AI+ Quantum™

  • 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
Enroll Now
AI+ Quantum™
Self-Paced: $495
Instructor-Led: $595

At a Glance: Course + Exam Overview

Category AI Data & Robotics, AI Technical, All Courses, Available Now, English, Language, Quantum Computing Specialist, Statistician
Program Name AI+ Quantum™
Duration Instructor-Led:5 days (live or virtual) | Self-Paced:40 hours (5 Days)
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 Format 50 questions, 70% passing, 90 minutes, online proctored exam

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.

Certification 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

Finish the course and get certified

Course Certificate

Industry 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.

Frequently Asked Questions

Prerequisites

Exam Details

Passing Score

70%

Format

50 multiple-choice/multiple-response questions

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-Paced Online

Self-Paced Online: 40 hours (5 Days)

Price: $495

Instructor-Led Online

Instructor-Led Online: 5 days (live or virtual)

Price: $595

Core AI Tools Covered