Download Our Latest Course Catalog | Download Now
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Download Our Latest Course Catalog | Download Now
This certification is built for engineers, data professionals, researchers, and developers who want to understand how machine learning and quantum computing come together. You’ll work with real-world datasets, use working code, and get familiar with the limitations, benefits, and practical applications of quantum systems.
You don’t need a physics degree. You just need curiosity and a solid grasp of programming and data logic.
This course helps you understand what quantum computing is, how it’s different from traditional computing, and when it’s useful to combine it with learning systems.
You’ll work on hands-on projects that explore topics like optimization, sampling, and simulations using both classical and quantum techniques. You’ll also learn how to work with hybrid setups using real platforms like IBM Qiskit and TensorFlow.
Strong understanding of Python
Familiarity with basic machine learning models
General knowledge of matrix operations and linear algebra
No quantum experience required
Software developers exploring new computing approaches
Data scientists curious about quantum-enhanced modeling
Technical consultants supporting high-compute workflows
Researchers testing quantum concepts with simulations
Engineers wanting to prepare for quantum integration
1. Can the course be taken online?
Yes. The course is available as a virtual instructor-led session with live teaching and hands-on labs.
2. Is in-person training available?
Yes. In-person sessions can be arranged at certified training centers or as private sessions for institutions or corporate teams.
3. Will I receive official course materials?
Yes. All participants receive electronic access to course materials. Printed versions are available upon request.
4. Is there a certificate of completion?
Yes. Upon successful completion of the course, participants will be awarded an AI CERTs official certificate.
Module 1: Overview of Artificial Intelligence (AI) and Quantum Computing
Artificial Intelligence Refresher
Quantum Computing Refresher
Module 2: Quantum Computing Gates, Circuits, and Algorithms
Quantum Gates and their Representation
Multi Qubit Systems and Multi Qubit Gates
Module 3: Quantum Algorithms for AI
Core Quantum Algorithms
QFT and Variational Quantum Algorithms
Module 4: Quantum Machine Learning
Algorithms for Regression and Classification
Algorithms for Dimensionality and Clustering
Module 5: Quantum Deep Learning
Algorithms for Neural Networks – Part I
Algorithms for Neural Networks – Part II
Module 6: Ethical Considerations
Ethics for Artificial Intelligence
Ethics for Quantum Computing
Module 7: Trends and Outlook
Current Trends and Tools
Future Outlook and Investment
Module 8: Use Cases & Case Studies
Quantum Use Cases
QML Case Studies
Module 9: Workshop
Project – I: QSVM for Iris Dataset
Project – II: VQC/QNN on Iris Dataset
Bonus: IBM Quantum Computers
Optional Module: AI Agents for Quantum
What Are AI Agents
Key Capabilities of AI Agents in Quantum Computing
Applications and Trends for AI Agents in Quantum Computing
How Does an AI Agent Work
Core Characteristics of AI Agents
Types of AI Agents
At DataCipher, we offer a variety of payment options for our Fortinet courses. Here are the methods available:
Purchase Order (PO) – If your organization prefers using a purchase order, begin the registration process by clicking the Register button. At the conclusion of the registration form, choose the option “My company will pay for it, please send an invoice with the payment details.” Our training team will then provide an official quote and any necessary additional information that your accounts department might need to issue the PO.
Bank Transfer – DataCipher maintains bank accounts in both the US and Europe, accommodating all standard bank transfer methods such as IBAN/BIC, Swift, ACH, or wire transfer. To make a payment via bank transfer, simply use the Register button to sign up for your selected course.
Credit Card Payments – We accept payments from all major credit cards, including Mastercard, VISA, American Express, Discover & Diners, and Cartes Bancaires. Payments can be made directly through the registration link or by requesting an invoice that includes a web link for online payment. All transactions are secure, and DataCipher does not store any credit card information.
These options are designed to make the registration process as smooth and flexible as possible for all participants.
Guaranteed to Run – DataCipher is committed to running this class unless unforeseen events such as an instructor’s accident or illness occur.
Guaranteed on Next Booking – The course will proceed once an additional student registers.
Scheduled Class – We have scheduled this course and rarely cancel due to low enrollment. We offer a “Cancel No More Than Once” guarantee, ensuring that if a class is canceled due to insufficient enrollment, the next session will run regardless of the number of attendees.
Sold Out – If the class is fully booked, please use our contact form to join the waiting list or to inquire about additional sessions. We’re here to accommodate your training needs and keep you informed of new opportunities.
At DataCipher, we offer our training courses in both traditional full-day and convenient half-day formats. Our half-day classes are specifically designed for IT professionals who cannot be away from their workplaces for consecutive full days. This flexible schedule allows participants to dedicate a few hours to learning and then return to their regular work responsibilities.
The curriculum for both the full-day and half-day formats is identical. The primary difference is that the half-day classes spread the coursework over a more extended period, providing a balanced approach to professional education. DataCipher has been successfully running these half-day training sessions for several years, receiving consistently positive feedback from our customers. They appreciate the flexibility and report that the extended timeframe facilitates a deeper understanding of the material, as it gives them more time to absorb and reflect on the information learned.
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