Course Description

The AI Quantum certification bridges the gap between Artificial Intelligence and Quantum Computing, offering an in-depth exploration of cutting-edge technologies. The course delves into Quantum Computing Gates, Circuits, and Algorithms, with a focus on real-world AI applications. Participants will explore advanced topics like Quantum Machine Learning, Quantum Deep Learning, and their transformative impact on traditional AI methodologies. This program critically examines ethical implications, explores industry trends, and provides hands-on workshops to solidify knowledge. Real-world case studies offer practical insights, making this certification essential for professionals and enthusiasts aiming to lead in the evolving field of AI and Quantum Computing.

Course Objectives

  • Learn to design and implement quantum algorithms optimized for AI applications, including how quantum gates operate within these frameworks.​
  • Discover how quantum principles can enhance machine learning and deep learning models for superior performance.
  • Gain practical skills in constructing and optimizing quantum circuits to solve complex computational challenges.
  • Master techniques to fine-tune quantum-AI systems, improving efficiency and reducing computational complexity.

Who Should Attend?

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.

Course Agenda

  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

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.