What’s Included?
High-Quality Video, E-book & Audiobook
Modules Quizzes
AI Mentor
Access for Tablet & Phone
Online Proctored Exam with One Free Retake
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.
Self Study Materials Included
Videos
Engaging visual content to enhance understanding and learning experience.
Podcasts
Insightful audio sessions featuring expert discussions and real-world cases.
Audiobooks
Listen and learn anytime with convenient audio-based knowledge sharing.
E-Books
Comprehensive digital guides offering in-depth knowledge and learning support.
Module Wise Quizzes
Interactive assessments to reinforce learning and test conceptual clarity.
Additional Resources
Supplementary references and list of tools to deepen knowledge and practical application.
Tools You’ll Master
IBM Qiskit
D-Wave Leap
Google TensorFlow Quantum (TFQ)
Amazon Braket
What You’ll Learn
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.
Course Modules
Module 1: Overview of Artificial Intelligence (AI) and Quantum Computing
- 1.1 Artificial Intelligence Refresher
- 1.2 Quantum Computing Refresher
Module 2: Quantum Computing Gates, Circuits, and Algorithms
- 2.1 Quantum Gates and their Representation
- 2.2 Multi Qubit Systems and Multi Qubit Gates
Module 3: Quantum Algorithms for AI
- 3.1 Core Quantum Algorithms
- 3.2 QFT and Variational Quantum Algorithms
Module 4: Quantum Machine Learning
- 4.1 Algorithms for Regression and Classification
- 4.2 Algorithms for Dimensionality and Clustering
Module 5: Quantum Deep Learning
- 5.1 Algorithms for Neural Networks – Part I
- 5.2 Algorithms for Neural Networks – Part II
Module 6: Ethical Considerations
- 6.1 Ethics for Artificial Intelligence
- 6.2 Ethics for Quantum Computing
Module 7: Trends and Outlook
- 7.1 Current Trends and Tools
- 7.2 Future Outlook and Investment
Module 8: Use Cases & Case Studies
- 8.1 Quantum Use Cases
- 8.2 QML Case Studies
Module 9: Workshop
- 9.1 Project – I: QSVM for Iris Dataset
- 9.2 Project – II: VQC/QNN on Iris Dataset
- 9.3 Bonus: IBM Quantum Computers
Optional Module: AI Agents for Quantum
- 1. What Are AI Agents
- 2. Key Capabilities of AI Agents in Quantum Computing
- 3. Applications and Trends for AI Agents in Quantum Computing
- 4. How Does an AI Agent Work
- 5. Core Characteristics of AI Agents
- 6. Types of AI Agents
Frequently Asked Questions
Yes, the course includes a hands-on workshop to reinforce theoretical concepts. Participants will engage in practical exercises to apply Quantum Computing principles to AI scenarios, enhancing their understanding through real-world applications.
This course is for professionals and enthusiasts with a basic understanding of AI, eager to explore AI and Quantum Computing technologies for innovative problem-solving.
Graduates of this course are equipped to contribute to industries undergoing rapid transformation, including healthcare, finance, cybersecurity, and logistics, where AI and Quantum Computing are driving innovative solutions and advancements.
By understanding both AI and Quantum Computing, participants gain insights into cutting-edge technologies that complement each other. This interdisciplinary knowledge equips them to innovate and solve complex problems more effectively across various industries.
The course emphasizes practical applications through hands-on workshops and real-world case studies. Participants gain experience in implementing Quantum Computing algorithms and techniques, enhancing their readiness to tackle industry challenges.