
- Application: Multiplying Two Polynomials
- Quantum Fourier Transform
Module 5: Shor’s Factoring Algorithm
- Factoring
- Shor’s Period-Finding Algorithm
- Continued Fractions
Module 6: Hidden Subgroup Problem
- Group Theory Reminder
- A General Algorithm for Abelian HSP
- Non-Abelian QFT on Coset States
Module 7: Grover’s Search and Quantum Walk Algorithm
- Grover’s Algorithm
- Amplitude Amplification
- Quantum Walk
- Applications
Module 8: Hamiltonian Simulation and HHL Algorithm
- Hamiltonians
- Methods of Hamiltonian Simulation
Module 9: Introduction to HHL Algorithm
- What is HHL Algorithm?
- Linear System Problem
- HHL Algorithm for Linear Systems
- Improving HHL Algorithm Complexity
Module 10: Quantum Query Lower Bounds
- Introduction
- Polynomial Method
- Quantum Adversary Method
Module 11: Quantum Complexity Theory
- Introduction to Quantum Complexity Theory
- Classical and Quantum Complexity Classes
- Classically Simulating Quantum Computers in Polynomial Space
Module 12: Quantum Encodings with a Non-Quantum Application
- Mixed States and General Measurements
- Quantum Encodings and Their Limits
- Lower Bounds on Locally Decodable Codes
Module 13: Quantum Communication Complexity
- Classical Communication Complexity
- Quantum Question
Module 14: Introduction to Quantum Cryptography
- Quantum Key Distribution
- Reduced Density Matrices and the Schmidt Decomposition
- Impossibility of Perfect Bit Commitment
Module 15: Error-Correction and Fault-Tolerance
- Introduction
- Classical Error-Correction
- Quantum Errors
- Quantum Error-Correcting Codes
- Fault-Tolerant Quantum Computation
- Concatenated Codes and the Threshold Theorem
Who’s this course for?
- Software Developers
- Data Scientists
- Mathematicians
- Computer Scientists
- Researchers
- Financial Analysts
- Telecommunications Experts
International Student Fees:600 US$
Stay connected even when you’re apart
👬🏻Join our WhatsApp Channel – Get discount offers
🧮 500+ Free Certification Exam Practice Question and Answers
🎥 Your FREE eLEARNING Courses (Click Here)
Internships, Freelance and Full-Time Work opportunities
👫🏻 Join Internships and Referral Program (click for details)
👫🏻 Work as Freelancer or Full-Time Employee (click for details)
Flexible Class Options
- Week End Classes For Professionals SAT | SUN
- Corporate Group Trainings Available
- Online Classes – Live Virtual Class (L.V.C), Online Training
Related Courses
Machine Learning with 9 Practical Applications
Specialist Diploma Big Data Analytics Course with Machine Learning
KEY FEATURES
Register Now
