Program Fee: ₹500/- only
Payment: via QR Code (in form) or UPI/VPA: annantgyan@icici
Resource Person: Prof. (Dr.) Debabrata Datta [Retired Nuclear Scientist, Bhabha Atomic Research Centre], Joint Director- Research & Development & Professor, Department of InformationTechnology, Heritage Institute of Technology, Kolkata, West Bengal, India
Session Time: 6:30 pm to 7:45 pm & Q&A: 7:45 pm to 8:00 pm
13.04.2026 (Monday): Fundamentals of quantum computing: Qubits, Superposition, Entanglement, Quantum Gates and quantum circuits
14.04.2026 (Tuesday): Introduction to Quantum Machine Learning (QML): Theoretical concepts, Toy QML problem introduces feature vector, data encoding, some general property of Hadamard operation, Measurement & output interpretation, Noisy algorithm (NISQ), Quantum Logistic Regression, QML Applications: Solving Burger’s Equation & Classification of Non-Communicable Diseases (NCDs)
15.04.2026 (Wednesday): Variational and Hybrid Quantum Models: Hybrid models, Variational Quantum Algorithms (VQA), Variational Quantum Eigensolver (VQE), Variational Quantum Circuits (VQC), Dual formalism in QML,Least-Squares SVM, Quantum Support Vector Machine (qSVM), Quantum Neural Networks (QNN): Theory and algorithm, Applications Heart disease prediction & Lung cancer detection
16.04.2026 (Thursday): Quantum Deep Learning and Physics-Inspired Models: Theoretical background, Data Handling through Quantum-Enhanced Machine Learning and the Study of Quantum Systems. Quantum physics inspired neural networks and its applications to damped oscillator and ecological systems
17.04.2026 (Friday): Quantum Unsupervised Learning: Quantum clustering, Quantum Thermography, Quantum Simulated Annealing, Urban traffic optimization using QML
18.04.2026(Saturday): Advanced Quantum Deep Learning & Future Directions: Quantum Convolutional Neural Networks (QCNN), Quantum Recurrent Networks, Time Series Analysis using Quantum ARIMA, Advantages and limitations of QML, Open research challenges in QML
