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Advanced Program in Quantum Computing & Quantum Algorithms

Transform your career with our cutting-edge 6-month Advanced Program in Quantum Computing & Quantum Algorithms, certified by Acacia University. This pioneering professional development program equips you with revolutionary skills in quantum mechanics, quantum algorithms, Python programming, and Qiskit implementation through 40 hours of live instructor-led training.

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  • Duration

6 Months

  • Modules

8 Modules

  • Assignments

16 Assignments

  • Format

Blended Learning

  • Projects

4 Projects

  • Level

Intermediate

Globally Recognized & Accredited:

15000

Students Trained Globally

25

Industry-Aligned Programs

70

Countries with Active Alumni

87

Career Transition Success

  • Industry-Standard Technology Stack

Tools & Technologies That Power Success

Master the complete data science ecosystem with hands-on experience using industry-leading tools and frameworks. Our Advanced Program in Data Science equips you with practical skills in Python programming, data manipulation, visualization, and machine learning – preparing you for real-world data challenges.

  • Production-Ready Skills
  • Industry-Relevant Tools
  • Hands-On Learning

Python

MySQL

learn anaconda

Anaconda

Jupyter Hub

Pandas

NumPy

Seaborn

Matplotlib

Excel

GIT

HTML

CSS

Join Airtics Education
  • Quantum Computing Technology Stack

Tools & Technologies That Power Success

Master the complete quantum computing ecosystem with hands-on experience using cutting-edge quantum frameworks and simulators. Our Advanced Program in Quantum Computing & Quantum Algorithms equips you with practical skills in Python programming, Qiskit development, quantum simulation, and algorithm implementation – preparing you for real-world quantum challenges.

  • Production-Ready Skills
  • Industry-Relevant Tools
  • Hands-On Learning

Python

Qiskit

learn anaconda

Anaconda

Jupyter Hub

Cirq

NumPy

Seaborn

Matplotlib

Excel

GIT

IBM Quantum

CSS

Join Airtics Education

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.
Airtics Education’s Advanced Programs are offered as part of Acacia University Professional Development Programs, and the learners are certified by the University.
Eligibility

Eligibility

This course is well suited for participants of all levels of experience because of the high demand for Data Science with Python programmers. Data Science with Python is beneficial for analytics professionals interested in Python, software and IT professionals interested in Analytics, as well as anyone with a genuine interest in Data Science.

Prerequisites

Good to have familiarity with basic concepts of mathematics and programming knowledge. Basic knowledge of Database tools and workflow will be a plus.

Course Modules

Module 1
Mathematics For Quantum Computing
Module 2
Computer Science For Quantum Computing
Module 3
Python For Quantum Computing
Module 4
Basics of Quantum Mechanics
Module 5
Introduction to Quantum Computing
Module 6
Quantum Communication Protocols
Module 7
Essential Quantum Algorithms
Module 8
Advanced Quantum Algorithms With Applications
Laying the Mathematical Foundation

Begin your journey into Quantum Computing by mastering the essential mathematical tools that underpin quantum theory. This module introduces you to the core concepts of Linear Algebra, Complex Numbers, and Probability Theory—each vital for understanding and applying quantum algorithms.

From Vectors to Probabilities

Learn to work with vectors, matrices, and linear transformations. Understand how quantum states are represented mathematically. Build confidence with complex numbers, and explore the fundamentals of probability theory as they relate to quantum measurements and uncertainty.

Learning Outcomes
Module Duration: 3–4 weeks

By completing this module, you will:

  • Understand the mathematical principles that form the basis of Quantum Computing
  • Gain hands-on skills in performing essential linear algebra operations involving vectors and matrices
  • Learn the role of complex numbers in quantum state representation
  • Get introduced to foundational probability theory relevant to quantum measurements and outcomes
  • Build a strong base to progress confidently into quantum circuits and algorithms in upcoming modules
Foundations of Computing and Logic

Begin your journey into quantum computing with a strong grasp of classical computing principles. Understand how data is represented through binary and decimal number systems and how traditional logic gates form the basis of computation.

Bridging Classical and Quantum Worlds

Gain insight into the key distinctions between classical and quantum computation. Explore how quantum computers process information differently, setting the stage for understanding their transformative potential.

Quantum Computational Complexity

Delve into the fundamentals of quantum computational complexity—an essential area that studies how efficiently quantum algorithms solve problems compared to classical ones. Build foundational knowledge necessary for advanced quantum computing modules.

Learning Outcomes
Module Duration: 2–4 weeks

By completing this module, you will:

  • Understand binary and decimal number systems and how machines use them to represent data
  • Identify and describe classical logical gates and their role in traditional computing
  • Differentiate between classical and quantum computational models
  • Gain introductory knowledge of quantum computational complexity and its significance
Essential Python Foundations

Gain proficiency in core Python concepts crucial for diving into the world of quantum computing. Master variables, data types, loops, and conditionals—the fundamental building blocks for writing clean and efficient code.

Object-Oriented Programming & Structures

Develop a solid grasp of object-oriented programming through hands-on experience with classes, objects, and inheritance. Learn how to structure code in reusable, scalable ways suitable for complex quantum problems.

Scientific Libraries for Quantum Readiness

Work with powerful Python libraries like NumPy for numerical operations and Matplotlib for data visualization. Learn how these tools support simulations and data analysis in quantum computing environments.

Learning Outcomes
Module Duration: 3–4 weeks

By completing this module, you will:

  • Acquire the foundational Python skills required for quantum computing
  • Understand object-oriented programming concepts and inheritance
  • Master the use of conditionals, iterations, and basic function definitions
  • Work fluently with data types such as tuples, lists, dictionaries, and learn data conversion

  • Gain experience using Python libraries like NumPy and Matplotlib for computation and visualization

Core Concepts and Foundational Experiments

Explore the fundamentals of quantum physics through key topics like Young’s double slit experiment, photoelectric effect, interference, and superposition. Understand the historical experiments that shaped quantum theory.

Postulates and Quantum Properties

Learn the postulates of quantum mechanics, wave-particle duality, and the significance of the De-Broglie wavelength. Dive into the Hamiltonian, symmetric and antisymmetric wavefunctions, and the foundational Schrödinger equation.

Introduction to Qubits and Quantum Behavior

Gain an introduction to quantum bits (qubits), entanglement, and quantum states. Understand how wavefunctions behave, and how these properties form the core of quantum computing and quantum information systems.

Learning Outcomes
Module Duration: 4–6 weeks

By completing this module, you will:

  • Understand fundamental quantum experiments such as the double slit and photoelectric effect

  • Learn core principles including superposition, interference, and entanglement
  • Grasp the postulates of quantum mechanics and mathematical formulations like the Schrödinger equation
  • Analyze the behavior of wavefunctions, including symmetry properties
  • Get introduced to the concept of qubits and their unique quantum characteristics
  • Understand key equations and concepts relevant to quantum computing foundations
Foundations of Quantum Information

Delve into the emerging field of quantum computing by understanding the fundamental differences between classical and quantum systems. Learn how quantum bits (qubits) operate within Hilbert spaces, and build your intuition around Bra-Ket notation and quantum states—pure, mixed, and visualized via the Bloch sphere.

Quantum Gates and Entanglement

Explore the world of quantum logic through single and multi-qubit gates, including unitary transformations and Bell states. Grasp the power of quantum entanglement, the mathematics behind it, and how it fundamentally changes computational logic and information transmission.

Introduction to Qubits and Quantum Behavior

Gain hands-on insights into how quantum algorithms are implemented in software, while also understanding the underlying physics of quantum hardware. This module acts as your entry point into the real-world application of quantum systems in computing.

Learning Outcomes
Module Duration: 3–5 weeks

By completing this module, you will:

  • Understand the basic concepts of quantum information and computation from both mathematical and physical perspectives
  • Explore Bra-Ket notation, Hilbert spaces, and qubit state representations including Bloch spheres
  • Learn and visualize key quantum logic gates used in computation—both single and multi-qubit
  • Develop an intuitive and theoretical understanding of entanglement and quantum logic operations
  • Build and simulate basic quantum circuits using software tools and comprehend the architecture of quantum hardware systems
Redefining Information Transfer

Dive into the next frontier of secure and instantaneous communication with quantum mechanics. This module introduces key quantum communication protocols that transcend the limitations of classical systems.

Protocols and Practical Implementation

Understand the science behind quantum teleportation, superdense coding, and BB84—a quantum key distribution protocol. Each protocol will be studied with mathematical depth and real-world implications in secure information transmission.

From Theory to Hardware

Gain an introduction to the hardware components used in global quantum labs for experimental validation. This includes an exploration of the tools that bring quantum communication from theoretical frameworks into practical, scalable systems.

Learning Outcomes
Module Duration: 4–6 weeks

By completing this module, you will:

  • Compare classical and quantum communication methods, identifying the advantages of quantum systems
  • Understand and mathematically derive protocols like quantum teleportation and quantum key distribution (QKD)
  • Gain exposure to the experimental setups and hardware required for implementing quantum communication in global research labs
  • Develop a foundational understanding necessary for future work in quantum networks and secure data systems
Foundation of Quantum Advantage

Dive into the pioneering algorithms that showcased the power of quantum computing over classical methods. Begin with Deutsch’s and Deutsch-Jozsa algorithms, which set the stage for quantum problem-solving efficiency.

Intelligent Search and Hidden Structure Problems

Understand algorithms like Grover’s Search and Simon’s Algorithm, which reveal how quantum systems can solve search and pattern problems exponentially faster than classical computers.

Mathematical Power of Quantum Mechanics

Explore the Quantum Fourier Transform, Phase Estimation, and Shor’s Algorithm to grasp the mathematical backbone of quantum computing. These tools unlock applications like cryptography, factorization, and signal processing in a quantum context.

Learning Outcomes
Module Duration: 3–4 weeks

By completing this module, you will:

  • Explore foundational quantum algorithms that demonstrate clear advantages over classical ones
  • Understand and visualize the efficiency of Grover’s Search in database querying
  • Analyze quantum phase estimation, Fourier transform, and Shor’s algorithm with conceptual clarity
  • Build an intuitive grasp of the logic behind key quantum algorithms to prepare for more advanced topics
Exploring Quantum Algorithm Breakthroughs

Dive into some of the most advanced quantum algorithms driving innovation in research and industry. Learn how leading-edge techniques like HHL, QAE, VQE, and QAOA are redefining computation across sectors.

From Theory to Practical Impact

Discover how quantum algorithms are being applied in real-world domains such as chemistry, finance, optimization, and machine learning. Analyze their computational advantages and limitations.

Variational Models and Custom Implementations

Build an in-depth understanding of variational quantum algorithms. Learn to design and implement your own quantum models using popular quantum computing libraries—or even from scratch.

Learning Outcomes
Module Duration: 4–6 weeks

By completing this module, you will:

  • Discover research-grade quantum algorithms like HHL, QAE, VQE, and QAOA
  • Apply quantum techniques across industries such as finance, chemistry, and machine learning
  • Develop case studies demonstrating quantum advantage in real-world scenarios
  • Gain expertise in variational quantum algorithms and their underlying mechanics
  • Create customized quantum models using libraries (like Qiskit or PennyLane) or implement them independently

Your Success Story Starts Here

Every image here tells a story of transformation, dedication, and success. Be the next to wear the cap and gown. Enroll today, and let your journey begin.

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What Our Students Say

Every student has a story—of ambition, of challenge, of growth. In their own words, they share how Airtics became a turning point in their learning journey and helped them move closer to their goals.

Pemsith Ravi

Thanks to the support of this prestigious institution – airtics. I was able to earn a master’s degree in data science. I had a fantastic educational experience there, and they possess a highly competent and knowledgeable lecturing panel. Anyone looking to make it major in the data science field should enrol in their course.
  • Verified Review

Zeeshan Ali

Airtics offers a truly transformative learning experience. The course content is up-to-date, the mentors are incredibly supportive, and the flexibility of the online platform made it easy to balance with my work. Highly recommended for anyone looking to upskill!

  • Verified Review

Aalaa Shbair

The experience at Airtics College has been tremendous for me. It has illuminated my path and opened the way for me to become a developer of solutions in my workplace. I cherish every moment of this online learning experience and the supportive community of instructors and peers.

  • Verified Review

Muhammad Fatouh

Airtics offered a great platform that allowed me to take a meaningful step forward in data science while balancing my demanding job as a telecom engineer. If you have a busy schedule and struggle with work-life balance, I encourage you to find a flexible platform like Airtics to pursue your goals.

  • Verified Review

Al Tayyab Bakhsh

Coming from a non-technical background in marketing, switching to data science was challenging. The faculty at Airtics was incredibly helpful, especially my mentor Miss Piyali, who guided me with patience every step of the way. Their mentorship gave me the confidence to succeed.

  • Verified Review

Dilnawaz Qureshi

Airtics provides an impressive curriculum for Python Full Stack development that is both well-structured and up-to-date. This comprehensive approach ensures we acquire a thorough understanding of the field and are well-prepared for real-world challenges.

  • Verified Review

Charuhaas Shenoy

Airtics offers a truly transformative learning experience. The course content is up-to-date, the mentors are incredibly supportive, and the flexibility of the online platform made it easy to balance with my work. Highly recommended for anyone looking to upskill!
  • Verified Review

Madonna Ghanem

The resources provided by Airtics for AI and ML students are top-notch. The institute has a well-equipped virtual lab with the latest software, allowing us to experiment with complex algorithms. The online library offers a wide range of reference materials and research papers.
  • Verified Review

Dhruv Narse

Airtics provides a conducive learning environment for data analytics students. They have experienced faculty, and provide access to the latest software and tools used in the industry. This ensures that we are well-prepared for our future careers in the field.

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Real-World Capstone Projects

Apply your data science skills to solve real business challenges through hands-on projects. Choose from our curated capstone projects or bring your own organizational problem to create a portfolio that showcases your expertise to future employers.

 

House Rental Predication

Build a machine learning model to predict house rental prices using market data, property features, and location analysis.
 

Image Classification

Develop a computer vision system using deep learning to automatically classify and categorize images.
 

Business Insights Reporting

Create interactive business dashboards that transform raw data into actionable insights and visual reports.

Learn from Industry Leaders & Experts

Learn from the best in the field. Our faculty combines academic brilliance with industry expertise, featuring PhD holders, senior data scientists, and AI researchers from top organizations.

Ms. PIYALI MONDAL - B&W
Ms. Piyali Mondal Head of Department
Ms. Priti Mondal - B&W
Ms. Priti Mondal Associate Faculty
Dr. Abdullah El Nokiti - B&W
Dr. Abdullah El-Nokiti Professor
Dr. Meraj Inamdar - B&W
Dr. Mohd Merajuddin Inamdar Professor
Dr. Madhavi Vaidya - B&W
Dr. Madhavi Vaidya Professor
Dr. Poonam Chaudhari - B&W
Dr. Poonam Chaudhari Professor
Dr. Anup Maurya - B&W
Dr. Anup Kumar Maurya Professor
Dr. Milan Joshi - B&W
Dr. Milan Amrutkumar Joshi Industry Expert
Dr. Mohamed Elhaw - B&W
Dr. Mohamed Elhaw Industry Expert
Dr. Pradeep Tiwari - B&W
Dr. Pradeep Tiwari Industry Expert
Global Student Community

Students from 60+ Countries Worldwide

Frequently Asked Questions

Find answers to common questions about our Advanced Program in Data Science. Learn about program details, requirements, and what to expect from this 6-month certification course.
Why should I join the Data Science program?
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.
What if I fail to attend the classes?
We provide you with live recorded classes of the same session to follow up if you end up missing the same.
How does Data Science differ from Big Data and Data Analytics?
Each of these technologies complements one another yet can be used as a separate entity. Big Data refers to any large and complex acquisition of data. Extracting meaningful information from data is why Data Analytics is used for. While Data Science is a multidisciplinary field that aims to produce broader insights.
What can I expect from the Data Science program?
Accelerated data science career guidance with world-class training on the most in-demand data science and machine learning skills. Training and hands-on experience with key tools and technologies including Python, PowerBi, and concepts of Machine Learning. Upon completing the program, you will be receiving an international certificate from Acacia University Professional Development (AUPD).
Who can join the program?
Aspirants and professionals who are having basic computer programming skills can enroll for the program.
Do I need prior experience in coding to learn the program?

Basic knowledge of programming logic and technology exposure will be helpful.

What are the current capabilities of Artificial Intelligence (AI)?
Google Duplex can make phone calls to make restaurant and hair appointments. Google Deep Mind won a global Starcraft game challenge against gaming pros. Amazon uses AI for book and product recommendations. Websites are using chatbots to answer basic customer queries. Airports are using image recognition for staff security. Rolls Royce is using AI for predictive maintenance and servicing of airplane engines. Informatica is using AI for compliance and data gathering and analysis purposes. Fintech is using AI to combine and analyze more diverse datasets. In healthcare, AI can help analyze more data for preventative medicine. Baidu in China is producing self-driving buses for large cities.
What is the future of Artificial Intelligence (AI)?

Automated transport, taking over dangerous jobs, robots working with humans, improved elderly care, cyborg (organic/bio-mechanic) organisms, environment monitoring and response to climate change goals.

What is TensorFlow?
TensorFlow is an end-to-end open-source platform for Machine Learning (ML). It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
Can a data analyst become a data scientist?
Yes. Many data analysts go on to become data scientists after gaining experience, advancing their programming and mathematical skills, and earning an advanced degree.‎
Should I study Data Analytics or Data Science?
Which you choose is largely a matter of preference. If you’re mathematically minded and enjoy the technical aspects of coding and modelling, a data science degree could be a good fit. On the other hand, if you love working with numbers, communicating your insights, and influencing business decisions, consider a degree in data analytics. Whether you study data science or data analytics, you’ll be building skills for an in-demand, high-paying career. ‎
How tough is deep learning?
The technical skills and concepts involved in machine learning and deep learning can certainly be challenging at first. But if you break it down using the learning pathways outlined above, and commit to learning a little bit every day, it’s possible. Plus, you don’t need to master deep learning or machine learning to begin using your skills in the real world.‎
Is Machine Learning a good career?

Yes. The average base pay for a machine learning engineer in the US is $123,608, as of April 2022. According to a December 2020 study by Burning Glass, demand for AI and machine learning skills is projected to grow by 71 per cent over the next five years. The same study reports a $14,175 salary premium associated with these skills.

Still have questions?

If you have any other questions or need further information about our Advanced Program in Data Science, don’t hesitate to contact us. Our admissions team is here to help you take the next step in your data science career.

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