Programme Parameters
Foundation
3 Weeks (30 Hrs)
Online (e-LMS)
• No prior experience required — basic computer literacy is sufficient.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Quantum Computing Basics gives you a rigorous but accessible foundation in how quantum computers work and why they matter. You will build intuition for qubits, superposition, entanglement and measurement, then express them concretely as quantum gates and circuits. From there you implement the landmark ideas — the Deutsch–Jozsa, Grover and quantum-teleportation protocols — and run them on a simulator using a modern SDK such as Qiskit. The course keeps the mathematics grounded and visual, so you leave genuinely able to read, write and reason about quantum circuits. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
Quantum Computing Basics introduces qubits, superposition, entanglement and core quantum algorithms, with hands-on circuits you build and run on a quantum SDK.
📋 Course Objectives
1. Explain qubits, superposition, entanglement and measurement.
2. Construct quantum circuits from fundamental gates.
3. Implement and run Deutsch–Jozsa, Grover and teleportation protocols.
4. Use a quantum SDK such as Qiskit on a simulator.
5. Reason about where quantum advantage is realistic.
👥 Who Should Enroll?
• Students and professionals curious about quantum computing
• Software engineers exploring quantum SDKs
• Physics and CS students wanting a hands-on start
• Researchers surveying quantum methods for their field
🚀 Key Learning Outcomes
• A working set of quantum circuits you have built and run.
• Clear intuition for the core principles of quantum computing.
• A foundation for further study in quantum algorithms.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
AI Fundamentals, Mathematics, and Quantum Computing Foundations
Analyze the principles of quantum mechanics and their application to quantum computing • Develop a deep understanding of linear algebra and its role in quantum computing • Evaluate the fundamentals of artificial intelligence and machine learning in the context of quantum computing
Data Engineering, Preprocessing, and Feature Pipelines
Design and implement data pipelines for quantum computing applications • Configure data preprocessing techniques for quantum computing datasets • Optimize data engineering workflows for efficient quantum computing
Model Architecture, Algorithm Design, and Quantum Computing Methods
Implement quantum algorithms such as Shor's and Grover's algorithms • Develop and evaluate quantum machine learning models using Qiskit and Cirq • Analyze the trade-offs between different quantum computing models and algorithms
Training, Hyperparameter Optimization, and Evaluation
Train and evaluate quantum machine learning models using various metrics • Optimize hyperparameters for quantum machine learning models using techniques such as grid search and Bayesian optimization • Develop strategies for regularizing and fine-tuning quantum machine learning models
Deployment, MLOps, and Production Workflows
Deploy quantum machine learning models in production environments using cloud services such as IBM Quantum and Google Cloud • Develop and implement MLOps workflows for quantum machine learning models • Configure and manage quantum computing infrastructure for production workloads
Ethics, Bias Mitigation, and Responsible AI Practices
Evaluate the ethical implications of quantum computing and AI applications • Develop strategies for mitigating bias in quantum machine learning models • Analyze the role of responsible AI practices in quantum computing and AI development
Industry Integration, Business Applications, and Case Studies
Analyze the applications of quantum computing in various industries such as finance and healthcare • Develop business cases for quantum computing and AI adoption in organizations • Evaluate the potential return on investment for quantum computing and AI initiatives
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | Qiskit |
| Covered Tool / Platform | Cirq |
| Covered Tool / Platform | TensorFlow |
Frequently Asked Questions
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