Quantum Computing and Quantum Machine Learning - Part 3

Name: Quantum Computing and Quantum Machine Learning - Part 3
Rating: 4.3 (219 reviews)

Learn great concepts like Quantum Teleportation, Super Dense Coding and IBM's qiskit toolkit

Created byRushabh Doshi

Last updated 3/2021

English

English [Auto],

What you'll learn

Quantum Physics
Quantum Computing
Quantum Machine Learning
Algebra
Calculus
Programming
Python
Quantum Gates
Electronics
Machine Learning
Data Science
Artificial Intelligence
Physics
Mathematics

Course content

9 sections • 24 lectures • 1h 52m total length

Introduction1:07
Pre-requisites:

https://www.udemy.com/course/quantum-computing-and-quantum-machine-learning-part-1/

https://www.udemy.com/course/quantum-computing-and-quantum-machine-learning-part-2/

Quantum Gates3:21
Explore quantum gates as unitary operators, including the identity matrix and adjoint concepts, and examine reversibility, noting quantum gates are reversible while classical computing is not, except the not gate.
Unitary Characteristics2:07
T-Gate3:01
Show how any matrix is a linear combination of the identity and Pauli X, Y, Z, and explain the phase flip and selective phase gates alongside the T-gate.
Unitary Operation3:50
Apply a two-by-two unitary matrix to a two-by-one Cubitt state to produce a two-by-one output, preserving the original dimension.
CCNOT, SWAP, CSWAP GATES3:58
Explore CCNOT, swap, and CSWAP gates in quantum computing and quantum machine learning, showing how control qubits enable conditional flips and state swaps.

Introduction to Quantum Circuits2:00
Compare quantum circuits with classical circuits, where qubits serve as inputs and outputs and time flows forward. Prevent fan-out; copying is forbidden by the no cloning theorem.
Half Adder Circuit2:43
Oracle2:11
Explore a quantum oracle as a black box that applies a circuit to x, flipping x when y is one and leaving it unchanged when y is zero.
Uniform Superposition of n qubit basis2:12

No Cloning Theorem5:55
Explore the no cloning theorem in quantum computing and quantum machine learning—part 3, showing no unitary transformation can copy an arbitrary state onto a blank state, with a Xerox analogy.
Quantum Teleportation - 12:10
Quantum Teleportation - 24:36
Explore quantum teleportation where Alice and Bob use unitary operations, CNOT, and Hadamard measurements to transfer a qubit and recover the original state with conditional gates.
Quantum Teleportation - 35:35
Explain the complete quantum teleportation protocol: share a Bell state, apply Hadamard and CNOT, perform Alice's measurement, and Bob applies X or Z to recover alpha|0>+beta|1>.
Reversible Computation - 16:57
Reversible Computation - 22:02
Explore reversible computation by translating classical circuits to quantum equivalents, examining how unitary quantum circuits output C(X) with junk bits and zero bits, and why removing junk matters.
Reversible Computation - 33:09
Discover why removing junk bits prevents quantum interference from corrupting outcomes, and see a reversible quantum circuit using unitary transformations to preserve qubits and information.

Practical - 18:21
Practical - 211:50
Explore representing quantum gates and states in a notebook, measure in the 01 basis, visualize Bloch sphere behavior, and study Pauli, Hadamard, and CNOT gates, decoherence, and dagger notation.
Practical - 34:18
Represent and visualize quantum circuits using quantum gate theory, applying gates and measurements in a Kaskade-based Biton workflow to illustrate reversible, unitary circuitry.

Requirements

Basic Python
Quantum Computing and Quantum Machine Learning - Part 1
Quantum Computing and Quantum Machine Learning - Part 2

Description

Quantum Computing and Quantum Machine Learning - Part 3 , is the continuation from what was taught in Part 1 and Part 2. This is going to be the new era of computation/ physics. Enroll for an enriching career in Quantum Research and learn Pythonic Libraries like Qiskit to operate with Quantum Gates and Quantum Circuits in depth. A fantastic computing era to join. In this course will see how to generate quantum circuits using quantum gates like CNOT, Hadamard, SWAP etc. This course sets the correct path in order to study Quantum Cryptography in depth and in the later series will move towards Quantum Machine Learning and libraries of Google like CIRQ.

Will see how to handle quantum circuits using quantum as well as classical channel. Applications of Quantum Teleportation and Super Dense Coding and a very important theorem called as No Cloning Theorem. Quantum computing is the use of quantum phenomena such as superposition and entanglement to perform computation. Computers that perform quantum computations are known as quantum computers.

In the classical view, one entry would have a value of 1 (i.e. a 100% probability of being in this state) and all other entries would be zero. In quantum mechanics, probability vectors are generalized to density operators. This is the technically rigorous mathematical foundation for quantum logic gates, but the intermediate quantum state vector formalism is usually introduced first because it is conceptually simpler.

Who this course is for:

Developers
Data Scientists
Machine Learning Engineer
Artificial Intelligence Researchers
Data Engineer
Researchers
Scientists
Physicists
Mathematicians
Deep Learning
Deep Learning Engineers
Reinforcement Learning
Programmers
Python Developers

Quantum Computing and Quantum Machine Learning - Part 3

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 1min

Quantum Gates Continued...5 lectures • 16min

Quantumener Blog1 lecture • 1min

Quantum Circuits4 lectures • 9min

No Cloning Theorem and Quantum Teleportation7 lectures • 30min

Super Dense Coding1 lecture • 16min

Density Matrix and Liouviele Equation1 lecture • 12min

Qiskit Practicals Continued..3 lectures • 24min

Conclusion1 lecture • 3min

Requirements

Description

Who this course is for: