What is Quantum Computing?

Quantum Computing is the intersection of computer science, mathematics and quantum physics which utilizes the phenomena of quantum mechanics to perform computations which classical computers cannot perform. Quantum computers provides significant speedup in different kinds of algorithms such as searching data elements or breaking RSA encryption systems!

What you will achieve from this course :-

  • Qualify IBM Qiskit Certification exam successfully in your first attempt

  • Secure a job in the Quantum Computing field

  • Implement your knowledge of Quantum Computing to your job and workspace

  • Conduct successful research and publish your results in the field of Quantum Computing

  • Complete all your Quantum Computing projects & assignments in your undergraduate degree or master's successfully

  • Wrap up your Undergraduate or Master's thesis in Quantum Computing Field

  • Teach Quantum Computing to University or College or School students

Course Prerequisites

  • Strongly Recommended - Quantum Computing Prerequisite Masterclass Course

  • Have coding experience with Python Programming language and basic knowledge of computer science

  • Have basic knowledge of Trigonometry, Complex Numbers, Linear Algebra and Probability

What will you learn in this course

  • Explore core concepts of Quantum Computing - Superposition, Interference and Entanglement

  • Learn about Quantum Gates and construct Quantum Circuits with IBM Qiskit

  • Learn Quantum Teleportation and Superdense Coding with their implementation using IBM Qiskit

  • Run your Quantum Programs on a real IBM Quantum Computer

  • Gain Confidence to tackle Quantum Programming challenges organized by various Quantum Computing Industries

  • Learn and gain background to think and analyze about Quantum Algorithms

Course Features - Top Quality

  • IBM Quantum Educator Recognized

    The training curriculum has been recognized by IBM for High Quality Comprehensive Quantum Education

  • 100% Online with Detailed Codes

    A self paced course with comprehensive video lectures and well commented Python codes

  • Industry Leading Mentorship

    Receive guidance from an IBM Qiskit Advocate on Quantum Technologies

  • Certification

    Complete the course to receive certification

  • Lifetime Access

    Receive lifetime access to the course. Only one time investment

  • Continuous Upgrades Free of Charge

    Receive continuous upgrades to the course materials as the technology progresses

Who is this course for?

This course is primarily for

  • Beginners who are curious to know about Quantum Computing

  • High School students with basic background on mathematics and Python programming

  • University students who want to learn and apply Quantum Computing

  • Industry professionals who want to up-skill themselves with Quantum Computing

  • Technology enthusiasts who want to explore the world of Quantum Computing

  • Business professionals who want to leverage the power of quantum computing in their decision making process

  • Solopreneurs and Entrepreneurs who want to enter into this cutting-edge field and provide services to others

  • Anyone who want to start their career in Quantum Computing

  • Machine Learning, Deep Learning or AI professionals who want to up-skill themselves with Quantum Computing

Course curriculum

Comprehensive Quantum Computing Training

  • 1

    Course Overview

  • 2

    IBM Qiskit Installation

    • Installing Anaconda IDE

    • Creating an Environment with Anaconda IDE

    • Installing IBM Qiskit and its Applications in Anaconda Environment

  • 3

    ---Part 1 Introduction to Classical Computing---

    • Classical Computing Introduction

  • 4

    Introduction to Classical Computing

    • Introducing Classical Computing Hardware

    • Digital Logic and Operations

    • Introducing Classical Logic Gates

    • Constructing Classical Circuits

    • Complexity of Algorithms

    • Introduction to Classical Computing Quiz

  • 5

    ---Part 2 Mathematics for Quantum Computing---

    • Mathematics for Quantum Computing

  • 6

    Linear Algebra

    • Introducing Vectors and Vector Spaces

    • Dot Products and Inner Products

    • Euclidean Norm

    • Properties of Hilbert Spaces

    • Matrices and Transformations

    • Arithmetic of Matrices

    • Outer Products

    • Eigenvalues and Eigenvectors of an Operator

    • Inverse of Matrix & Unitary Transformations

    • Determinant, Trace & Expectation Value of an Operator

    • Tensor Products

    • Linear Algebra LaTeX Notes

    • Linear Algebra Quiz

  • 7

    Trigonometry & Complex Numbers

    • 2D & 3D Cartesian Coordinate System

    • Polar Coordinate System

    • Complex Numbers & Complex Plane

    • Complex Numbers Quiz

  • 8

    Probability

    • Introduction to Probability & its Axioms

    • Random Variables, Expectations & Variances

    • Law of Large Numbers

  • 9

    ---Part 3 Quantum Mechanics---

    • Overview of Quantum Mechanics

  • 10

    Overview of Quantum Mechanics

    • Primary Concepts of Quantum Mechanics

    • Interference, Young's Double Slit Experiment & Wave-Particle Duality

    • Wavefunctions and Hamiltonians

    • The Schrodinger Equation

    • Postulates of Quantum Mechanics

    • Quantum Mechanics Quiz

  • 11

    ---Part 4 Introduction to Quantum Computing---

    • Introduction to Quantum Computing

  • 12

    Introduction to Quantum Computing

    • Introducing Quantum Bits (Qubits) - Single Qubits, Bra-Ket Notation and Superposition

    • Visualizing Single Qubits - The Bloch Sphere and Basis States

    • Mathematics behind Bloch Sphere

    • Quantum Measurements

  • 13

    ---Part 5 Single Qubit Quantum Gates---

    • Single Qubit Quantum Gates

  • 14

    Single Qubit Quantum Logic Gates

    • Pauli I Gate - Quantum Identity Gate

    • Pauli X Gate - Quantum X Gate

    • Pauli X Gate Eigenvalues and Eigenvectors

    • Pauli Y Gate - Quantum Y Gate

    • Pauli Y Gate Eigenvalues and Eigenvectors

    • Pauli Z Gate - Quantum Z Gate

    • Pauli Z Gate Eigenvalues and Eigenvectors

    • Hadamard Gate - Quantum H Gate

    • Quantum S and S-Dagger Gate

    • Quantum T and T-Dagger Gate

    • Quantum Rotation Gates - Rx, Ry and Rz Gates

    • Universal Quantum Gates

    • Single Qubit Quantum Gates Quiz

  • 15

    Qiskit Basics & Single Qubit Quantum Gates in Qiskit

    • Qiskit Basics - Importing Libraries, Checking Versions and Backends

    • Pauli X Gate in Qiskit with Bloch Sphere, Unitary & QASM Simulator

    • Pauli Y & Pauli Z Gates in Qiskit

    • S, S Dagger, T & T Dagger Gates in Qiskit

    • Rx, Ry & Rz Rotation Gates in Qiskit

    • Qiskit Basics & Single Qubit Quantum Logic Gates Jupyter Notebook

    • Practice Exam 1 : Qiskit Basics & Single Qubit Quantum Gates

  • 16

    ---Part 6 Multi Qubit Quantum Gates---

    • Multi Qubit Quantum Gates

  • 17

    Multiple Qubit Quantum Logic Gates

    • Quantum Entanglement

    • Quantum CX/CNOT Gate

    • Quantum CZ or CPHASE Gate

    • The Bell States or EPR Pairs

    • Quantum SWAP Gate

    • Quantum Toffoli/CCNOT Gate

    • Quantum Fredkin/CSWAP Gate

    • Hadamard Gate Applied to n Qubits

    • Multi Qubit Quantum Gates Quiz

  • 18

    Qiskit Multi Qubit Quantum Gates

    • CNOT, CZ & CH Quantum Gates in Qiskit

    • Quantum SWAP Gate in Qiskit

    • The Bell State in Qiskit

    • CCNOT or Toffoli Gate in Qiskit

    • CSWAP or Fredking Gate in Qiskit

    • Qiskit Multi Qubit Quantum Gates Jupyter Notebook

    • Practice Exam 2: Qiskit Multi Qubit Quantum Gates

  • 19

    ---Part 7 Constructing Quantum Circuit using Quantum Gates---

    • Constructing Quantum Circuit using Quantum Gates

  • 20

    Constructing Quantum Circuits with Quantum Gates

    • NOT, AND and OR Gates using Quantum Gates

    • NOT, AND and OR Gates using Qiskit

    • XOR & NAND Gates using Quantum Gates

    • XOR & NAND Gates using Qiskit

    • Half Adder using Quantum Gates

    • Half Adder using Qiskit

    • Constructing Classical Gates using Quantum Gates Notes

    • Constructing Classical Gates using Quantum Gates Jupyter Notebook

    • Constructing Classical Gates using Quantum Gates Quiz

  • 21

    ---Part 8 Quantum Teleportation---

    • Quantum Teleportation

  • 22

    Quantum Teleportation (Theory)

    • Quantum Teleportation Part I

    • Quantum Teleportation Part II

    • Quantum Teleportation Part III

    • Quantum Teleportation Part IV

    • Quantum Teleportation Notes

  • 23

    Quantum Teleportation with Qiskit

    • Quantum Teleportation with Qiskit I

    • Quantum Teleportation with Qiskit II

    • Quantum Teleportation with Qiskit III

    • Quantum Teleportation with Qiskit IV

    • Quantum Teleportation with Qiskit V

    • Quantum Teleportation with Qiskit VI

    • Quantum Teleportation with Qiskit VII

    • Quantum Teleportation with Qiskit VIII

    • Quantum Teleportation with Qiskit Jupyter Notebook

  • 24

    ---Part 9 Quantum Superdense Coding---

    • Quantum Superdense Coding

  • 25

    Superdense Coding (Theory)

    • Superdense Coding Part I

    • Superdense Coding Part II

    • Superdense Coding Part III

    • Superdense Coding Notes

  • 26

    Superdense Coding with Qiskit

    • Superdense Coding with Qiskit I

    • Superdense Coding with Qiskit II

    • Superdense Coding with Qiskit III

    • Superdense Coding with Qiskit IV

    • Superdense Coding with Qiskit V

    • Superdense Coding with Qiskit VI

    • Superdense Coding with Qiskit Jupyter Notebook

  • 27

    ---Part 10 Deutsch's Algorithm---

    • Deutsch's Algorithm

  • 28

    Deutsch's Algorithm (Theory)

    • Deutsch Algorithm I - Intro

    • Deutsch Algorithm II - Problem

    • Deutsch Algorithm III - Quantum vs Classical

    • Deutsch Algorithm IV - Oracles

    • Deutsch Algorithm V - Algo Steps

    • Deutsch Algorithm VI - Circuit Analysis Step 0

    • Deutsch Algorithm VII - Circuit Analysis Step 1

    • Deutsch Algorithm VIII - Circuit Analysis Step 2

    • Deutsch Algorithm IX - Circuit Analysis Step 3

    • Deutsch Algorithm X - Circuit Analysis Step 4

    • Deutsch Algorithm Notes

  • 29

    Deutsch Algorithm with Qiskit

    • Deutsch Algorithm with Qiskit I

    • Deutsch Algorithm with Qiskit II

    • Deutsch Algorithm with Qiskit III

    • Deutsch Algorithm with Qiskit IV

    • Deutsch Algorithm with Qiskit V

    • Deutsch Algorithm with Qiskit VI

    • Deutsch Algorithm with Qiskit VII

    • Deutsch Algorithm with Qiskit VIII

    • Deutsch Algorithm with Qiskit IX

    • Deutsch Algorithm with Qiskit Jupyter Notebook

  • 30

    ---Part 11 Deutsch-Jozsa Algorithm---

    • Deutsch-Jozsa Algorithm

  • 31

    Deutsch-Jozsa Algorithm (Theory)

    • Deutsch-Jozsa Algorithm I - Intro

    • Deutsch-Jozsa Algorithm II - Problem & Classical Case

    • Deutsch Jozsa Algorithm III - Features of DJ Algorithm

    • Deutsch Jozsa Algorithm IV - Constant vs Balanced Oracles

    • Deutsch Jozsa Algorithm V - Circuit Analysis Step 0

    • Deutsch Jozsa Algorithm VI - Circuit Analysis Step 1

    • Deutsch Jozsa Algorithm VII - Circuit Analysis Step 2

    • Deutsch Jozsa Algorithm VIII - Circuit Analysis Step 3

    • Deutsch Jozsa Algorithm IX - Circuit Analysis Step 4

    • Deutsch Jozsa Algorithm Handwritten Notes

  • 32

    Deutsch Jozsa Algorithm with Qiskit

    • Deutsch Jozsa Algorithm with Qiskit I

    • Deutsch Jozsa Algorithm with Qiskit II

    • Deutsch Jozsa Algorithm with Qiskit III

    • Deutsch Jozsa Algorithm with Qiskit IV

    • Deutsch Jozsa Algorithm with Qiskit V

    • Deutsch Jozsa Algorithm with Qiskit VI

    • Deutsch Jozsa Algorithm with Qiskit VII

    • Deutsch Jozsa Algorithm with Qiskit VIII

    • Deutsch Jozsa Algorithm with Qiskit IX

    • Deutsch Jozsa Algorithm with Qiskit X

    • Deutsch Jozsa Algorithm with Qiskit XI

    • Deutsch Jozsa Algorithm with Qiskit XII

    • Deutsch Jozsa Algorithm with Qiskit XIII

    • Deutsch Jozsa Algorithm with Qiskit XIV

    • Deutsch Jozsa Algorithm with Qiskit XV

    • Deutsch Jozsa Algorithm with Qiskit Jupyter Notebook

  • 33

    ---Part 12 Bernstein-Vazirani Algorithm---

    • Bernstein-Vazirani Algorithm

  • 34

    Bernstein-Vazirani Algorithm (Theory)

    • Bernstein-Vazirani Algorithm I - The Problem

    • Bernstein Vazirani Algorithm II - Circuit Analysis Step 0

    • Bernstein Vazirani Algorithm III - Circuit Analysis Step 1

    • Bernstein Vazirani Algorithm IV - Circuit Analysis Step 2

    • Bernstein Vazirani Algorithm V - Circuit Analysis Step 3

    • Bernstein Vazirani Algorithm VI - Circuit Analysis Step 4

    • Bernstein Vazirani Algorithm Handwritten Notes

  • 35

    Bernstein-Vazirani Algorithm with Qiskit

    • Bernstein-Vazirani Algorithm with Qiskit I

    • Bernstein-Vazirani Algorithm with Qiskit II

    • Bernstein-Vazirani Algorithm with Qiskit III

    • Bernstein-Vazirani Algorithm with Qiskit IV

    • Bernstein-Vazirani Algorithm with Qiskit V

    • Bernstein-Vazirani Algorithm with Qiskit Jupyter Notebook

  • 36

    ---Part 13 Simon's Algorithm---

    • Simon's Algorithm

  • 37

    Simon's Algorithm (Theory)

    • Simon's Algorithm I - Intro

    • Simon's Algorithm II - Problem

    • Simon's Algorithm III - Facts

    • Simon's Algorithm IV - Circuit Analysis Step 1

    • Simon's Algorithm V - Circuit Analysis Step 2

    • Simon's Algorithm VI - Circuit Analysis Step 3

    • Simon's Algorithm VII - Circuit Analysis Step 4

    • Simon's Algorithm VIII - Circuit Analysis Step 5

    • Simon's Algorithm IX - Circuit Analysis Step 6

    • Simon's Algorithm X - Circuit Analysis Step 7

    • Simon's Algorithm Handwritten Notes

  • 38

    Simon's Algorithm with Qiskit

    • Simon's Algorithm with Qiskit I

    • Simon's Algorithm with Qiskit II

    • Simon's Algorithm with Qiskit III

    • Simon's Algorithm with Qiskit IV

    • Simon's Algorithm with Qiskit V

    • Simon's Algorithm with Qiskit VI

    • Simon's Algorithm with Qiskit Jupyter Notebook

  • 39

    ---Part 14 Grover's Search Algorithm---

    • Grover's Search Algorithm

  • 40

    Grover's Search Algorithm (Theory)

    • Grover's Algorithm I - Intro

    • Grover's Search Algorithm II - The Algorithm

    • Grover's Algorithm III - Geometric Interpretation Step 1

    • Grover's Algorithm IV - Geometric Interpretation Step 2

    • Grover's Algorithm V - Geometric Interpretation Step 3

    • Grover's Algorithm VI - Matrix Representation

    • Grover's Algorithm VII - Grover's Circuit

    • Grover's Algorithm Handwritten Notes

  • 41

    Grover's Algorithm with Qiskit

    • Grover's Algorithm with Qiskit I

    • Grover's Algorithm with Qiskit II

    • Grover's Algorithm with Qiskit III

    • Grover's Algorithm with Qiskit IV

    • Grover's Algorithm with Qiskit V

    • Grover's Algorithm with Qiskit VI

    • Grover's Algorithm with Qiskit VII

    • Grover's Algorithm with Qiskit VIII

    • Grover's Algorithm with Qiskit IX

    • Grover's Algorithm with Qiskit Jupyter Notebook

  • 42

    ---Part 15 Quantum Fourier Transform (QFT)---

    • Quantum Fourier Transform

  • 43

    Quantum Fourier Transform (Theory)

    • QFT I - Intro

    • QFT II - QFT Formula

    • QFT III - Main QFT Derivation

    • QFT IV - Circuit Analysis Step 1

    • QFT V - Circuit Analysis Step 2

    • QFT VI - Circuit Analysis Step 3

    • QFT VII - Circuit Analysis Step 4

    • QFT VIII - Our & Qiskit Ordering 3 Qubit QFT Circuit

    • QFT IX - Qiskit Ordering 3 Qubit Circuit Analysis Step 1

    • QFT X - Qiskit Ordering 3 Qubit Circuit Analysis Step 2

    • QFT XI - Qiskit Ordering 3 Qubit Circuit Analysis Step 3

    • QFT XII - Qiskit Ordering 3 Qubit Circuit Analysis Step 4

    • QFT XIII - Qiskit Ordering 3 Qubit Circuit Analysis Step 5

    • QFT XIV - Qiskit Ordering 3 Qubit Circuit Analysis Step 6

    • QFT XV - Qiskit Ordering 3 Qubit Circuit Analysis Step 7

    • QFT XVI - Qiskit Ordering 3 Qubit Circuit Examples

    • QFT Handwritten Notes

  • 44

    Quantum Fourier Transform with Qiskit

    • Quantum Fourier Transform with Qiskit I

    • Quantum Fourier Transform with Qiskit II

    • Quantum Fourier Transform with Qiskit III

    • Quantum Fourier Transform with Qiskit IV

    • Quantum Fourier Transform with Qiskit V

    • Quantum Fourier Transform with Qiskit VI

    • Quantum Fourier Transform with Qiskit VII

    • Quantum Fourier Transform with Qiskit VIII

    • Quantum Fourier Transform with Qiskit IX

    • Quantum Fourier Transform with Qiskit X

    • Quantum Fourier Transform with Qiskit Jupyter Noyebook

  • 45

    ---Part 16 Quantum Phase Estimation (QPE)---

    • Quantum Phase Estimation

  • 46

    Quantum Phase Estimation (Theory)

    • QPE I - Intro

    • QPE II - QPE Registers

    • QPE III - Circuit Analysis Step 1

    • QPE IV - Circuit Analysis Step 2

    • QPE V - Circuit Analysis Step 3

    • QPE VI - Circuit Analysis Step 4

    • QPE VII - Phase Kickback

    • QPE VIII - QPE Circuit in Qiskit Ordering

    • Quantum Phase Estimation Handwritten Notes

  • 47

    Quantum Phase Estimation with Qiskit

    • Quantum Phase Estimation with Qiskit I

    • Quantum Phase Estimation with Qiskit II

    • Quantum Phase Estimation with Qiskit III

    • Quantum Phase Estimation with Qiskit IV

    • Quantum Phase Estimation with Qiskit V

    • Quantum Phase Estimation with Qiskit VI

    • Quantum Phase Estimation with Qiskit VII

    • Quantum Phase Estimation with Qiskit VIII

    • Quantum Phase Estimation with Qiskit Jupyter Notebook

  • 48

    ---Part 17 Shor's Algorithm (Coming Soon!)---

    • Shor's Algorithm

Top Student Testimonials

Hear from our students

“Srinjoy sir is a very humble and extremely helping person. He has high expertise in Artificial Intelligence & Quantum Computing. He has guided and mentored me for developing and applying the concepts of ML & DL at the industry level and because of his excellent mentorship, I was able to acquire multiple job offers. Whenever it comes to research related work then his dedication and hard work is always commendable. He is a great leader, teammate, and mentor. If you're looking for the proper guidance and support in the field of cutting edge technologies then Srinjoy sir is the perfect person to get in touch with, you won't regret going there as the learning experience is really good!”

Mohit Kumar

“I am pleased to share that due to your guidance and mentoring in machine learning and deep learning I learned a lot and I am able to land my first job in the field of data science and machine learning. Your perseverance and thorough knowledge about machine learning, deep learning, and its underlying concepts along with simple and intuitive explanations of hard concepts helped me in understanding the intricate concepts of in-demand technologies. I always wanted to work in the field of machine learning and deep learning and struggled a lot with numerous resources during my early days but your guidance and mentorship helped me a lot in understanding those concepts and landing my first job in the field of ML/ DL. I would always love to learn from you and have a mentor like you. Thanks a lot.”

Avinash Tiwari

“Srinjoy provided me excellent guidance in Machine Learning and Deep Learning related courses, with the help of which I successfully built a complete knowledge structure in these fields by understanding the intricate concepts in both mathematical algorithm aspects and practical coding deployment. His perseverance and thorough knowledge in Artificial Intelligence is the base of simple and intuitive explanations which are taught to all other students. It is because of his brief but effective explanations that I was able to progress a lot in my exploration of the in-demand technologies. I was always excited to work in the field of machine learning and deep learning and struggled a lot with numerous resources but Srinjoy’s mentorship proved to be a boon for me and helped me to get my first job in the field of ML/DL. I look forward to learning more from you. Thanks a lot.”

Tianyu Du

“Srinjoy sir’s teaching has helped me a lot in implementing various projects in the field of Artificial Intelligence and Machine Learning. Srinjoy sir’s mentorship has helped me to gain an internship & job, and I am really grateful for the quality time he dedicates. He taught me python modules for the NPTEL examination which helped me a lot. He has the excellent industry knowledge and a strong hold on concepts which helped me a lot. He is really an awesome mentor and you can rely upon him. His teachings have helped me in knowing the core concepts of deep learning and machine learning. I worked with him on a project related to self-driving cars which we completed with flying colors. I am always thankful to him for his guidance and mentorship. ”

Rohan Giri

“I am happy to share that due to your guidance and mentoring Srinjoy Ganguly sir, in machine learning and deep learning, I learned a lot and I am able to work on many projects with ease in the field of data science and machine learning. Your good nature, helping tendency and knowledge about machine learning, deep learning has helped me a lot which has landed me in a good position in my academics. Though this was a remote interaction it wasn't like that because of your efforts and your commitment to helping people who are struggling to come up. I should have been blessed to have a mentor like you. Thanks a lot sir.”

Abhirami Mohanarangam

FAQs

1. Why should I enroll in your program?

It is expected that the Quantum Computing industry is going to grow at a rapid rate from around USD 500 million in 2021 to nearly USD 1800 million (1.8 billion!) by 2026. Various industries such as banking, finance, space technology, defense, healthcare, pharmaceuticals, chemicals, energy, power, transportation, logistics, academia and government are going to do well out of this cutting-edge technology.


Several countries such as USA, China, Japan, UK, France, Germany, Spain, South Korea, India and Canada are investing large amounts of finances in the field of quantum computing due to its promising potential which is also going to create more jobs in this field. There is a huge talent deficit in the field of quantum computing and therefore much efforts and investments (in billions) have been put by various industries working on quantum computing through education and research. Some of the prominent players in quantum computing includes - IBM, Microsoft, Google, Intel, D-Wave, Xanadu Quantum Technologies, Rigetti Computing, Zapata Computing, Honeywell, IonQ, Cambridge Quantum Computing, Oxford Quantum Circuits and many more!


Just as Deep Learning, Machine Learning, Data Science or Artificial Intelligence became popular a few years back due to the availability of data sets and technology (GPUs and TPUs), in a very similar manner, the field quantum computing is witnessing rapid growth and is going to have a major impact in your lives through the release of products or services by industries. This is the time to make yourself future proof and remain ahead of others!


2. Is this course refundable? 

No, this course is not entitled for any refunds because the instructor Mr Srinjoy Ganguly has provided an immense amount of efforts into this course which is worth 4+ years of his experience in quantum computing. The instructor with his best of abilities has tried to deliver super high quality content equivalent to that of the quantum courses which are taught at top universities and industiries across the world. 

AdroitERA (AERA) reserves the right to revoke access from the course without any refund if you are found guilty of fraudulent acts such as copying the course contents, sharing with friends or family members without permission and pirating the course in any manner.


3. Will this course prepare me for the IBM Quantum Developer Certification Exam?

Yes! This course will prepare you for the IBM Quantum Developer Certification Exam as all the coding sections are prepared in suchh a way that it by default covers the exam syllabus.


4. What jobs will this training program prepare me for? 

This industry leading training program on quantum computing will prepare you for various job roles in the quantum computing industry such as quantum developer, quantum software developer, quantum software engineer, quantum computing consultants, quantum software architects and many others.

Your Instructor

IBM Qiskit Advocate | IBM Quantum Educator | Awarded Excellence in Education

Srinjoy Ganguly

IBM Qiskit Advocate | Visiting Professor @ Woxsen University

Srinjoy Ganguly is the founder & CEO of AERA (AdroitERA) an EdTech firm which provides training on cutting edge technologies and IBM recognized Quantum Educator. He is IBM Qiskit Advocate and possesses a Masters in Quantum Computing Technologies from Technical University of Madrid, Spain and an MSc in Artificial Intelligence from University of Southampton, UK. He has over 4+ years of experience in Quantum Computing and 5+ years of experience in Machine Learning, Deep Learning, AI. He has completed research-based courses on 5G signal processing systems from IIT Kanpur. He led, mentored and taught Quantum Machine Learning (QML) study space at QResearch QWorld and authored a book on Quantum Computing with Silq Programming. He has conducted Faculty Development Training at IIIT Pune by special invitation, gave expert talks on QML at IEEE SPS and has conducted several webinars at various institutes related to QML and Quantum Computing. He has been specially appointed and invited by Woxsen University as a Visiting Faculty to teach Quantum Computing to MBA students. He has also supervised research interns on QNLP, ZX calculus and Quantum Music as a part of QIntern 2021. His research interests include Quantum Machine Learning, Quantum Natural Language Processing (QNLP), Graphical Calculus for Quantum Computing (ZX Calculus) and Quantum Image Processing.