Quantum Computing Training in Ameerpet Hyderabad

By Josh Innovations

Josh Innovations offers an industry-oriented Quantum Computing Training in Ameerpet Hyderabad, designed to take learners from classical computing foundations to advanced quantum algorithms, quantum machine learning, and real-world capstone projects. This program is ideal for students, researchers, software engineers, and professionals looking to build a future-ready career in quantum technologies.

Why Choose Quantum Computing Training at Josh Innovations?

• Structured beginner-to-advanced curriculum

• Strong focus on Qiskit & Python implementation

• Hands-on labs, simulations, and projects

• Career-oriented training aligned with global quantum standards

• Expert trainers with real-world quantum research exposure

Course Curriculum – Quantum Computing Training in Ameerpet Hyderabad

Chapter 1: Foundations of Classical Computing

• Classical vs Quantum computing overview

• Bits, bytes, and binary addition

• Boolean logic and truth tables

• Logic gates and circuit construction

• Python implementation of Boolean functions

Chapter 2: Mathematical Foundations – Linear Algebra

• Complex numbers refresher

• Scalars, vectors, and matrices

• Tensor products and Bra-Ket notation

• Qiskit setup and basic quantum circuits

Chapter 3: Quantum Mechanics Primer

• Wave-particle duality

• Qubits and quantum states (|0⟩, |1⟩, superposition)

• Probability amplitudes and quantum measurement

• Bloch sphere representation

• Multi-qubit systems and entanglement

Chapter 4: Single & Multi-Qubit Gates

• Pauli gates (X, Y, Z)

• Special gates (H, S, T, Rϕ)

• Controlled gates (CNOT, Toffoli)

• Bell states and entanglement generation

• Qiskit visualization and simulations

Chapter 5: Quantum Randomness & Probability

• Pseudorandom vs true random numbers

• Quantum coin flip experiment

• Quantum random number generator using Qiskit

Chapter 6: Quantum Algorithms I – Deutsch’s Algorithm

• Oracles and black-box functions

• Classical vs quantum query complexity

• Deutsch’s algorithm circuit design

• Qiskit implementation and execution

Chapter 7: Quantum Algorithms II – Grover’s Algorithm

• Big-O notation and search problems

• Oracle construction for Grover search

• Phase inversion and amplitude amplification

• Grover algorithm coding and testing in Qiskit

Chapter 8: Quantum Computing Landscape

• History of quantum mechanics

• Evolution of quantum computing

• Current platforms: IBM Q, Google Quantum AI, D-Wave

• Future research trends and career paths

Chapter 9: Final Beginner Projects

• Quantum coin flip with visualization

• 2-qubit entanglement generator

• Simple Grover search application

• Project presentation and peer review

Chapter 10: Advanced Quantum Algorithms

• Quantum Fourier Transform (QFT)

• Phase estimation and real-world applications

• Shor’s algorithm for integer factoring

• Variational algorithms (VQE, QAOA)

• Hands-on implementation using Qiskit

Chapter 11: Quantum Error Correction

• Quantum noise and decoherence

• Error models: bit-flip, phase-flip, depolarizing

• 3-qubit repetition code and Shor code

• Logical qubits and fault-tolerance thresholds

Chapter 12: Quantum Cryptography & Communication

• BB84 protocol and no-cloning theorem

• E91 entanglement-based QKD

• Quantum teleportation and superdense coding

• Qiskit implementation of BB84 and teleportation

Chapter 13: Quantum Machine Learning

• Introduction to Quantum Machine Learning (QML)

• Data encoding strategies

• Quantum feature maps and kernels

• Quantum classifiers (QSVM, VQC)

• Hands-on with Qiskit Machine Learning library

Chapter 14: Professional Capstone Project

• Quantum Machine Learning model implementation

• Quantum Error Correction code simulation

• Quantum chemistry simulation

• Quantum cryptography protocol implementation