I B M C E R T I F I C A T I O N
C0010300 IBM Certified Associate Developer – Quantum Computation using Qiskit v0.2X Practice Exam
Exam Number: 4367 | Last updated April 17, 2026 | 295+ questions across 5 vendor-aligned objectives
Entry-level quantum developers learning Qiskit v0.2X target this C0010300 credential. The associate exam predates the primitive-based workflow introduced in Qiskit v1 and v2, so it focuses on the original Terra-based circuit API, backend selection, and classic algorithm implementations like VQE and QAOA. Candidates should understand quantum states, circuit construction, and the execution flow used before Qiskit Runtime primitives became the default.
Nudging through 26% of the exam, Circuit Construction covers QuantumCircuit, gate composition, measurement, and circuit parameters. At 22%, Operators and States covers statevectors, Pauli operators, and fidelity calculations. A further 20% targets Backend and Execution, covering the IBMQ provider, backend filtering, job submission, and result retrieval.
Screwing in the remaining objectives, Algorithms and Optimization accounts for 18% and spans VQE, QAOA, variational forms, and classical optimizers. Transpilation and Noise represents 14% and spans transpiler passes, noise models, and basic error mitigation. Because this exam covers an older Qiskit API, avoid answering from memory of newer primitive-based patterns; several answers that would be correct today are wrong against the v0.2X surface.
Every answer links to the source. Each explanation below includes a hyperlink to the exact IBM documentation page the question was derived from. PowerKram is the only practice platform with source-verified explanations. Learn about our methodology →
719
practice exam users
94%
satisfied users
91%
passed the exam
4.6/5
quality rating
Test your C0010300 qiskit v0 associate knowledge
10 of 295+ questions
Question #1 - Circuit Construction
A Qiskit v0.2X developer at Clearfield Research needs to build a two-qubit Bell state.
Which v0.2X QuantumCircuit sequence matches the intended circuit?
A) Create a QuantumCircuit on two qubits, apply H to qubit 0, then CX(0,1), and measure both qubits into a classical register
B) Apply CX(0,1) before H on qubit 0
C) Use only X gates and skip any Hadamard
D) Skip measurement entirely and hope the counts appear
Show solution
Correct answers: A – Explanation:
H followed by CX is the Qiskit v0.2X Bell-state circuit reference. Swapping the order, using only X, and omitting measurement all miss the construction. Source: Check Source
Question #2 - Circuit Construction
A Qiskit v0.2X circuit at Oakridge Labs uses parameters that will vary across jobs.
Which v0.2X technique fits?
A) Avoid parameterization because it is unsupported
B) Rebuild the circuit from scratch for every parameter value
C) Hard-code values and recompile
D) Use Parameter objects in the QuantumCircuit and substitute values with bind_parameters (or by binding on the job submission) rather than rebuilding the circuit each time
Show solution
Correct answers: D – Explanation:
Parameter objects with bind_parameters is the v0.2X parameterization reference. Rebuilds, hard-coding, and unsupported claims all miss the API. Source: Check Source
Question #3 - Circuit Construction
A v0.2X developer at Silvercrest Physics needs to initialize a specific statevector on the input qubits.
Which Qiskit v0.2X approach initializes a specific statevector on the input qubits?
A) Skip initialization and hope the amplitude shows up
B) Assume the default |0…0> state always equals the desired state
C) Use QuantumCircuit.initialize() with the desired statevector at the start of the circuit, recognizing that Qiskit will generate the corresponding preparation gates
D) Initialize only one qubit and ignore the others
Show solution
Correct answers: C – Explanation:
QuantumCircuit.initialize() is the v0.2X reference for specific statevector initialization. Assumptions, skipping, and single-qubit initialization all fail correctness. Source: Check Source
Question #4 - Operators and States
A v0.2X developer at Penford Labs needs to compute ⟨ψ|H|ψ⟩ where H is a Pauli-string Hamiltonian.
Which Qiskit v0.2X approach computes the expectation value of a Pauli-string Hamiltonian?
A) Compute expectation values by hand without tools
B) Use qiskit.opflow (or equivalent PauliSumOp) to define H as a weighted sum of Pauli strings, and evaluate the expectation against the state prepared by the circuit
C) Approximate H as identity and report expectation 1.0
D) Avoid the computation entirely
Show solution
Correct answers: B – Explanation:
PauliSumOp/opflow is the v0.2X expectation-value reference. Hand calculation at scale, identity approximations, and avoidance all fail the task. Source: Check Source
Question #5 - Operators and States
A v0.2X developer at Harnwick Quantum compares two state preparations’ outputs.
Which v0.2X concept computes their agreement?
A) Subtract random bits and call it a comparison
B) Compute the state fidelity between the two Statevectors (or DensityMatrices) using the provided fidelity utilities
C) Ignore fidelity and rely on intuition
D) Compute inner products on unrelated vectors
Show solution
Correct answers: B – Explanation:
Statevector/DensityMatrix fidelity is the v0.2X state-comparison reference. Random subtraction, intuition, and unrelated inner products all fail the task. Source: Check Source
Question #6 - Backend and Execution
A v0.2X developer at Thornwell Physics needs to run a circuit on real IBM Quantum hardware.
Which v0.2X execution approach fits?
A) Bypass the provider and hope the hardware accepts raw circuits
B) Use the IBMQ provider to select a backend, transpile the circuit for it, submit a job via backend.run() (or execute), and retrieve the result with job.result()
C) Only run circuits on the statevector simulator
D) Skip transpilation and submit the logical circuit directly
Show solution
Correct answers: B – Explanation:
IBMQ provider plus transpile plus submit plus retrieve is the v0.2X execution reference. Provider bypass, simulator-only runs, and un-transpiled submissions all fail the flow. Source: Check Source
Question #7 - Backend and Execution
A v0.2X developer at Ashmere Labs needs to pick the least-busy backend with at least five qubits.
Which v0.2X backend-filter approach fits?
A) Avoid filters and select backends randomly
B) Hard-code a backend name that may be retired
C) Submit to every backend and take the first to return
D) Use the IBMQ provider’s backends() filter on number of qubits and least_busy() to select an appropriate backend dynamically at job-submission time
Show solution
Correct answers: D – Explanation:
Filter-based backend selection with least_busy is the v0.2X reference. Hard-coded names, fire-everywhere, and random selection all fail backend management. Source: Check Source
Question #8 - Algorithms and Optimization
A developer at Orkby Analytics implements VQE on v0.2X to find a ground-state energy.
Which v0.2X design fits?
A) Skip the classical optimizer and hope the parameters converge by luck
B) Run VQE with no ansatz
C) Choose a variational form (ansatz), select a classical optimizer (SPSA, L_BFGS_B, or similar), define the Hamiltonian, and run VQE using the v0.2X algorithms module
D) Use VQE only for unrelated problems
Show solution
Correct answers: C – Explanation:
Ansatz classical optimizer Hamiltonian VQE runner is the v0.2X VQE reference. No-ansatz, no-optimizer, and off-task runs all fail VQE. Source: Check Source
Question #9 - Algorithms and Optimization
A v0.2X developer at Bankworth Labs runs QAOA for a combinatorial optimization.
Which v0.2X pattern fits?
A) Define the cost Hamiltonian for the problem, choose QAOA p-depth, pair it with a classical optimizer, and run QAOA from the v0.2X algorithms module
B) Skip the cost Hamiltonian and hope QAOA finds the answer
C) Use only p=0 and expect the ground state to appear
D) Run QAOA on an unrelated problem
Show solution
Correct answers: A – Explanation:
Cost Hamiltonian p-depth classical optimizer is the v0.2X QAOA reference. No Hamiltonian, p=0-only, and off-task runs all fail QAOA. Source: Check Source
Question #10 - Transpilation and Noise
A v0.2X developer at Cresthollow Physics needs to reduce circuit depth to improve fidelity on a noisy backend.
Which v0.2X transpiler approach fits?
A) Run transpile with an appropriate optimization_level and pass it the backend so layout, routing, and gate-cancellation passes target the hardware’s coupling map
B) Skip transpilation and submit the circuit as-is
C) Force optimization_level=0 to disable all optimization
D) Hard-code gate decompositions that ignore the backend
Show solution
Correct answers: A – Explanation:
transpile(optimization_level, backend=) is the v0.2X transpile reference. Skipping, level=0, and backend-agnostic decompositions all miss noise-aware transpilation. Source: Check Source
Get 295+ more questions with source-linked explanations
Every answer traces to the exact IBM documentation page — so you learn from the source, not just memorize answers.
Exam mode & learn mode · Score by objective · Updated April 17, 2026
Learn more...
What the C0010300 qiskit v0 associate exam measures
- Construct and measure QuantumCircuit, gate composition, measurement, and parameters to express quantum algorithms in the Qiskit v0.2X programming model cleanly
- Represent and compute statevectors, Pauli operators, and fidelity calculations to reason about quantum states before submitting circuits to hardware
- Select and submit IBMQ provider, backend filtering, job submission, and result retrieval to run experiments on real quantum hardware efficiently given limited shot budgets
- Optimize and iterate VQE, QAOA, variational forms, and classical optimizers to apply variational algorithms to optimization and chemistry problems
- Transpile and mitigate transpiler passes, noise models, and basic error mitigation to extract usable signal from noisy near-term quantum hardware
How to prepare for this exam
- Review the official exam guide to understand every objective and domain weight before you begin studying
- Work through the relevant IBM Training learning path — ibm certified associate developer quantum computation using qiskit v0 2x C0010300 — to cover vendor-authored material end-to-end
- Get hands-on inside IBM TechZone or a comparable sandbox so you can practice the console tasks, CLI commands, and APIs the exam expects
- Tackle a real-world project at your workplace, a volunteer role, or an open-source repository where the technology under test is actually in use
- Drill one exam objective at a time, starting with the highest-weighted domain and only moving on once you can teach it to someone else
- Study by objective in PowerKram learn mode, where every explanation links back to authoritative IBM documentation
- Switch to PowerKram exam mode to rehearse under timed conditions and confirm you consistently score above the pass mark
Career paths and salary outlook
Quantum developers pioneer a still-rare skill set, positioning themselves for leadership roles as the field grows:
- Quantum Computing Associate — $100,000–$140,000 per year, supporting quantum algorithm development on Qiskit (Glassdoor salary data)
- Research Software Engineer — $115,000–$155,000 per year, building quantum and hybrid-classical tooling (Indeed salary data)
- Applied Quantum Researcher — $120,000–$170,000 per year, exploring quantum applications in industry settings (Glassdoor salary data)
Official resources
Work through the official IBM Training learning path for this certification, which bundles videos, labs, and skill tasks aligned to every objective. The official exam page lists the full objective breakdown, prerequisite knowledge, and scheduling details.