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Roadmap
Ricard Santiago Raigada García edited this page Aug 11, 2025
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Below is the roadmap for the first phase of Mastering Qiskit v2.0, running from August 07, 2025 to September 19, 2025.
| # | 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 Phase 1, the course will expand into topics such as Quantum Machine Learning (QML) and Variational Quantum Eigensolvers (VQE).
Keep an eye on the roadmap for updates.
© 2025 Ricard Santiago Raigada García • Licensed under Apache 2.0
This course is independent and not affiliated with IBM.
It uses the open-source Qiskit SDK for educational purposes.