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quantum computing learning paths skip to main content quantumcomputing courses com courses all courses course platforms coursera edx udemy brilliant hardware providers google quantum ai ibm quantum ionq quantinuum amazon braket azure quantum quera rigetti d wave tutorials all tutorials hello world qiskit hello world cirq hello world pennylane hello world braket quantum gates grover s algorithm shor s algorithm reference all frameworks qiskit cirq pennylane amazon braket pyquil tket d wave ocean q explore learn learning paths prerequisites programming guide case studies glossary books quantum news podcasts tools bloch sphere quantum pinball guides algorithm guide hardware guide qubit types framework comparison migration guide language timeline cheat sheets career events 2026 jobs careers certifications salary guide universities interview prep faq troubleshooting about about team search browse courses home learning paths structured journeys learning paths four paths from complete beginner to research ready pick where you are now each path builds on the last by dr donovan founder quantumcomputingcourses com last reviewed june 2026 4 paths built around free courses tested tutorials and interactive tools in this guide 5 sections 01 path 01 the complete beginner 02 path 02 first quantum code qiskit 03 path 03 quantum machine learning 04 path 04 research track 05 questions people ask the short version path 01 the complete beginner understand quantum computing concepts without any maths 2 3 weeks at 20 min day path 02 first quantum code qiskit write and run your first quantum circuits in python 4 6 weeks at 30 min day path 03 quantum machine learning apply quantum computing to machine learning problems 6 8 weeks at 45 min day path 04 research track develop deep theoretical and practical understanding for research or engineering roles 3 6 months at 60 min day the paths are cumulative but you can enter at the level that matches your background path 01 the complete beginner understand quantum computing concepts without any maths 2 3 weeks 20 min day prerequisites none 6 steps beginner reset where you re headed you ll be the person who can explain superposition entanglement and why quantum computers matter without hand waving to anyone who asks you ll understand what ibm and google are actually building and why it isn t just faster classical computing start here introduction to quantum computing free coursera course no maths required great conceptual grounding read what is a qubit clear explanation of how qubits differ from classical bits read quantum entanglement explained what entanglement actually means and why it matters explore bloch sphere simulator visualize qubit states interactively see superposition in action you can now visualize a qubit state that mental picture will stay with you browse quantum computing glossary key terms explained in plain language bookmark and revisit optional quantum pinball learn gate sequences through gameplay surprisingly effective you now understand quantum computing if a step is hard that s useful information it tells you exactly what to study next hard is not the same as wrong direction path 02 first quantum code qiskit write and run your first quantum circuits in python 4 6 weeks 30 min day prerequisites python basics high school maths 9 steps intermediate reset where you re headed you ll open a jupyter notebook write a quantum circuit from scratch run it on real ibm quantum hardware over the cloud and understand every line of output including what the noise means quantum programming will feel like programming prerequisite linear algebra brilliant self paced fills the maths gaps you ll need for circuits foundation quantum gates explained how gates work and the matrix maths behind h cnot and toffoli code hello world qiskit your first quantum circuit from scratch install build and run you ve run real quantum code every quantum programmer started exactly here deep dive getting started with qiskit circuits backends transpilation and running on real ibm hardware reference qiskit framework reference api overview and code examples to keep open while you work algorithm bernstein vazirani algorithm find a hidden string in one query the cleanest example of quantum speedup algorithm grover s algorithm the canonical quantum search speedup implement it step by step you ve implemented a real quantum algorithm this is the thing lov grover proved in 1996 algorithm shor s algorithm how quantum computers threaten rsa and the maths behind it advanced quantum algorithms and error correction delft edx free to audit takes you from circuits to real algorithms you are now a quantum programmer if a step is hard that s useful information it tells you exactly what to study next hard is not the same as wrong direction path 03 quantum machine learning apply quantum computing to machine learning problems 6 8 weeks 45 min day prerequisites python numpy sklearn basic linear algebra 6 steps advanced reset where you re headed you ll implement a quantum classifier in pennylane train it on real data compare it to its classical equivalent and have a grounded opinion on where quantum ml is actually useful versus where it s hype that last part matters foundation pennylane hello world first circuits in pennylane the leading framework for quantum ml core quantum ml classifier with pennylane build a variational quantum classifier and train it on real data you ve trained a quantum model this is genuinely new territory for most engineers advanced vqe with pennylane variational quantum eigensolver optimising parameterised circuits reference pennylane framework reference devices transforms and autodiff the api you ll use daily theory variational quantum eigensolver glossary deep dive entry on vqe and variational algorithms case study deloitte quantum ml fraud detection on amazon braket real world quantum machine learning applied to payments fraud data you can evaluate quantum ml claims critically and build the models yourself if a step is hard that s useful information it tells you exactly what to study next hard is not the same as wrong direction path 04 research track develop deep theoretical and practical understanding for research or engineering roles 3 6 months 60 min day prerequisites linear algebra complex numbers basic physics 6 steps research reset where you re headed you ll read a new quantum algorithm paper trace through the circuit construction identify what hardware constraints it assumes and hold an informed conversation with researchers working in the field you ll know what questions to ask mathematics complex numbers linear algebra brilliant both courses together form the essential mathematical foundation linear algebra course core programme quantum 101 professional certificate delft edx four course programme covering theory hardware and algorithms free to audit completing this programme puts you in rare company most people who study quantum computing never get this far algorithms quantum algorithms and error correction delft edx error correction and fault tolerance the path to practical qc hardware key hardware concepts study surface code fault tolerant qc and logical qubit entries in depth fault tolerant quantum computing logical qubit frameworks multiple frameworks try qiskit cirq pennylane and braket compare their models and use cases qiskit cirq pennylane braket case studies all case studies read every case study to understand real world applications across industries you can engage with the frontier of quantum computing if a step is hard that s useful information it tells you exactly what to study next hard is not the same as wrong direction questions frequently asked questions what order should i learn quantum computing in build intuition first concepts like superposition and entanglement no math then learn to write and run circuits in a framework such as qiskit then study the core algorithms grover s then a variational algorithm like vqe or qaoa then specialize in one area such as quantum machine learning error correction or hardware the four paths below follow exactly this order and each one builds on the previous which learning path is right for me start with the complete beginner if you are new and want to understand quantum computing without math choose first quantum code qiskit if you can already program in python and want to write real circuits choose quantum machine learning if you know the basics plus some classical ml choose the research track if you have the math and want graduate level depth when unsure start one path earlier than you think the early steps go quickly if you already know the material do i have to do the paths in order the paths are cumulative but you can enter at the level that matches your background each path assumes the skills built in the previous one so if you skip ahead and a step feels too hard drop back a path for the missing foundation within a path the steps are designed to be done in sequence how long does it take to complete a learning path the complete beginner takes about 2 to 3 weeks at around 20 minutes a day first quantum code takes about 4 to 6 weeks at around 30 minutes a day the machine learning and research paths take longer and assume more background these are guides not deadlines consistency matters more than speed are these learning paths free the paths themselves are free and they are built primarily around free resources free courses free tested tutorials on this site and free interactive tools like the circuit builder and bloch sphere a few optional steps point to paid courses where they are the best option but you can complete a full path without paying have questions see the faq for common questions about prerequisites and timelines browse the glossary for any unfamiliar terms all courses free tutorials faq on this page 01 path 01 the complete beginner 02 path 02 first quantum code qiskit 03 path 03 quantum machine learning 04 path 04 research track 05 questions people ask read next the prerequisites guide what each track actually requires all courses coursera edx udemy brilliant and more free tested tutorials qiskit pennylane cirq and braket get one quantum email a week new tutorials courses worth taking and what changed in qiskit cirq pennylane this week no spam unsubscribe anytime email address subscribe 112 courses 220 tutorials 241 glossary terms 26 framework references 34 case studies quantumcomputing courses com free tutorials curated courses framework references and tools for anyone learning quantum computing written and maintained by dr donovan who writes on quantum computing research hardware and industry at quantum zeitgeist learn all courses free tutorials learning paths compare frameworks algorithm guide case studies quantum news reference glossary framework docs hardware guide qubit types history timeline cheatsheets bloch sphere quantum programming careers careers guide salary guide 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