Advanced Program in Quantum Computing & Quantum Algorithms

The program introduces participants to the fundamentals of quantum computation and quantum algorithms using the popular Python programming language and Qiskit library. It introduces advanced quantum algorithms which are state-of-the-art and used by academia, research and industries.

Monthly Recurring Batch

Program Duration

6 Months

Learning Format

Blended Learning

Program Fees


Course Overview

The program introduces participants to the fundamentals of quantum computation and quantum algorithms using the popular Python programming language and Qiskit library. It introduces advanced quantum algorithms which are state-of-the-art and used by academia, research and industries.

Training Key Features

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    Acacia University Professional Development

    Acacia University Professional Development has initiated various programs in partnership with Airtics Education. The wide range of programs aims to upskill millions of students in trending technologies through a blend of theoretical and hands-on knowledge and are taught by leading academicians.

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    Skills Covered

    Introduction to Data Science

    Core Python - Basic concepts

    Data structure in Python

    OOP in Python

    Python Libraries for Data Science

    Mathematical Computing with Python (NumPy),

    Data Manipulation with Pandas


    Who Can Apply for the Course?

    This course is open to all who are interested in gaining an in depth understanding of Quantum Computing and it’s corresponding technical and business impact.

    On the path to quantum’s maturity, everybody from undergraduates to graduates to software developers, researchers, CEOs, data scientists, product managers, security experts, professors, video game developers, financial analysts, etc. can apply and harness quantum’s potential.

    Tools/ Frameworks/ Libraries

    Scripting tools


    IDE shell


    Application And Use Cases

    Quantum Finance
    Credit Risk Analysis
    Quantum Chemistry
    Protein Folding
    Quantum Optimization
    Battery Revenue Optimization
    Quantum Machine Learning
    Classification problems


    Candidates from engineering and physical sciences background could opt for this in-demand course. Individuals from a non-scientific background are also eligible for this cutting-edge course.


    Prerequisite knowledge on basic linear algebra and python programming will be beneficial.

    Course Modules

    Topics Covered

    • Linear Algebra, Complex Numbers and Probability Theory


    • Get to know about the Mathematical foundation of Quantum Computing starting with Linear Algebra which includes learning of vectors, matrices, operation and linear functions etc.
    • Be able to perform basic linear algebra operations.
    • Get introduced to Complex Numbers and concept of probability theory.

    Topics Covered

    • Basics of Computing, The Binary and Decimal Number System, Classical logic gates, Quantum Computational Complexity


    • Explore different number systems used to represent data in machines.
    • Learn about different classical logical gates.
    • Describe the differences between quantum and classical computation. 
    • Get introduced to the fundamentals of Quantum Computational Complexity.

    Topics Covered

    • Variable and Data types, Conditional Statements, Iteration Statements, Functions, Classes and Objects, Inheritance, Numpy, Matplotlib


    • To know the basic required python language for Quantum Computing
    • Get an Understanding of Object orientated programming.
    • Be capable of using basic functions like conditional statements, different types of loops etc
    • To know different data types like Tuples, Dictionaries and be able to convert datatypes.
    • Be able to work with different libraries like NumPy etc.
    Topics Covered
    • Young’s double slit experiment, Postulates of quantum mechanics, Superposition, Interference, Entanglement, Photoelectric effect, De-Broglie wavelength, Hamiltonian, Schrodinger equation, EM Spectrum
    • Understanding of the basic experiments and principles of quantum physics.
    • Explore importance of double slit experiments, wavefunction, symmetric and antisymmetric  property and postulates of Quantum Mechanics.
    • Get introduced to different properties of Quantum bit (qubit) and different equations involved in them.

    Topics Covered

    • Motivation to go for quantum, classical vs quantum computing, Introduction to Qubits – BraKet notation, Hilbert spaces, Pure & Mixed states, Bloch sphere, Unitary transformations Single & Multi qubit quantum logic gates, Bell states


    • Get to know the fundamentals of quantum information and computation with an intuitive understanding about the physics and mathematics
    • Explore single and multi-qubit quantum logic gates and their software implementation for algorithm building
    • Learn the mathematical and the physics of entanglement along with intuition of the quantum hardware setup

    Topics Covered

    • Quantum Teleportation, Quantum Superdense Coding, BB84 protocol


    • Know the comparison between classical communication and quantum communication along with their advantages
    • Experimentally understand the quantum teleportation and quantum key distribution protocols with their detailed mathematical derivation
    • Get introduced to basic hardware elements required to experimentally prove the quantum communication in global laboratories
    Topics Covered
    • Deutsch Algorithm, Deutsch-Jozsa Algorithm, Bernstein-Vazirani Algorithm, Simon’s Algorithm, Grover’s Search Algorithm, Quantum Fourier Transform, Quantum Phase Estimation, Shor’s Algorithm
    • Explore the very first quantum algorithms which proved to provide advantage over classical algorithms
    • Learn about quantum version of database search algorithm and visualize its speedup compared to classical algorithms
    • Analyse the complex fundamentals of quantum algorithms so as to gain intuitive understanding essential for advanced quantum algorithms
    Topics Covered
    • HHL Algorithm, Quantum Amplitude Estimation (QAE), Variational Quantum Algorithms (VQA), Variational Quantum Eigensolver (VQE), Quantum Approximate Optimisation Algorithm (QAOA)
    • Discover industry and research leading quantum algorithms used by academicians, professionals and researchers globally
    • Develop applications and case studies in different areas of the industry – chemistry, finance, optimization and machine learning
    • Gain deep understanding about variational algorithms so as to create your own customized quantum models using libraries and without libraries

    Interested in This Program? Secure your spot now.

    The application is free and takes only 5 minutes to complete.

      Student Reviews

      Veeraiah Yadav Doddaka
      IT Manager, Samsung

      I choose to learn Data Science and explored many options on which institute to join, among that what I found is Airtics as the best in terms of the course curriculum/on line content they designed and most…..

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      Prasad Joshi
      RF Optimization Engineer, Nokia

      I was a Data Science student at Airtics Education, which helped build a solid data science background and sharpen my programming skills…

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      Mohamed Hanan
      Procurement Assistant

      The program in Data Science offered by Airtics Education is rigorous and has provided me with a greater understanding of the data science world…

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      Career Support

      Capstone Projects & Internship/Projects

      AERA Academy provides internships in the respective field for a period of 2-3 months to all eligible and able students on the following projects –

      Capstone Projects & Internship/Projects includes:

      Frequently Asked Questions

      Data science isn’t just the way of the future, it’s the way of right now! It is being adopted in all sorts of industries, from health care to route planning, marketing & sales to banking industries and beyond. Even industries such as retail that you might not associate with big data are getting on board. Data science is the fuel of the 21st Century.

      We provide you with live recorded classes of the same session to follow up if you end up missing the same.

      Being a newbie in coding might be frightening. Python, however, is an exception. Especially when compared to more sophisticated languages like C, C++, and Java, it has an incredibly basic syntax and vocabulary, making it very easy to learn. Python is a clear choice of language for data scientists to learn.

      You’ll join a lot of people if you study Python. It’s one of the languages used the most in data science (and elsewhere). TIOBE’s 2020 index places it as the third most frequently spoken language in the world. It has surpassed my former favorite language, R, and has become the leader in data science in particular.

      Without at least a basic understanding of Python, it will be difficult to succeed in the field of data science. Fortunately, learning is fun!

      Aspirants and professionals who are having basic computer programming skills can enroll in the program.

      This course provides basic to advance programming knowledge. So having basic knowledge is an added benefit but not necessary.

      Python is a great language to learn for data science, but you may use the same abilities to get work in other areas of computer science as well. Since Python has been there and relevant for thirty years and is continually reinventing itself to be helpful for new occupations and vocations, it is more secure than any professional path. It’s possible that data science’s future is in doubt or that your professional objectives have changed. Python knowledge will benefit you in any situation.

      What is included in this course?

      I’m Interested in This Program

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        Course Preview

        Advanced Program in Quantum Computing & Quantum Algorithms

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