
Pre-requisites - https://www.udemy.com/course/quantum-computing-and-quantum-machine-learning-part-1/
Niche articles on Quantum Mechanics, Technology, Life and Spirituality with very simple language to understand
Explore how superposition combines states, illustrated by light polarization through parallel and perpendicular polarizers, where alignment controls light transmission and extinction.
Contrast a classical bit (0 or 1) with a qubit that exists everywhere until measured under the superposition principle. See how measurement collapses and disturbs the quantum state.
Apply the superposition principle to model an electron’s state as a weighted sum of basis states with complex amplitudes alpha_0, alpha_1, alpha_2, yielding probabilities |alpha_i|^2 that normalize to one.
Explore the geometrical interpretation of quantum states through the superposition principle, using complex probability amplitudes, normalization of state vectors, and column-vector representations for two- and three-level systems to compute probabilities.
Measure quantum states in arbitrary bases and derive probabilities from amplitudes. See how measurement collapses the state and how basis choice, including plus and minus bases, affects outcomes.
Explore how a two-qubit system forms a superposition of all four basis states, with amplitudes α00, α01, α10, α11, normalized to one. The lecture illustrates measurement collapsing states and probabilities.
Explore entanglement as a key quantum phenomenon, form composite two-qubit states, examine factorization versus entangled states, and study Bell states and measurement outcomes.
Investigate quantum gates and their unitary matrix representations. Examine the quantum not gate, which flips basis states and preserves state length, using the matrix [[0,1],[1,0]].
Explore the Pauli X gate, its unitary matrix [[0,1],[1,0]], and how it reverses basis states; compare with xor behavior on arbitrary quantum states.
Explain the Pauli z gate, a phase flip gate, represented by the diag(1,-1) matrix. Applying it to the state alpha zero plus beta one yields alpha zero minus beta one.
Discover how the Bloch sphere visualizes a qubit from the state alpha|0>+beta|1>, with complex alpha and beta, mapped to dimensions by latitude and longitude. Global phase does not affect observables.
Represent the qubit state on the Bloch sphere by expressing α and β in terms of θ and φ, ensuring |α|^2+|β|^2=1.
Learn how multi-particle systems arise from tensor products of single-particle Hilbert space bases to form a composite Hilbert space, and how to compute tensor products of states with coefficients.
Set up an IBM quantum experience account, verify via email, accept the end user agreement, then explore circuit composer and install the casket library to run Jupiter notebook.
Set up a Jupyter notebook with Qiskit and IBM Quantum Experience, verify installation, and configure your API token. Run a five-qubit qasm simulator to visualize measurement probabilities.
Open a Jupiter notebook to experiment with cubits, visualize states in plus minus and clockwise anticlockwise bases, and derive probabilities from probability amplitudes on the block sphere.
Conclude part two by revisiting superposition and entanglement, gates like Hadamard and Pauli X, Y and Z, eigenvalues and eigenvectors, Bloch sphere visualization, and programming with IBM Quantum Experience Lab.
Please ensure you have completed the Part 1 course which sets the foundational tone for this part 2 series
This course sets the correct foundation for learning Quantum Computing and Quantum Machine Learning. Machine Learning, Artificial Intelligence, Physicists, Researchers, Cloud Computing Professionals, Python Programmers, DevOps , Security and Data Science Professionals would cherish this course to join the new era of computing. In this course all the pre-requisites would be covered in depth, so that in the forth coming series of quantum computing and machine learning one can grasp the concepts pretty well
This Quantum Computing Series will have multiple parts and will be launched in segments. It will start from the very basics.
No pre-requisites as such is assumed for this course.
Part 1 will lay down the foundations to study quantum computation.
So part 1 will be mostly quantum mechanics and some mathematical foundations to study this course
From part 2 onward the programming will begin inside using Qiskit library of IBM and gradually more important concepts of quantum computing and quantum machine learning will be unearthed.
Multiple parts of quantum computing series will be launched step wise keeping concepts in certain sections and segregated it will be stepwise progression and gradually building the concepts around quantum computing and quantum machine learning.
This course would build solid foundation for Quantum Computing or anyone who would like to pursue further in this field. This course will introduce you to Quantum Computing/ Programming/ Physics/ Qiskit Framework and Quantum Gates
This course would build solid foundation for Quantum Computing or anyone who would like to pursue further in this field. This course will introduce you to Quantum Computing/ Programming/ Physics/ Qiskit Framework and Quantum Gates
Pre-requisites:
Python
10th Grade Mathematics/Physics
Please ensure you have completed the Part 1 course which sets the foundational tone for this part 2 series