NIT Warangal | Quantum Machine Learning (QML 2026) FDP | Apply Online
Overview
About the Programme
Electronics & ICT Academy, National Institute of Technology (NIT) Warangal, in association with National Institute of Technology (NIT) Raipur, is organizing a Faculty Development Programme (FDP) on Quantum Machine Learning (QML 2026).
The programme aims to bridge the gap between Quantum Computing and Artificial Intelligence by introducing participants to quantum algorithms, quantum data encoding, variational quantum circuits, quantum machine learning models, and practical implementation using Qiskit. The FDP is sponsored by the Ministry of Electronics and Information Technology (MeitY), Government of India.
Programme Details
| Particulars | Details |
|---|---|
| Programme Name | Quantum Machine Learning (QML 2026) |
| Programme Type | Faculty Development Programme (FDP) |
| Mode | Online |
| Duration | 06 July 2026 to 11 July 2026 |
| Organized By | Electronics & ICT Academy, NIT Warangal |
| Associated Institute | NIT Raipur |
| Sponsor | Ministry of Electronics and Information Technology (MeitY), Government of India |
| Certificate | E-Certificate upon Successful Completion |
Major Topics Covered
Quantum Computing Fundamentals
- Quantum Bits (Qubits)
- Quantum Gates and Operations
- Quantum Circuit Design
Quantum Algorithms
- Quantum Amplitude Amplification (QAA)
- Quantum Phase Estimation (QPE)
- Harrow-Hassidim-Lloyd (HHL) Algorithm
Quantum Machine Learning
- Quantum Data Encoding
- Quantum Feature Maps
- Quantum Kernel Methods
- Variational Quantum Circuits (VQC)
- Variational Quantum Eigensolver (VQE)
Advanced Learning Techniques
- Quantum Supervised Learning
- Quantum Unsupervised Learning
- Classification and Regression Models
- Clustering Using Quantum Methods
Emerging Technologies
- Quantum Deep Learning (QDL)
- Quantum Artificial Intelligence (QAI)
- NISQ-Era Quantum Computing
- Hybrid Quantum-Classical Learning Architectures
Hands-on Sessions
- Qiskit Programming
- Real-Time Quantum Computing Applications
- Practical Implementation of QML Models
Who Can Apply?
Applications are invited from:
- Faculty Members
- Research Scholars
- Industry Professionals
- Academicians
- AI and Machine Learning Enthusiasts
- Quantum Computing Researchers
Registration Fee
| Category | Registration Fee |
| Faculty Members / Research Scholars | ₹500 |
| Industry Participants | ₹2,250 |
Important Dates
| Event | Date |
| Last Date to Apply | 03 July 2026 |
| Selection Intimation | 04 July 2026 |
| Programme Start Date | 06 July 2026 |
| Programme End Date | 11 July 2026 |
Selection will be made on a first-come-first-served basis for a maximum of 40 participants.
Benefits of Participation
- Learn Quantum Machine Learning from experts.
- Gain hands-on experience using Qiskit.
- Explore Quantum AI and Quantum Deep Learning.
- Understand practical applications of Quantum Computing.
- Network with researchers and industry experts.
- Receive an FDP Completion Certificate.
Registration Link
Official Notification
https://eict.nitw.ac.in/files/QML_FDP_Brochure_12.06.2026.pdf
Streams
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