QC101 Quantum Computing & Intro to Quantum Machine Learning

This is the bestselling quantum computing course on Udemy, carrying both “Bestseller” and “Highest Rated” badges, and created by Kumaresan Ramanathan. It is designed for beginners and starts from quantum physics fundamentals before progressing to practical quantum programming. With over 26,000 students enrolled, it is one of the most popular paid quantum computing courses anywhere.

The course is notably hands-on across multiple frameworks. Learners build quantum circuits using both Microsoft Q# and IBM Qiskit, and run programs on real quantum computers through IBM Quantum. It covers quantum cryptography for secure communication and then extends into quantum machine learning, including training a quantum support vector machine on real-world data. This breadth - physics, two programming stacks, real hardware, and a QML on-ramp - is what makes it a strong single entry point.

Who is this for?

Beginners who want a guided, video-based path from quantum physics basics through to writing and running real quantum programs. It suits self-learners, software developers, and students who prefer a structured course over piecing together free resources.

One trade-off worth knowing: covering physics, two programming stacks (Q# and Qiskit), and a QML on-ramp in one course means each topic gets a pass rather than exhaustive depth. Learners who want to go deep on Qiskit specifically may want to follow this with a Qiskit-focused course or the PennyLane Codebook once they know which direction they want to specialize in.

Prerequisites

No prior quantum computing experience is required. Some comfort with high-school mathematics and basic programming concepts will help, particularly when working through the Qiskit and Q# coding sections.