QC101 Quantum Computing & Intro to Quantum Machine Learning

BY
Udemy

Acquire the knowledge necessary to securely communicate using quantum cryptography.

Mode

Online

Fees

₹ 549 1299

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

Quantum computers use quantum mechanics. Quantum computing uses specialized hardware to exploit physical matter's particle-wave properties at small scales. A scalable quantum computer could perform some calculations exponentially faster than any "classical" computer. Classical physics cannot explain their operation. A large-scale quantum computer could break encryption schemes and help physicists simulate physical phenomena, but it is still experimental and impractical. Quantum computing uses qubits like digital electronics. Qubits can be in both of their "basis" states at once, unlike classical bits. Qubit measurements produce probabilistic classical bit outputs. QC101 Quantum Computing & Intro to Quantum Machine Learning certification is made available by Udemy to candidates who want to run quantum programs on a real quantum computer.

QC101 Quantum Computing & Intro to Quantum Machine Learning online training includes 12 hours of video, 10 articles, five downloadable resources, and a digital certificate upon course completion.

QC101 Quantum Computing & Intro to Quantum Machine Learning online classes consist of quantum physics, multiple input gates, introduction to statistics, computing eigenvalues, quantum cryptography, quantum physics, spin states, irreversible transformations, multi-qubit systems, and entanglement.

The highlights

  • Full Lifetime Access
  • 12 Hours of Video
  • Ten Articles
  • Five Downloadable Resources
  • Access on Mobile and TV
  • Certificate of Completion

Program offerings

  • Online course
  • Learning resources
  • 30-day money-back guarantee
  • Unlimited access

Course and certificate fees

Fees information
₹ 549  ₹1,299
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Measurement skills

QC101 Quantum Computing & Intro to Quantum Machine Learning certification course, the candidate will master utilizing quantum cryptography for secure communication; develop, simulate, and debug quantum programs using IBM Qiskit and Microsoft Q#; and execute quantum programs on a real quantum computer using IBM quantum experience. The candidate will learn how to analyze quantum circuits using Dirac's notation and quantum physics models, as well as how to train a quantum support vector machine on real-world data and use it to make predictions. The aspirant will learn data science, how quantum computing can aid artificial intelligence and machine learning, and why machine learning will be the killer app for quantum computing.

The syllabus

Introduction

  • Introduction
  • How is Quantum Computing Different?

Quantum Physics Through Photon Polarization

  • Introduction to Quantum Physics
  • Quantum Physics Through Photon Polarization 1
  • Quantum Physics Through Photon Polarization 2
  • Quantum Physics Through Photon Polarization 3
  • Quantum Physics Through Photon Polarization 4
  • Quantum Physics Through Photon Polarization 5
  • Quantum Physics Through Photon Polarization 6
  • Quantum Physics Through Photon Polarization 7
  • Quantum Physics Through Photon Polarization 8
  • Quantum Physics Through Photon Polarization 9
  • Quantum Physics Through Photon Polarization 10
  • Quantum Physics Through Photon Polarization 11
  • Quantum Physics Through Photon Polarization 12
  • Quantum Physics Through Photon Polarization 13
  • Quantum Physics Through Photon Polarization 14

Math Foundation: Complex Numbers, Probability, Linear Algebra & Logic

  • Quantum Computing Through Math
  • Boolean Algebra
  • Boolean Variables and Operators
  • Truth Tables
  • Logic Gates
  • Logic Circuits
  • AND Gate
  • OR Gate
  • NOT Gate
  • Multiple Input Gates
  • Equivalent Circuits 1
  • Equivalent Circuits 2
  • Universal Gate NAND
  • Exclusive OR
  • XOR for Assignment
  • XOR of Bit Sequences 1
  • XOR of Bit Sequences 2
  • Introduction to Cryptography
  • Cryptography with XOR
  • Shared Secret
  • Importance of Randomness
  • Breaking the Code
  • Introduction to Probability
  • Probability of a Boolean Expression
  • Mutually Exclusive Events
  • Independent Events
  • Manipulating Probabilities With Algebra
  • P (Mutually Exclusive Events)
  • P (Independent Events)
  • Complete Set of MutEx Events
  • P ( A OR B )
  • Examples
  • Examples
  • P ( Bit Values )
  • Analysis With Venn Diagrams
  • Venn Diagram : P (A AND B)
  • Venn Diagram : P (A OR B)
  • Venn Diagram : P ( NOT A )
  • Examples
  • Examples
  • Conditional Probability
  • Examples
  • Introduction to Statistics
  • Random Variables
  • Mapping Random Variables
  • Mean, Average, Expected Value, ...
  • Example
  • Example
  • Beyond Mean
  • Standard Deviation
  • Examples
  • Combinations of Random Variables
  • Correlation
  • Analysis of Correlation
  • Introduction to Complex Numbers
  • Imaginary i
  • Addition
  • Subtraction
  • Multiplication by a Real
  • Division by a Real
  • Complex Multiplication
  • Examples
  • Complex Conjugates
  • Squared Magnitude
  • Complex Division
  • Examples
  • Euler's Formula
  • Polar Form
  • Examples
  • Fractional Powers
  • Complex Cube Roots of 1
  • Square Root of i
  • 2D Coordinates
  • Matrices
  • Matrix Dimensions
  • Matrix Addition
  • Matrix Subtraction
  • Scalar Multiplication
  • Matrix Multiplication
  • Examples
  • Examples
  • 3x3 Example
  • Exercises
  • More Multiplications
  • When is Multiplication Possible?
  • Example
  • Not Commutative
  • Associative and Distributive
  • Dimension of Result
  • Odd Shaped Matrices
  • Examples
  • Outer Product
  • Exercise
  • Inner Product
  • Exercises
  • Identity Matrix
  • Matrix Inverse
  • Transpose
  • Transpose Examples
  • Transpose of Product
  • Complex Conjugate of Matrices
  • Adjoint
  • Unitary
  • Hermitian
  • Hermitian and Unitary
  • Why Hermitian or Unitary ?
  • Vectors and Transformations
  • Rotation in 2D
  • Special Directions
  • Eigen Vectors and Eigen Values
  • More Eigen Vectors
  • Computing Eigen Values

Quantum Cryptography

  • Photons
  • Photon Polarization
  • Experiments with Photon Polarization
  • No-Cloning Theorem
  • Encoding with XOR
  • Encryption with Single-Use Shared-Secrets
  • Encoding Data in Photon Polarization
  • Making the Protocol Secure
  • Exchanging Polarization Angles
  • Why is the BB84 protocol secure?
  • Analysis

Developing a Math Model for Quantum Physics

  • Modeling Physics with Math
  • Subtractive Probabilities Through Complex Numbers
  • Modeling Superposition Through Matrices
  • Overview of Math Model

Quantum Physics of Spin States

  • Introduction to Spin States
  • Basis
  • Column Matrix Representation of Quantum State
  • State Vector
  • Experiments with Spin 1
  • Experiments with Spin 2
  • Experiments with Spin 3

Modeling Quantum Spin States with Math

  • Analysis of Experiments 1
  • Analysis of Experiments 2
  • Analysis of Experiments 3
  • Dirac Bra-Ket Notation 1
  • Dirac Bra-Ket Notation 2
  • More Experiment Analysis 1
  • More Experiment Analysis 2
  • On Random Behavior

Reversible and Irreversible State Transformations

  • Irreversible Transformations: Measurement
  • Reversible State Transformations

Multi-Qubit Systems

  • Analyzing Multi-Qubit Systems

Entanglement

  • Entanglement

Understanding Superposition and Entanglement With Quantum Simulators

  • Download the Simulator Code
  • Installing Java and Running the Simulators
  • Launching the Superposition Simulator
  • Classical Photon
  • Quantum Photon
  • No Cloning
  • No Cloning
  • Measurement is Irreversible
  • Deterministic vs Probabilistic
  • Running the Simulator
  • Superposition 1
  • Superposition 2
  • Measurement and Superposition
  • Two-Photon Systems
  • Entanglement
  • Simulating Entanglement 1
  • Simulating Entanglement 2
  • Simulating Entanglement 3
  • Simulating Entanglement 4
  • Independent Photons
  • Effect of Measurement
  • Summary

Quantum Computing Model

  • Quantum Circuits
  • Fanout
  • Uncomputing
  • Reversible Gates
  • Quantum NOT
  • Other Single Qubit Gates
  • CNOT Gate
  • CCNOT: Toffoli Gate
  • Universal Gate
  • Fredkin Gate
  • Effects of Superposition and Entanglement on Quantum Gates

Quantum Programming with Microsoft Q#

  • Q#, Qiskit, or Cirq?
  • Installing Q#
  • Reminder
  • Q# Simulation Architecture
  • Q# Controller
  • Q# Execution Model
  • Measuring Superposition States
  • Overview of 4-Qubit Simulation Framework
  • Set Operation
  • Iterative Measurement
  • Verifying Output after Initialization - 1
  • Verifying Output after Initialization - 2
  • NOT Operation
  • Superposition
  • SWAP
  • CNOT
  • Significance of Superposition and Entanglement
  • Effect of Superposition on Quantum Gates
  • Toffoli Gate: General Configuration
  • Verifying Results
  • Toffoli Configured as NOT
  • Toffoli Configured as AND
  • Toffoli Configured as Fanout

IBM Quantum Experience

  • IBM Quantum - Note
  • IBM Quantum Experience

Quantum Programming and Algorithms With IBM Qiskit

  • Qiskit Code Resources
  • What is Qiskit ?
  • Installing Python and Qiskit
  • Interactive Python
  • Jupyter Notebooks
  • Spyder Python IDE
  • Variables and Assignment
  • Data Types
  • Operators
  • Type Conversion
  • Strings
  • Lists
  • Dictionaries
  • Loops
  • Decisions
  • Functions
  • Object Oriented Programming
  • Exceptions
  • Modules
  • Quantum Circuits 1
  • Quantum Circuits 2
  • Quantum Circuits 3
  • Quantum Circuits 4
  • Quantum Circuits 5
  • Running a Circuit
  • Circuit Matrix
  • Implementing BB84 Cryptography
  • Shor's Algorithm

Machine Learning Foundation

  • Introduction to Machine Learning
  • What is AI ?
  • Structure of ML Systems
  • Learning With Models
  • Speed Up Learning
  • Underfit & Overfit
  • Classification
  • Sigmoid Models
  • Regularization 1
  • Regularization 2
  • Machine Learning Libraries
  • Machine Learning Coding
  • Multi-Layer Network 1
  • Multi-Layer Network 2
  • Convolution 1
  • Convolution 2
  • Convolution 3
  • Recurrent

Quantum Machine Learning With Qiskit

  • Quantum Machine Learning with KNN
  • KNN Problem Description
  • Code for Classical KNN
  • Code for Quantum KNN
  • Math for Classical KNN
  • Math Prerequisites for Quantum KNN
  • Math for Quantum KNN
  • Connecting Math and Code for Classical KNN
  • Connecting Math and Code for Quantum KNN
  • Introduction to Classification
  • Support Vector Machines - Separation
  • Support Vector Machines - Overfitting
  • Support Vector Machines - Soft Margins
  • Support Vector Machines - Higher Dimensions and Kernels
  • Support Vector Machines - Multiple Classes
  • Quantum Support Vector Machines
  • Significance of Quantum Machine Learning

Instructors

Mr Kumaresan Ramanathan
Architect
Freelancer

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