AI+ Quantum™
This comprehensive course provides a deep dive into the intersection of Artificial Intelligence (AI) and Quantum Computing, exploring fundamental concepts, advanced techniques, and ethical considerations. Participants will gain insights into Quantum Computing Gates, Circuits, and Algorithms, with a particular focus on their application in AI domains. Through discussions on Quantum Machine Learning and Quantum Deep Learning, attendees will discover how these technologies are reshaping traditional AI methodologies. Ethical implications are carefully examined throughout, alongside an exploration of current trends and future outlooks. Real-world case studies offer practical insights, while a hands-on workshop solidifies understanding, making this course essential for professionals and enthusiasts alike seeking to navigate and contribute to the transformative landscape of AI and Quantum Computing.
Fee structure:
Self-Learning Mode:
Each certificate: INR: 19,999
(online videos access + practice tests) – 4 weeks
On-line Instructure led training:
Certificate: INR: 29,999
(online videos access + practice tests) – 4 weeks
Objectives
Quantum Algorithm Development
Learners will acquire skills in developing quantum algorithms specifically designed for AI applications. This involves creating and implementing quantum circuits and understanding how quantum gates operate within these algorithms.
Quantum Machine Learning and Deep Learning
Learners will learn how to apply quantum computing principles to machine learning and deep learning models. This includes the development and optimization of quantum-enhanced models that leverage the unique advantages of quantum computing.
Designing Quantum Circuits
Learners will gain practical skills in designing and constructing quantum circuits, essential for implementing quantum algorithms and solving complex computational problems.
Optimization of Quantum-AI Models
Learners will learn techniques to optimize quantum-AI models for better performance, including fine-tuning parameters and reducing computational complexity.
Prerequisites
- A foundational knowledge of AI concepts, no technical skills are required.
- Willingness to exploring unconventional approaches to problem-solving within the context of AI and Quantum.
- Openness to engage critically with ethical dilemmas and considerations related to AI technology in quantum practices.
