10 answers
Momin
Student
Navi Mumbai, Maharashtra, India
6
Questions
Updated
5844 views
How do I learn Quantum Computing from scratch?
Are there any resources to get started in Quantum Computing, for a person not having a heavy math or physics background?
Or is it necessary to know all the math and physics involved, to get into quantum programming?
I am an undergrad studying Data Science currently.
Login to comment
8 answers
Doc Frick
Career Coach and Mentor
1942
Answers
California, CA
Updated
Doc’s Answer
To learn quantum computing from scratch Momin, you need to build a foundation in linear algebra, complex numbers, and probability theory. You'll also need to grasp quantum mechanics concepts like superposition and entanglement, and familiarize yourself with quantum programming languages like Qiskit. Online resources, communities, and hands-on experiments can further enhance your learning journey.
1️⃣ PHYSICS
What differentiates quantum computers from the computers we have today is how they use the phenomenon of quantum physics and mechanics, such as entanglement and quantum superposition, to solve problems differently. In the case of classic computing, you don’t need to know precisely how a computer's hardware works in order to create with it. Mostly, you just need to know how to use it. Quantum computing is the opposite (at least right now), particularly at the algorithmic and software levels. To be a quantum software programmer, you need to know how a quantum computer works and then use that knowledge to build your applications, which will require you to understand some physics and the mechanics of how quantum algorithms work. This was the case for classical computers in their early stages, and hopefully, as quantum technology advances, knowing exactly how these computers work won't be necessary for people to develop and use these them.
2️⃣ MATH
Math is probably the first thing that might discourage someone from getting into quantum computing. That said, math is also an essential part of most technical and scientific fields, including data science, statistics and artificial intelligence. When it comes to quantum computing, two particular branches of math are heavily involved in describing and analyzing a quantum computer’s behavior: linear algebra and probability theory. Linear algebra is the core way of representing all aspects of a quantum system — from the qubits themselves, to their current state and even how the different gates in a quantum circuit behave. Meanwhile, we use probability theory to predict the system’s behavior and its possible outputs.
3️⃣ COMPUTER SCIENCE
Most theory topics are relevant although are less crucial at first: i.e. algorithms, cryptography, information theory, error-correcting codes, optimization, complexity, machine learning. If you haven't had any CS theory exposure, undergrad algorithms is a good place to start because it will show you CS-theory ways of thinking. To get started with quantum computing in the current landscape, you’ll probably need to know some programming basics. Currently, some programming languages are entirely designed to program quantum computers. Still, they’re designed to be similar to existing classical programming languages to make the transition to quantum much easier. Python is one of the most frequently used programming languages to program quantum computers today. Many companies such as IBM and Google have released Python packages that can be used to learn the basics of quantum computers and implement different algorithms.
4️⃣ ELECTRONICS
Because quantum computing is, after all, a computing field, we can say it has three primary layers: algorithmic, software and hardware. If you decide to pursue a career in this field, you’ll probably be drawn toward specializing in one of these areas. Suppose the hardware aspect of quantum computing intrigues you the most. In that case, having a fundamental knowledge of electronics and electrical components can help you take your first step in the field. Of course, if hardware becomes your speciality, developing expertise in electronics will become a necessity.
CONCLUSION
Embarking on the journey of learning quantum computing may seem daunting, but with perseverance and dedication, you can acquire the knowledge and skills necessary to explore this transformative field. The more official advice will tell you to "build a strong foundation in quantum mechanics and develop your mathematical proficiency", but this doesn't mean there's not a role for you sooner rather than that. It's not just for the experts now. With some understanding of the common programming languages in quantum computing (such as Python), you can easily engage with the quantum computing community, study quantum algorithms, and conduct hands-on experiments with some of the cloud-based and open source tools. My advice is to embrace the continuous learning process and stay curious, as quantum computing is a rapidly evolving field with immense possibilities waiting to be explored. As we will see in my next post where I will recommend some great open source projects to help you get started.
I hope this will be helpful Momin.
1️⃣ PHYSICS
What differentiates quantum computers from the computers we have today is how they use the phenomenon of quantum physics and mechanics, such as entanglement and quantum superposition, to solve problems differently. In the case of classic computing, you don’t need to know precisely how a computer's hardware works in order to create with it. Mostly, you just need to know how to use it. Quantum computing is the opposite (at least right now), particularly at the algorithmic and software levels. To be a quantum software programmer, you need to know how a quantum computer works and then use that knowledge to build your applications, which will require you to understand some physics and the mechanics of how quantum algorithms work. This was the case for classical computers in their early stages, and hopefully, as quantum technology advances, knowing exactly how these computers work won't be necessary for people to develop and use these them.
2️⃣ MATH
Math is probably the first thing that might discourage someone from getting into quantum computing. That said, math is also an essential part of most technical and scientific fields, including data science, statistics and artificial intelligence. When it comes to quantum computing, two particular branches of math are heavily involved in describing and analyzing a quantum computer’s behavior: linear algebra and probability theory. Linear algebra is the core way of representing all aspects of a quantum system — from the qubits themselves, to their current state and even how the different gates in a quantum circuit behave. Meanwhile, we use probability theory to predict the system’s behavior and its possible outputs.
3️⃣ COMPUTER SCIENCE
Most theory topics are relevant although are less crucial at first: i.e. algorithms, cryptography, information theory, error-correcting codes, optimization, complexity, machine learning. If you haven't had any CS theory exposure, undergrad algorithms is a good place to start because it will show you CS-theory ways of thinking. To get started with quantum computing in the current landscape, you’ll probably need to know some programming basics. Currently, some programming languages are entirely designed to program quantum computers. Still, they’re designed to be similar to existing classical programming languages to make the transition to quantum much easier. Python is one of the most frequently used programming languages to program quantum computers today. Many companies such as IBM and Google have released Python packages that can be used to learn the basics of quantum computers and implement different algorithms.
4️⃣ ELECTRONICS
Because quantum computing is, after all, a computing field, we can say it has three primary layers: algorithmic, software and hardware. If you decide to pursue a career in this field, you’ll probably be drawn toward specializing in one of these areas. Suppose the hardware aspect of quantum computing intrigues you the most. In that case, having a fundamental knowledge of electronics and electrical components can help you take your first step in the field. Of course, if hardware becomes your speciality, developing expertise in electronics will become a necessity.
CONCLUSION
Embarking on the journey of learning quantum computing may seem daunting, but with perseverance and dedication, you can acquire the knowledge and skills necessary to explore this transformative field. The more official advice will tell you to "build a strong foundation in quantum mechanics and develop your mathematical proficiency", but this doesn't mean there's not a role for you sooner rather than that. It's not just for the experts now. With some understanding of the common programming languages in quantum computing (such as Python), you can easily engage with the quantum computing community, study quantum algorithms, and conduct hands-on experiments with some of the cloud-based and open source tools. My advice is to embrace the continuous learning process and stay curious, as quantum computing is a rapidly evolving field with immense possibilities waiting to be explored. As we will see in my next post where I will recommend some great open source projects to help you get started.
I hope this will be helpful Momin.
Munu Gandhi
Technology
5
Answers
Oak Brook, Illinois
Updated
Munu’s Answer
A good place to start is with ChatGPT, Gemini, or Perplexity (or a combination of them). Ask the platforms to summarize what you'd like to learn at a novice/beginner level.
Karin P.
Lecturer, Academic Advisor, Career Coach
1091
Answers
Göttingen, Lower Saxony, Germany
Updated
Karin’s Answer
Hi Momin,
Try classcentral.com to find a course that suits you:
https://www.classcentral.com/subject/quantum-computing
They curate courses from different sources: universities, IBM, YouTube, Coursera, etc. So, you can get a quick overview what's out there.
I hope this helps! All the best!
KP
Try classcentral.com to find a course that suits you:
https://www.classcentral.com/subject/quantum-computing
They curate courses from different sources: universities, IBM, YouTube, Coursera, etc. So, you can get a quick overview what's out there.
I hope this helps! All the best!
KP
Puneet Garg
Technology Consultant
21
Answers
Noida, Uttar Pradesh, India
Updated
Puneet’s Answer
Quantum computing might seem like something out of a science fiction story, but starting from the beginning is totally possible and really exciting. Here's a simple guide to help you get started:
Step 1: Build Your Foundations
- Math: Refresh your knowledge of linear algebra, complex numbers, and probability.
- Physics: Learn the basics of quantum mechanics, like superposition and entanglement.
- Programming: Python is key here. If you're new to it, begin with beginner tutorials.
Step 2: Dive into Quantum Concepts
- Discover what makes quantum computers unique.
- Get to know qubits, quantum gates, and quantum circuits.
Step 3: Start Learning with Hands-On Platforms
- IBM Quantum Learning offers free courses and simulators to help you build and run quantum circuits.
- Coursera has a beginner course that teaches quantum computing with Python and Qiskit, and you don't need any prior experience.
Step 4: Experiment and Build
- Try simple projects, like a quantum random number generator or basic quantum algorithms.
- Check out this DIY guide that shows how to build quantum circuits using affordable parts.
Step 5: Keep Exploring
- Follow quantum computing blogs, YouTube channels like Qiskit’s, and research papers.
- Join communities like the Qiskit Slack or Reddit’s r/QuantumComputing to connect with others.
Step 1: Build Your Foundations
- Math: Refresh your knowledge of linear algebra, complex numbers, and probability.
- Physics: Learn the basics of quantum mechanics, like superposition and entanglement.
- Programming: Python is key here. If you're new to it, begin with beginner tutorials.
Step 2: Dive into Quantum Concepts
- Discover what makes quantum computers unique.
- Get to know qubits, quantum gates, and quantum circuits.
Step 3: Start Learning with Hands-On Platforms
- IBM Quantum Learning offers free courses and simulators to help you build and run quantum circuits.
- Coursera has a beginner course that teaches quantum computing with Python and Qiskit, and you don't need any prior experience.
Step 4: Experiment and Build
- Try simple projects, like a quantum random number generator or basic quantum algorithms.
- Check out this DIY guide that shows how to build quantum circuits using affordable parts.
Step 5: Keep Exploring
- Follow quantum computing blogs, YouTube channels like Qiskit’s, and research papers.
- Join communities like the Qiskit Slack or Reddit’s r/QuantumComputing to connect with others.
Patrick Meyer
Executive - Data Analytics and AI
1058
Answers
Naperville, Illinois
Updated
Patrick’s Answer
I want you to know that learning quantum computing from scratch is absolutely achievable without a heavy math or physics background, and your data science foundation actually provides significant advantages since you already understand programming concepts, linear algebra basics, and probability theory - all core to quantum computing. You don't need to master all the physics first because modern quantum computing allows you to start programming quantum circuits without diving deep into quantum mechanics theory, much like web development where you don't need to understand electron movement through transistors to build websites.
I would strongly suggest that you begin with practical quantum programming platforms like IBM Qiskit, Microsoft Q# and Azure Quantum, or Google Cirq, which offer excellent tutorials, simulators, and interactive resources that let you write quantum code and see results immediately. The essential math requirements are surprisingly minimal - you'll need comfort with linear algebra (vectors, matrices, basic operations), basic complex numbers, and probability theory, most of which you likely already have from your data science background.
I am going to suggest something I did when I wanted to first learn about Quantum and that is that I started by following a structured learning path starting with foundations using resources like "Quantum Computing: An Applied Approach" by Hidary or IBM's free Qiskit textbook for 2-3 months, then move to hands-on programming for 3-4 months building simple algorithms before specializing in areas like quantum machine learning. Like me, your data science background is actually a significant asset because quantum computing intersects heavily with data science in optimization, machine learning, and cryptography, and companies specifically seek people who can bridge quantum computing with practical data applications. The field needs professionals who can translate quantum capabilities into real-world solutions rather than just theoretical physicists, making your practical programming mindset exactly what the quantum computing industry needs as it transitions from research to application - so start programming quantum circuits immediately rather than spending months on physics theory.
I would strongly suggest that you begin with practical quantum programming platforms like IBM Qiskit, Microsoft Q# and Azure Quantum, or Google Cirq, which offer excellent tutorials, simulators, and interactive resources that let you write quantum code and see results immediately. The essential math requirements are surprisingly minimal - you'll need comfort with linear algebra (vectors, matrices, basic operations), basic complex numbers, and probability theory, most of which you likely already have from your data science background.
I am going to suggest something I did when I wanted to first learn about Quantum and that is that I started by following a structured learning path starting with foundations using resources like "Quantum Computing: An Applied Approach" by Hidary or IBM's free Qiskit textbook for 2-3 months, then move to hands-on programming for 3-4 months building simple algorithms before specializing in areas like quantum machine learning. Like me, your data science background is actually a significant asset because quantum computing intersects heavily with data science in optimization, machine learning, and cryptography, and companies specifically seek people who can bridge quantum computing with practical data applications. The field needs professionals who can translate quantum capabilities into real-world solutions rather than just theoretical physicists, making your practical programming mindset exactly what the quantum computing industry needs as it transitions from research to application - so start programming quantum circuits immediately rather than spending months on physics theory.
David Allen
Consultant
84
Answers
Dallas, Texas
Updated
David’s Answer
Getting started with quantum computing doesn’t require a deep background in physics or advanced math right away—especially if your focus is on the programming and application side rather than the theoretical foundations. As a data science undergrad, you already have a good foundation in logic, linear algebra, and algorithms, which are more relevant to quantum programming than quantum physics. Begin by learning the basic concepts such as qubits, superposition, entanglement, and quantum gates. Introductory tutorials and visualizations, like those from IBM’s Quantum Computing for the Very Curious or Microsoft's Quantum Katas, are designed to be accessible for beginners.
Once you have a conceptual grasp, start learning a quantum programming language like Qiskit (from IBM) or Cirq (from Google). These frameworks let you write and simulate quantum circuits using Python, which makes it easier for people with a programming background to dive in. IBM’s Qiskit Textbook is a particularly beginner-friendly, interactive guide that teaches quantum computing concepts alongside practical coding examples. You’ll get hands-on experience with creating circuits, understanding quantum algorithms (like Grover’s and Shor’s), and even running your code on real quantum machines via the IBM Quantum Experience.
While advanced math (especially linear algebra and complex numbers) and quantum mechanics become more important if you want to dive deep into algorithm design or theoretical research, they are not prerequisites for getting started. As you grow more curious and comfortable, you can gradually learn the necessary math and physics in context, rather than upfront. Think of it like learning machine learning—you don’t need to understand all of the calculus and statistics at first to build and run models. Similarly, you can begin exploring quantum computing today and build up your knowledge layer by layer.
Once you have a conceptual grasp, start learning a quantum programming language like Qiskit (from IBM) or Cirq (from Google). These frameworks let you write and simulate quantum circuits using Python, which makes it easier for people with a programming background to dive in. IBM’s Qiskit Textbook is a particularly beginner-friendly, interactive guide that teaches quantum computing concepts alongside practical coding examples. You’ll get hands-on experience with creating circuits, understanding quantum algorithms (like Grover’s and Shor’s), and even running your code on real quantum machines via the IBM Quantum Experience.
While advanced math (especially linear algebra and complex numbers) and quantum mechanics become more important if you want to dive deep into algorithm design or theoretical research, they are not prerequisites for getting started. As you grow more curious and comfortable, you can gradually learn the necessary math and physics in context, rather than upfront. Think of it like learning machine learning—you don’t need to understand all of the calculus and statistics at first to build and run models. Similarly, you can begin exploring quantum computing today and build up your knowledge layer by layer.
Jorge Hurtado
Unified Service Research
1
Answer
Coconut Creek, Florida
Updated
Jorge’s Answer
Learning a new skill often involves following specific guidelines and rules related to your practice, career, or degree.
Quantum computing is the future of technology, combining quantum mechanics and computing. To get started, it's important to understand the basic concept of quanta and how it applies to computing. This field isn't just about using a computer; it's about understanding science and expanding our knowledge through technology.
Begin by learning the basics: algorithms, vectors, and related concepts. Use this knowledge to develop projects that can be shared online. If you have questions or need help, don't hesitate to reach out.
Quantum computing is the future of technology, combining quantum mechanics and computing. To get started, it's important to understand the basic concept of quanta and how it applies to computing. This field isn't just about using a computer; it's about understanding science and expanding our knowledge through technology.
Begin by learning the basics: algorithms, vectors, and related concepts. Use this knowledge to develop projects that can be shared online. If you have questions or need help, don't hesitate to reach out.
Karan Gupta
Software Developer
22
Answers
Bengaluru, Karnataka, India
Updated
Karan’s Answer
Hi Momin,
It depends on which layer of Quantum Computing stack you aspire to work upon.
If you want to be able to use the infrastructure of Quantum Computing to run your tasks, apps and workflows:
1. Learn Quantum Computing languages released by Google, Microsoft, IBM, Nvidia etc.
2. Experiment extensively inside their cloud hosted playgrounds
If you want to be able to work on building different layers of the infrastructure itself, then you would need to brush up on basics of core Physics and Maths and work your way upwards from there.
All The Best,
Karan Gupta
It depends on which layer of Quantum Computing stack you aspire to work upon.
If you want to be able to use the infrastructure of Quantum Computing to run your tasks, apps and workflows:
1. Learn Quantum Computing languages released by Google, Microsoft, IBM, Nvidia etc.
2. Experiment extensively inside their cloud hosted playgrounds
If you want to be able to work on building different layers of the infrastructure itself, then you would need to brush up on basics of core Physics and Maths and work your way upwards from there.
All The Best,
Karan Gupta