</> Hands-On Engineering

AI+ Quantum Practitioner™

Formerly known as AI+ Quantum™ <br> <br>Harness Quantum Power with AI

Instructor-Led: 5 days (live or virtual)  Self-Paced: 40 hours of content
Hands-On Labs
Real Projects
Capstone Build
View Modules
AI+ Quantum Practitioner™
Tech you'll master:
Python LLMs LangChain Vector DBs Cloud APIs
// What You'll Build

Engineering-First Curriculum

  • 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
// SPECS

Program Details

Duration

  • Instructor-Led: 5 days (live or virtual) 
  • Self-Paced: 40 hours of content

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

Included

Instructor-led OR Self-paced course + Official exam + Digital badge

// CURRICULUM

Module Stack

Each module includes hands-on labs and real-world projects.

[01]

Module 1: Overview of Artificial Intelligence (AI) and Quantum Computing

  1. 1.1 Artificial Intelligence Refresher
  2. 1.2 Quantum Computing Refresher
[02]

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
[03]

Module 3: Quantum Algorithms for AI

  1. 3.1 Core Quantum Algorithms
  2. 3.2 QFT and Variational Quantum Algorithms
[04]

Module 4: Quantum Machine Learning

  1. 4.1 Algorithms for Regression and Classification
  2. 4.2 Algorithms for Dimensionality and Clustering
[05]

Module 5: Quantum Deep Learning

  1. 5.1 Algorithms for Neural Networks – Part I
  2. 5.2 Algorithms for Neural Networks – Part II
[06]

Module 6: Ethical Considerations

  1. 6.1 Ethics for Artificial Intelligence
  2. 6.2 Ethics for Quantum Computing
[07]

Module 7: Trends and Outlook

  1. 7.1 Current Trends and Tools
  2. 7.2 Future Outlook and Investment
[08]

Module 8: Use Cases & Case Studies

  1. 8.1 Quantum Use Cases
  2. 8.2 QML Case Studies
[09]

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
[10]

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
Why Engineers Choose This

Career-Defining Skills

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.