Quantum Computing Fundamentals

Introduction to Quantum Computing

• Overview of quantum computing and its evolution
• Differences between classical and quantum computing
• Key concepts: qubits, superposition, entanglement, and quantum interference
• Potential applications across industries

Quantum Mechanics for Computing

• Basic principles of quantum physics relevant to computing
• Quantum states, measurement, and probabilities
• Quantum gates and circuits
• Representation of information in quantum systems

Quantum Algorithms and Programming

• Introduction to quantum algorithms (e.g., Grover’s, Shor’s algorithms)
• Quantum programming languages and frameworks (Qiskit, Cirq)
• Writing, simulating, and testing quantum programs
• Problem-solving with quantum approaches

Quantum Hardware and Platforms

• Types of quantum computers: superconducting, trapped ion, photonic, and topological
• Quantum processors and qubit architectures
• Noise, decoherence, and error correction
• Accessing cloud-based quantum computing platforms

Applications and Case Studies

• Cryptography, optimization, and machine learning applications
• Quantum simulation and material science
• Industry use cases in finance, healthcare, and logistics
• Lessons from research and pilot projects

1ST BATCH: Tuesday, April 14, 2026 — Friday, April 17, 2026.

2ND BATCH: Tuesday, August 4, 2026 — Friday, August 7, 2026.

3RD BATCH: Tuesday, December 1, 2026 — Friday, December 4, 2026.

The training methodology integrates lectures, interactive discussions, collaborative group exercises, and
illustrative examples. Participants will acquire a blend of theoretical insights and hands-on practical
experience, emphasizing the application of learned techniques. This approach ensures that attendees return
to their professional environments equipped with both the competence and self-assurance to effectively
implement the acquired skills in their responsibilities.