The Best Free Tools & Platforms to Practise Quantum Computing Skills in 2025/26
Quantum computing has moved from theory to practice. No longer confined to physics labs, it is now a serious field of research, development, and even early commercial application. From cryptography and drug discovery to optimisation in finance and logistics, quantum computing is shaping up to be one of the most transformative technologies of the coming decades.
For job seekers in the UK, this is a once-in-a-generation opportunity. Roles in quantum computing are appearing not only in big tech but also in finance, aerospace, pharmaceuticals, and government research. Employers want candidates who don’t just understand the theory, but who can actually design, test, and deploy quantum algorithms.
The challenge? Quantum hardware is still rare, expensive, and limited. But the good news is that there are many free tools, platforms, and resources you can use to practise quantum computing skills today — building your knowledge, portfolio, and career prospects without spending a penny.
This article explores the best free platforms for learning and practising quantum computing, how to use them effectively, and how to build portfolio projects that stand out to UK employers.
Why Practising Quantum Computing Skills Matters
Quantum computing is unlike any other computing field. The rules of quantum mechanics govern it, and those rules defy classical intuition. You can’t just memorise formulas or read about qubits — you need hands-on practice to understand how they behave in circuits and algorithms.
By practising quantum computing, you will:
Understand the fundamentals deeply: Implementing superposition, entanglement, or teleportation in code cements concepts that are abstract on paper.
Get used to limitations: Real quantum hardware has noise, decoherence, and limited qubit counts. Practising on simulators and real devices teaches you what’s realistic.
Experiment with algorithms: From Shor’s factoring algorithm to quantum machine learning, you’ll learn what works and what doesn’t.
Develop transferable skills: Quantum programming often uses Python, linear algebra, and machine learning — skills that are valuable across tech.
Build a portfolio: Employers want to see GitHub repositories, notebooks, or blog posts showing you can apply your knowledge.
Free Quantum Learning Platforms
Before diving into software, it’s worth exploring some structured learning resources. These courses and platforms offer free access to lectures, labs, and exercises:
IBM Quantum Learning
IBM provides free online lessons, tutorials, and interactive labs through its Quantum Learning platform. It ranges from basics of qubits and quantum gates to advanced topics like quantum error correction and quantum machine learning.
OpenLearn – Introduction to Quantum Computing
The Open University offers a free introduction to quantum computing that covers gates, circuits, and measurement. It’s beginner-friendly and gives you the conceptual foundation you need before using software.
IBM SkillsBuild & Virtual Labs
IBM’s SkillsBuild offers short courses with virtual labs that let you practise in real environments. Perfect if you want a guided start with immediate hands-on exercises.
Linux Foundation Fundamentals of Quantum Computing
This free course covers quantum theory, algorithms, and applications, alongside ethical and industry considerations. It’s well-suited for professionals exploring quantum’s impact on their sector.
Quantum CERN – Practical Introduction
CERN offers a practical introduction to quantum computing that includes building algorithms in simulators and running them on real hardware. It bridges theory with practical coding.
Free Software & Frameworks for Practising Quantum Computing
Once you understand the basics, you’ll need tools to write code, simulate quantum circuits, and run experiments. Luckily, many of the leading platforms are free.
1. IBM Quantum Platform and Qiskit
IBM’s platform allows free access to real quantum hardware (on a limited basis) and powerful simulators. Qiskit, their open-source software development kit, lets you build circuits, run algorithms, and analyse results. It is Python-based and widely used in academia and industry.
2. Microsoft Quantum Development Kit and Q#
Microsoft’s toolkit includes the Q# programming language, libraries, and simulators. It’s free to download and allows you to practise algorithm design without needing access to hardware.
3. Cirq and TensorFlow Quantum
Google’s Cirq is a Python library for creating and simulating quantum circuits. TensorFlow Quantum extends this into hybrid quantum-classical workflows, making it a valuable tool for exploring quantum machine learning.
4. QuTiP (Quantum Toolbox in Python)
QuTiP is designed for simulating quantum systems. It allows you to model dynamics, Hamiltonians, and open quantum systems. It’s a strong choice for those interested in the physics side of quantum computing.
5. OpenFermion
OpenFermion focuses on translating quantum chemistry problems into quantum circuits. If you’re interested in applying quantum computing to materials science or pharmaceuticals, this is the tool to use.
6. ProjectQ
An open-source quantum programming framework that includes simulators and a Python interface. It is lightweight and flexible, making it good for experimentation and algorithm development.
7. Browser-Based Quantum Simulators
Free tools like Quirk let you build and test circuits entirely in your browser. While limited, they are perfect for quick experimentation and learning without installation.
Project Ideas for Practising Quantum Computing
The best way to show off your skills is to build small projects. Here are some ideas:
Quantum Circuit DemonstrationsCreate circuits that generate Bell states, GHZ states, or implement quantum teleportation. These are the “hello world” projects of quantum computing.
Quantum Optimisation ProblemsUse the Quantum Approximate Optimisation Algorithm (QAOA) or the Variational Quantum Eigensolver (VQE) to tackle small optimisation tasks like knapsack or max-cut problems.
Hybrid Quantum-Classical Machine LearningExperiment with TensorFlow Quantum or Qiskit to build hybrid models where quantum circuits act as layers in a classical ML model.
Quantum Chemistry SimulationApply OpenFermion to simulate the ground state energy of simple molecules like hydrogen or lithium hydride. This is a realistic use case for quantum computers.
Noise and Error AnalysisRun the same circuits on simulators and real hardware. Compare results to study the effect of noise, then experiment with error mitigation techniques.
Document these projects on GitHub or in blog posts. Screenshots of circuits, visualisations of outputs, and code notebooks are excellent portfolio material.
Open Communities and Collaboration
Quantum computing is a small but fast-growing field, and communities play a big role in learning.
Quantum Open Source Foundation (QOSF): Supports open projects and mentorship opportunities.
IBM Quantum Community: Active forums and events to help learners.
GitHub Projects: Contributing to Qiskit, Cirq, or ProjectQ repositories is a great way to learn and network.
Conferences and Meetups: Many are free to attend virtually, offering opportunities to hear from experts.
Joining these groups will not only help you solve problems but also connect you with potential employers and collaborators.
Learning Roadmap for Quantum Computing
Quantum computing can feel overwhelming, but you can make steady progress by following a structured path:
Master the FundamentalsStart with linear algebra, probability, and the basics of quantum mechanics. Free courses from OpenLearn or the Linux Foundation are perfect here.
Experiment with SimulatorsBuild small circuits in Quirk, Qiskit, or Cirq. Focus on creating and measuring superposition and entanglement.
Progress to Real HardwareUse the IBM Quantum Platform to run small experiments on actual quantum devices. Compare results with simulators to learn about noise.
Tackle AlgorithmsImplement algorithms like Grover’s search, Deutsch-Jozsa, or Shor’s algorithm. Even small implementations show understanding.
Explore ApplicationsMove into optimisation, quantum chemistry, or machine learning with frameworks like OpenFermion and TensorFlow Quantum.
Build a Portfolio ProjectPick one application — such as optimisation or quantum chemistry — and develop a well-documented project that shows end-to-end skills.
Final Thoughts
Quantum computing is still in its early days, but it is advancing rapidly. By starting now, you’ll be ahead of the curve when large-scale commercial applications emerge.
With tools like Qiskit, Cirq, QuTiP, ProjectQ, and OpenFermion, along with platforms like IBM Quantum and Microsoft Quantum Development Kit, you can practise quantum computing skills entirely for free. Add in free courses, online simulators, and open communities, and you have everything you need to prepare for a career in this exciting field.
Employers in the UK will look for candidates who have shown initiative — who have experimented with quantum circuits, built small projects, and contributed to open source. Start practising today, and you could be among the first generation of professionals shaping the quantum future.
