QuLearnLabs Program – AI-assisted Software Engineering for Quantum Computing [AI-SEQ]

Purpose and aims:
The AI-SEQ (AI-assisted software engineering for Quantum Computing and Post-Quantum Cryptography) course introduces learners to the fundamentals of quantum computing and post-quantum cryptography (PQC), with a strong emphasis on practical software engineering. Delivered through a blended learning format, the course empowers participants to explore quantum computing using Qiskit, the open-source quantum computing Python libraries.

A key innovation in the course is the integration of Q, an open-source AI coding assistant developed in-house to support learners in writing, debugging, and optimizing code but also in accelerating the learning by enabling conversations right inside the Development Environment where software engineers are coding and building the applications. With this hands-on and AI-enhanced approach, participants will gain the tools and knowledge needed to contribute to cutting-edge deep tech fields such as quantum software development, cryptography, and secure digital infrastructure.

Target audience
This course is ideal for:

• Software engineers, cybersecurity professionals, and STEM students or graduates
• Early-career technologists aiming to enter the deep tech workforce
• Researchers and developers exploring quantum algorithms or cryptographic systems
• Innovation-minded professionals looking to understand the intersection of AI, quantum computing, and cybersecurity
• No prior experience in quantum computing is required. The course includes support for learners with basic to intermediate Python skills.

Key knowledge and skills developed:

• Understand core principles of quantum mechanics relevant to computing
• Develop and simulate quantum circuits using Qiskit
• Gain insight into post-quantum cryptography and quantum-safe protocols
• Use Q, the AI coding assistant, to improve code efficiency and accelerate learning
• Explore classical-quantum hybrid approaches and real-world use cases
• Build a capstone project demonstrating quantum or PQC concepts in practice

Course structure and Deep Tech relevance
The course is structured into 8 main modules:

• Fundamentals of Software Engineering
• AI-enhanced development and learning with Q – assistant integrated from Github marketplace
• Foundations of Quantum Computing & Python Programming
• Quantum Circuit Development with Qiskit
• Post-Quantum Cryptography and Secure Coding
• Capstone Project
  Deep tech elements include: real-time circuit simulation, quantum-safe cryptographic coding, hybrid algorithm design, and AI-assisted software engineering—all of which are increasingly critical to the future of secure digital infrastructure.

Teaching and assessment
The course is delivered fully online and includes:

• Pre-recorded video lectures and tutorials
• Interactive GitHub-based exercises
• Weekly mentoring/Q&A sessions
• Hands-on practice with Q, the AI coding assistant

Assessment is based on:

• Practical coding exercises
• Short quizzes and code reviews
• A final capstone project showcasing quantum or PQC applications

Practical Information

Duration: 10–12 weeks (4–6 hours/week)
Format: Fully online, self-paced with optional live mentoring
Tools: Visual Studio Code, Qiskit, Python, GitHub, and Q (AI assistant)
Fee: Free or subsidized (see course details)
Outcome: Certificate of completion