EdX

Applied Quantum Computing I: Fundamentals (edX)

Offered by Purdue University, PurdueX,
Applied Quantum Computing I: Fundamentals (edX)

Learn the fundamental postulates of quantum mechanics and how they can be mapped onto present-day quantum information processing models, including computation, simulation, optimization, and machine learning.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

This fundamentals course is part 1 of the series of quantum computing courses and covers aspects from fundamentals to present-day hardware platforms to quantum software and programming. This course provides the essential foundations required to understand computing models built from the principles of quantum mechanics.
This course requires a minimal set of engineering and science prerequisites but will allow students to develop a physical and intuitive understanding of the topics.
Attention:
Quantum Computing 1: Fundamentals is an essential prerequisite to Quantum Computing 2: Hardware and Quantum Computing 3: Algorithm and Software. Learners should plan to complete Fundamentals before enrolling in the Hardware or the Algorithm and Software courses.
This course is part of the Quantum Technology: Computing MicroMasters and Quantum Technology: Detectors and Networking MicroMasters.

What you'll learn

  • Postulates of quantum mechanics
  • Gate-based quantum computing
  • Quantum errors and error correction
  • Adiabatic quantum computing
  • Quantum simulation
  • Quantum machine learning
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Foundations of Data Analytics (edX) EdX
The Hong Kong University of Science and Technology - HKUST,HKUSTx

Foundations of Data Analytics (edX)

Learn the fundamental techniques for data analytics and to be prepared for learning and applying more advanced big data technologies. Foundations of Data Analytics: This course will provide fundamental techniques for data analytics, including data collection, data extraction, data integration, data cleansing, and basic machine learning techniques.

Self Paced
Self-Paced
PyTorch Basics for Machine Learning (edX) EdX
IBM

PyTorch Basics for Machine Learning (edX)

This course is the first part in a two part course and will teach you the fundamentals of PyTorch. In this course you will implement classic machine learning algorithms, focusing on how PyTorch creates and optimizes models. You will quickly iterate through different aspects of PyTorch giving you strong foundations and all the prerequisites you need before you build deep learning models.

Self Paced
Self-Paced
Data Science: Capstone (edX) EdX
HarvardX,Harvard University

Data Science: Capstone (edX)

Show what you’ve learned from the Professional Certificate Program in Data Science. To become an expert data scientist you need practice and experience. By completing this capstone project you will get an opportunity to apply the knowledge and skills in R data analysis that you have gained throughout the series. This final project will test your skills in data visualization, probability, inference and modeling, data wrangling, data organization, regression, and machine learning.

Self Paced
Self-Paced
CS50's Introduction to Artificial Intelligence with Python (edX) EdX
HarvardX,Harvard University

CS50's Introduction to Artificial Intelligence with Python (edX)

Learn to use machine learning in Python in this introductory course on artificial intelligence. AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.

Self Paced
Self-Paced
Recommender Systems: Behind the Screen (edX) EdX
Université de Montréal,UMontrealX

Recommender Systems: Behind the Screen (edX)

How are items recommended when you’re browsing for movies, jobs or clothing online? Register here and you’ll discover the fundamental concepts and methods allowing the most relevant item suggestions to users from e-commerce to online advertisement. In this course, you will explore and learn the best methods and practices in recommender systems, which are an essential component of the online ecosystem. This course was developed by IVADO and HEC Montréal as part of a workshop that took place in Montreal.

Self Paced
5-12 Weeks
Digital Marketing Analytics: Tools and Techniques (edX) EdX
University of Maryland, College Park,University System of Maryland - USM,USMx,UMD

Digital Marketing Analytics: Tools and Techniques (edX)

Learn how to leverage leading tools and approaches to digital marketing data analysis. Dive into SEO and SEM strategies including web analytics, machine learning and AI/Big Data applications to strengthen your digital marketing efforts and leverage your resources most effectively.

Self Paced
Self-Paced
Modeling and Simulation of Multibody Systems - Part I (edX) EdX
LouvainX,Université Catholique de Louvain - UCL

Modeling and Simulation of Multibody Systems - Part I (edX)

Vehicles, bicycles, cranes, human body and robots are multibody systems. Learn how to model them and compute their kinematic and dynamic characteristics, such as velocities, accelerations and forces. This course aims at acquainting you with the modeling and simulation of complex articulated mechanical systems, denoted as multibody systems, such as vehicles, merry-go-rounds, motorbikes, cranes, human bodies, suspensions, robot manipulators, mechanical transmissions, etc.

Self Paced
Self-Paced