Quantum computing is often introduced either through high-level circuit abstractions or through heavy theoretical formalism. Developers frequently struggle to bridge the gap between textbook concepts, real algorithms, and hardware-aware execution. This tutorial provides a practical, hands-on introduction to quantum computing using QiliSDK, a Python framework designed to support both digital and analog workflows in a unified and modular way.

The session begins with the foundations: qubits, quantum states, gates, and measurement. Participants will implement basic circuits and understand how quantum programs are constructed, simulated, and executed. From there, we move to algorithmic patterns such as variational circuits and Hamiltonian-based workflows, demonstrating how quantum programs can be expressed in a clean and composable API.

The core value of the tutorial is depth without unnecessary abstraction. Attendees will not only build and simulate quantum circuits, but also explore time evolution, noise models, and backend selection. We will demonstrate how the same high-level program can target different execution layers, including simulators and hardware-oriented backends. For advanced participants, we will introduce pulse-level programming concepts, showing how quantum operations map to control-level primitives and how pulse-based experiments can be expressed in the SDK.

By the end of the tutorial, participants will have:

• A clear understanding of core quantum computing concepts.
• Hands-on experience building and simulating quantum circuits.
• Exposure to variational and Hamiltonian-based workflows.
• Insight into noise modeling and realistic execution.
• An understanding of how circuit-level abstractions connect to pulse-level control.

This tutorial is designed for developers and researchers who want a practical entry point into quantum computing without sacrificing architectural clarity. Prior experience with Python is required. No prior quantum computing knowledge is assumed, though basic linear algebra familiarity is helpful.

Quantum computing is often introduced either through high-level circuit abstractions or through heavy theoretical formalism. Developers frequently struggle to bridge the gap between textbook concepts, real algorithms, and hardware-aware execution. This tutorial provides a practical, hands-on introduction to quantum computing using QiliSDK, a Python framework designed to support both digital and analog workflows in a unified and modular way.

The session begins with the foundations: qubits, quantum states, gates, and measurement. Participants will implement basic circuits and understand how quantum programs are constructed, simulated, and executed. From there, we move to algorithmic patterns such as variational circuits and Hamiltonian-based workflows, demonstrating how quantum programs can be expressed in a clean and composable API.

The core value of the tutorial is depth without unnecessary abstraction. Attendees will not only build and simulate quantum circuits, but also explore time evolution, noise models, and backend selection. We will demonstrate how the same high-level program can target different execution layers, including simulators and hardware-oriented backends. For advanced participants, we will introduce pulse-level programming concepts, showing how quantum operations map to control-level primitives and how pulse-based experiments can be expressed in the SDK.

By the end of the tutorial, participants will have:

• A clear understanding of core quantum computing concepts.
• Hands-on experience building and simulating quantum circuits.
• Exposure to variational and Hamiltonian-based workflows.
• Insight into noise modeling and realistic execution.
• An understanding of how circuit-level abstractions connect to pulse-level control.

This tutorial is designed for developers and researchers who want a practical entry point into quantum computing without sacrificing architectural clarity. Prior experience with Python is required. No prior quantum computing knowledge is assumed, though basic linear algebra familiarity is helpful.