- Coursera
- advanced
- Free
Introduction to Quantum Information (KAIST)
- Level
- advanced
- Format
- Online course
- Duration
- 7 modules · ~5-12 weeks
- Provider
- Coursera
- Certificate
- Yes
- Price
- Free
Skills you'll gain
- Quantum Information
- Qubits
- Entanglement
- Quantum Teleportation
- Quantum Gates
- Quantum Channels
This course from the Korea Advanced Institute of Science and Technology (KAIST) presents quantum information at a beginning graduate level. Taught by Associate Professor Joonwoo Bae of the School of Electrical Engineering, it frames quantum theory as a framework for processing information and works carefully through how quantum properties translate into advantages for computing and communication tasks. It is free to audit on Coursera, with a paid certificate available.
The course opens by introducing quantum systems through single and two-qubit examples, then builds up the axioms of quantum theory: quantum states, operators, and measurement. From this foundation it develops the core machinery of quantum information processing, including quantum gates, quantum circuits, and algorithms. A recurring theme is entanglement as a physical resource, which is what makes effects like quantum teleportation and superdense coding possible.
Who is this for?
This is an advanced course aimed at students and professionals who want a rigorous, theory-first grounding in quantum information rather than a tools-focused programming course. While the course states no strict prerequisites, it is genuinely at a graduate level: comfort with linear algebra, probability, and basic information theory will make the material far more approachable.
For a similarly rigorous treatment that also includes graded problem sets, see MIT’s OpenCourseWare Quantum Computation course. This KAIST course, by contrast, has no listed problem sets or programming component in its Coursera format, so learners who want hands-on practice alongside the theory should pair it with a coding-focused course such as IBM Learning’s Basics of Quantum Information.
Prerequisites
Linear algebra (vector spaces, inner products, eigenvalues), probability theory, and ideally some exposure to classical information theory. No programming is required, as the course focuses on the mathematical and conceptual framework rather than implementation.
Topics covered
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