Author: Ricard Santiago Raigada García Status: Active
Citation: To cite this course you can use the following DOI:
Mastering Qiskit v2.0 is a complete learning series designed to take you from the very basics of quantum circuits to running optimized workloads on IBM Quantum hardware. The course is based on the latest Qiskit v2.0 SDK and IBM Quantum Platform updates.
This repository contains:
- All course materials (notebooks, code, and visual assets)
- The official episode roadmap
- Example circuits and visualizations
- Ready-to-run Qiskit v2.0 code
By the end of this series, you will be able to:
- Set up your environment and connect to IBM Quantum hardware
- Prepare and manipulate quantum states
- Use the Qiskit SDK effectively for building and optimizing circuits
- Apply measurement strategies and visualize results
- Implement advanced circuit techniques
- Work with operators, observables, and execution primitives
- Run jobs on real hardware and apply error mitigation
Mastering-Qiskit-v2.0/
│
├── fundamentals/
│ ├── ep1-python-env-setup/
│ ├── ep2-connect-ibm-cloud/
│ ├── ep3-preparing-states-one-qubit/
│ ├── ep4-preparing-superposition/
│ └── ep5-preparing-multiqubit-bell/
│
├── qiskit-foundations/
│ ├── ep6-intro-qiskit-stack/
│ ├── ep7-intro-qiskit-patterns/
│ ├── ep8-using-circuit-library/
│ └── ep9-constructing-circuits/
│
├── measurement-and-gates/
│ ├── ep10-measuring-qubits/
│ └── ep11-fractional-gates/
│
├── advanced-circuit-techniques/
│ ├── ep12-classical-feedforward/
│ ├── ep13-bit-ordering/
│ ├── ep14-timing-and-stretch/
│ ├── ep15-resynthesizing-unitaries/
│ └── ep16-saving-circuits-qpy/
│
├── operators-and-execution/
│ ├── ep17-operator-classes/
│ ├── ep18-measuring-pauli-basis/
│ ├── ep19-operator-class-in-depth/
│ ├── ep20-hardware-aware-optimization/
│ ├── ep21-running-on-hardware/
│ └── ep22-analyzing-results-error-mitigation/
│
├── qml/ # (Future topic)
├── vqe/ # (Future topic)
├── assets/ # Logos, banners, roadmap
├── README.md
└── requirements.txt
| # | Episode Title | Status | Date |
|---|---|---|---|
| 1 | Python Environment Setup | Released | 08/07/2025 |
| 2 | Connect to IBM Quantum with IBM Cloud | Released | 08/08/2025 |
| 3 | Preparing Quantum States – One Qubit | Released | 08/09/2025 |
| 4 | Preparing Quantum States – Superposition | Released | 08/10/2025 |
| 5 | Preparing Multi-Qubit States – Bell States and Ordering | Released | 08/11/2025 |
| 6 | Introduction to the Qiskit Stack | Soon | 08/13/2025 |
| 7 | Introduction to Qiskit Patterns | Soon | 08/15/2025 |
| 8 | Using the Qiskit Circuit Library | Soon | 08/18/2025 |
| 9 | Constructing Circuits Programmatically | Soon | 08/20/2025 |
| 10 | Measuring Qubits | Soon | 08/22/2025 |
| 11 | Fractional Gates | Soon | 08/25/2025 |
| 12 | Implementing Classical Feedforward Logic and Conditional Execution | Soon | 08/27/2025 |
| 13 | Understanding Qubit and Bit Ordering in Qiskit | Soon | 08/29/2025 |
| 14 | Controlling Timing and Stretch for Quantum Scheduling | Soon | 09/01/2025 |
| 15 | Re-Synthesizing Unitary Operators for Circuit Optimization | Soon | 09/03/2025 |
| 16 | Saving and Loading Circuits with QPY Serialization | Soon | 09/05/2025 |
| 17 | Exploring Operator Classes and Their Applications | Soon | 09/08/2025 |
| 18 | Measuring Observables in the Pauli Basis | Soon | 09/10/2025 |
| 19 | Working with the Operator Class in Depth | Soon | 09/12/2025 |
| 20 | Hardware-Aware Circuit Optimization with the Qiskit Transpiler | Soon | 09/15/2025 |
| 21 | Running Quantum Jobs on IBM Hardware with Qiskit Runtime | Soon | 09/17/2025 |
| 22 | Analyzing Results and Applying Error Mitigation | Soon | 09/19/2025 |
After Episode 22, the series will continue with more advanced topics:
- Quantum Machine Learning (QML)
- Variational Quantum Eigensolver (VQE)
- Quantum algorithms (Grover, Shor, QAOA, VQE)
- Error correction and mitigation techniques
This course follows a structured educational program that outlines the complete Phase 1 learning plan, including:
- A detailed description of the course scope and structure.
- Specific learning objectives for each phase.
- Competencies and skills to be acquired.
- Teaching methodology and delivery mode.
- Assessment and self-evaluation criteria.
You can consult the full educational program here:
📄 View Educational Program (PDF)
Episodes are published daily on:
- LinkedIn: Ricard Santiago Raigada García
- GitHub: This repository