Why This Certification Matters

  • Demand for AI and Quantum Technology Experts: Organizations are seeking certified experts who can integrate AI with quantum technologies to optimize data processing and accelerate problem-solving.

  • Mitigating Risks in AI and Quantum Integration: Mismanagement of quantum computing systems and AI integration can result in inefficiencies and inaccurate results in critical applications.

  • Developing Reliable Quantum Strategies with AI: Certified professionals play a key role in developing quantum strategies that ensure performance, reliability, and alignment with industry standards.

  • Gaining a Competitive Edge: As quantum computing and AI continue to revolutionize industries, this certification provides professionals with a competitive edge, preparing them for advanced roles.

At a Glance: Course + Exam Overview

Program Name
AI+ Quantum Practitioner™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Prerequisites
Basic understanding of AI concepts, Problem-solving mindset in AI and Quantum, Openness to ethical considerations in AI and quantum practices.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience

Who Should Enroll?

  • Quantum Computing Engineers: Enhance quantum system design and performance using AI for optimization and control.

  • Physics Engineers: Apply AI techniques to improve quantum simulations and computational models.

  • AI Specialists: Leverage AI and quantum algorithms to create intelligent solutions for complex problems.

  • IT Specialists & System Integrators: Integrate AI-driven quantum computing systems to optimize infrastructure and solve large-scale challenges.

  • Students & New Graduates: Gain foundational skills in AI and quantum computing to excel in the rapidly advancing quantum technology field.

Skills You'll Gain

Quantum Circuit DesignQuantum Simulation TechniquesQuantum CryptographyQuantum Optimization MethodsQuantum Information Theory

What You'll Learn

  • AI + Quantum Integration: Explore Quantum Gates, Circuits, and AI applications
  • Advanced Learnings: Includes Quantum Deep Learning and transformative AI methodologies
  • Industry-Oriented: Real-world case studies and trend analysis
  • Ethical Focus: Learn implications of quantum AI responsibly and efficiently

  • 1.1 Artificial Intelligence Refresher
  • 1.2 Quantum Computing Refresher

  • 2.1 Quantum Gates and their Representation
  • 2.2 Multi Qubit Systems and Multi Qubit Gates

  • 3.1 Core Quantum Algorithms
  • 3.2 QFT and Variational Quantum Algorithms

  • 4.1 Algorithms for Regression and Classification
  • 4.2 Algorithms for Dimensionality and Clustering

  • 5.1 Algorithms for Neural Networks – Part I
  • 5.2 Algorithms for Neural Networks – Part II

  • 6.1 Ethics for Artificial Intelligence
  • 6.2 Ethics for Quantum Computing

  • 7.1 Current Trends and Tools
  • 7.2 Future Outlook and Investment

  • 8.1 Quantum Use Cases
  • 8.2 QML Case Studies

  • 9.1 Project – I: QSVM for Iris Dataset
  • 9.2 Project – II: VQC/QNN on Iris Dataset
  • 9.3 Bonus: IBM Quantum Computers

  • 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

Tools You'll Master

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

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.

Exam Details

Duration
90 minutes
Passing Score
70% (35/50)
Format
50 multiple-choice/multiple-response questions
Delivery Method
Online via proctored exam platform (flexible scheduling)

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%

Choose the Format That Fits Your Schedule

What's Included (One-Year Subscription + All Updates):

  • High-Quality Videos, E-book (PDF & Audio), and Podcasts
  • AI Mentor for Personalized Guidance
  • Quizzes, Assessments, and Course Resources
  • Online Proctored Exam with One Free Retake
  • Comprehensive Exam Study Guide
  • Access for Tablet & Phone
Instructor-Led (Live Virtual/Classroom)
  • 5 days (live or virtual) Self-Paced: 40 hours of content
  • Real-time Q&A, peer collaboration, and hands-on labs
  • Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
  • 40 hours of content
  • Learn anywhere, anytime, with modular quizzes to track progress
Need More Flexibility?

Need More Flexibility?

To help you along your way, we can help you set up a customizable payment plan. Just book a call, we’ll provide you with the details!

Let's Arrange a Call

9/10 of our learners achieve their learning objectives after successful completionProcess Advisors

fortray global services

Hear it from our Alumni

fortray global services Success Stories
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Anu Lanish
Anu Lanish

IT Service Desk Technician

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Rahul Raj Nalam

Network Security (Traineeship)

My path to cloud architecture had its hurdles, but Fortray was there every step of the way. They provided valuable insights into cloud technologies and architectural design. With their guidance, I turned challenges into opportunities, and today, as a Cloud Architect, I help organizations leverage the cloud for their growth and success.
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Cloud Architect

The path to becoming a Cybersecurity Engineer felt like decrypting an impossible algorithm—until Fortray provided the key. Their mentorship was like a robust IPS, detecting and eliminating my weaknesses while optimizing my strengths. Now, I stand as a protector in the ever-evolving IT landscape, proud to carry their legacy forward.
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Full Stack Web Developer

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Data Scientist

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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.