QC101 Quantum Computing & Intro to Quantum Machine Learning

Math-Based Introduction to Quantum Computing, Cryptography & Quantum Machine Learning. Code with Python, Q#, & Qiskit

4.59 (3516 reviews)

Udemy

platform

English

language

Software Engineering

What you will learn

Use quantum cryptography to communicate securely

Develop, simulate, and debug quantum programs on IBM Qiskit and Microsoft Q#

Run quantum programs on a real quantum computer through IBM Quantum Experience

Use Dirac's notation and quantum physics models to analyze quantum circuits

Train a Quantum Support Vector Machine (Quantum Machine Learning) on real-world data and use it to make predictions

Learn Data science and how quantum computing can help in artificial intelligence / machine learning

Learn why machine learning will be the killer-app for quantum computing

Course Gallery

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QC101 Quantum Computing & Intro to Quantum Machine Learning – Screenshot 4 — Screenshot 4 – QC101 Quantum Computing & Intro to Quantum Machine Learning

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Comidoc Review

Our Verdict

*QC101 Quantum Computing & Intro to Quantum Machine Learning* offers an expansive look into the world of quantum computing, providing learners with a math-based and accessible approach. Despite minor areas for improvement such as providing more practice opportunities and expanding on machine learning topics, the course delivers value through clear explanations of complex topics backed by hands-on coding tasks using Q# and Qiskit. Ideal candidates include STEM professionals looking to dive into quantum computing or expand their knowledge in artificial intelligence & machine learning using a quantum perspective.

What We Liked

Comprehensive coverage of quantum computing concepts, including cryptography and machine learning
Instructor explains complex topics in an easy-to-understand manner using analogies and clear examples
Well-designed course structure with a strong focus on fundamentals makes it accessible for learners at various levels
Hands-on coding experience using popular quantum programming languages such as Q# and Qiskit

Potential Drawbacks

Occasional repetition of basic concepts, which might be unnecessary for more experienced learners
Machine learning portion could be more in-depth, specifically on converting classical to quantum algorithms
Lack of practice problems and guided exercises for better hands-on experience
Instructor sometimes assumes certain questions without explicitly addressing them