AI+ Quantum™

Certificate Code: AT-410

Passing Score: 70% (35/50)

Exam Info: 50 MCQs, 90 Minutes

Tagline: Harness Quantum Power with AI

Course Overview:

Prerequisites:

Tools Used:

• IBM Qiskit
• D-Wave Leap
• Google TensorFlow Quantum (TFQ)
• Amazon Braket

Modules:

• Module 1: Overview of Artificial Intelligence (AI) and Quantum Computing
  1. 1.1 Artificial Intelligence Refresher
  2. 1.2 Quantum Computing Refresher
• Module 2: Quantum Computing Gates, Circuits, and Algorithms
  1. 2.1 Quantum Gates and their Representation
  2. 2.2 Multi Qubit Systems and Multi Qubit Gates
• Module 3: Quantum Algorithms for AI
  1. 3.1 Core Quantum Algorithms
  2. 3.2 QFT and Variational Quantum Algorithms
• Module 4: Quantum Machine Learning
  1. 4.1 Algorithms for Regression and Classification
  2. 4.2 Algorithms for Dimensionality and Clustering
• Module 5: Quantum Deep Learning
  1. 5.1 Algorithms for Neural Networks – Part I
  2. 5.2 Algorithms for Neural Networks – Part II
• Module 6: Ethical Considerations
  1. 6.1 Ethics for Artificial Intelligence
  2. 6.2 Ethics for Quantum Computing
• Module 7: Trends and Outlook
  1. 7.1 Current Trends and Tools
  2. 7.2 Future Outlook and Investment
• Module 8: Use Cases & Case Studies
  1. 8.1 Quantum Use Cases
  2. 8.2 QML Case Studies
• Module 9: Workshop
  1. 9.1 Project – I: QSVM for Iris Dataset
  2. 9.2 Project – II: VQC/QNN on Iris Dataset
  3. 9.3 Bonus: IBM Quantum Computers
• Optional Module: AI Agents for Quantum
  1. 1. What Are AI Agents
  2. 2. Key Capabilities of AI Agents in Quantum Computing
  3. 3. Applications and Trends for AI Agents in Quantum Computing
  4. 4. How Does an AI Agent Work
  5. 5. Core Characteristics of AI Agents
  6. 6. Types of AI Agents

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.

Career Opportunities:

• Quantum Computing AI Expert — Develop groundbreaking solutions at the intersection of AI and quantum computing.​
• Quantum-AI Integration Specialist — Specialize in merging AI and quantum computing technologies to maximize their combined potential.​
• AI Quantum Systems Analyst — Analyze and optimize systems that integrate AI and quantum computing for enhanced performance.​
• AI Quantum Technology Innovator — Lead innovations by applying quantum mechanics principles to advance AI applications.

Exam Blueprint:

• Overview of Artificial Intelligence (AI) and Quantum Computing – 5% 
• Quantum Computing Gates, Circuits, and Algorithms – 11% 
• Quantum Algorithms for AI – 12% 
• Quantum Machine Learning – 12% 
• Quantum Deep Learning – 12% 
• Ethical Considerations – 12% 
• Trends and Outlook – 12% 
• Use Cases & Case Studies – 12% 
• Workshop – 12%

Self-Study Materials:

• 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.
• Labs: Interactive lab sessions to apply concepts and strengthen technical skills.
• 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.

Frequently Asked Questions:

• Q: Are there hands-on components in the course?
  A: 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.
• Q: Who should enroll in this AI+ Quantum™ course?
  A: 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.
• Q: What career opportunities does this course open up?
  A: 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.
• Q: What are the benefits of learning about AI and Quantum Computing together?
  A: 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.
• Q: How practical are the skills learned in this course for real-world applications?
  A: 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.

Certificate Features:

• High-Quality Video, E-book & Audiobook
• Modules Quizzes
• AI Mentor
• Access for Tablet & Phone
• Online Proctored Exam with One Free Retake
• LABs Practices