Ce que vous devez savoir avant
Vous commencez

Débute 4 June 2026 15:44

Se termine 4 June 2026

00 Jours
00 Heures
00 Minutes
00 Secondes
course image

Quantum Machine Learning

Explorez l'intersection de pointe entre l'informatique quantique et l'apprentissage automatique avec notre cours sur l'Apprentissage Machine Quantique. Alors que l'informatique quantique évolue à une vitesse vertigineuse, parallèlement aux avancées en apprentissage automatique (ML) et en intelligence artificielle (IA), la question se pose : comment.
National Taiwan University via edX

National Taiwan University

10 Cours


L'Université Nationale de Taïwan (NTU) est une université de recherche de classe mondiale située à Taipei, Taïwan. Elle dispose d'un corps professoral de premier ordre, de programmes académiques complets, et d'une atmosphère amicale et dynamique qui en fait l'endroit parfait pour étudier et faire de la recherche.

Non spécifié

Amélioration optionnelle disponible

Tous niveaux

Progressez à votre rythme

Free

Amélioration optionnelle disponible

Aperçu

Explore the cutting-edge intersection of quantum computing and machine learning with our Quantum Machine Learning course. As quantum computing evolves at a breakneck speed, paralleling advancements in machine learning (ML) and artificial intelligence (AI), the question arises:

How can quantum technologies amplify the capabilities of learning algorithms?

This course delves into quantum-enhanced machine learning, aiming to unveil the potential benefits that current and forthcoming quantum technologies could bring to the ML realm, particularly in scenarios where classical computers struggle.

Participants will gain hands-on experience by implementing various protocols through Python's open-source frameworks, enhancing their practical understanding of the subject. The course is enriched with guest lectures from prominent figures in the field, including Alán Aspuru-Guzik, Seth Lloyd, Roger Melko, and Maria Schuld, offering deeper insights into each significant topic covered.

Key learning outcomes include:

  • Grasping the fundamentals of quantum states as an extension of classical probability distributions, their dynamics in different systems, and the role of measurements.
  • Comparing quantum computing models and their physical implementations, acknowledging the limitations of current and near-future quantum technologies, and identifying tasks where quantum computing shows promise over classical approaches.
  • Understanding and applying classical-quantum hybrid algorithms, encoding classical data into quantum systems, and exploring discrete optimization and unsupervised learning through quantum methods.
  • Mastering coherent quantum machine learning protocols, implementing significant quantum algorithms, and experimenting with quantum computing's capabilities in advanced mathematical operations.

Offered by the National Taiwan University through edX, this course is perfect for individuals eager to dive into the realms of Quantum Computing and Quantum Mechanics, promising to equip learners with the skills and knowledge to advance in this pioneering field.

Categories:

Quantum Computing Courses, Quantum Mechanics Courses.


Enseigné par

Peter Wittek


Matières