Note: Peter Wittek, the creator of the MOOC, disappeared in an avalanche in October 2019. So let's take a moment to remember him and honour him for these notes and his contribution to QML.
These notebooks are part of the Quantum Machine Learning course offered in EdX. Here is the original repo.
However, I plan to make some heavy changes in most of the notes I have already updated some of them and I am in the process of changing others. Some of the standard changess include the using latest qiskit version in the notebooks and removing the deprecated functions.
I also plan to add a few chapters from Qiskit textbook in the middle in order to make the course a complete cource for any one from beginner level to the more advanced level.
Here is the git repo for Quantum Computing class -Fall 2020.
Here is the link for the YouTube videos of the lectures.
Few More Qiskit chapters will be added in the middle
- 00 and 01 Introduction to the Course and Qiskit
- 02 Measurements and Mixed States
- 03 Evolution in Closed and Open Systems
- 04 Classical and Quantum Many-Body Physics
- 05 Gate-Model Quantum Computing
- 05 II DJ, Shor Algorithm
- 05 III Shor algorithm, Quantum Fourier Transform
- 06 Adiabatic Quantum Computing
- 07 Variational Circuits
- 08 Sampling a Thermal State
- 09 Discrete Optimization and Ensemble Learning
- 10 Discrete Optimization and Unsupervised Learning
- 11 Kernel Methods
- 12 Training Probabilistic Graphical Models
- 13 Quantum Phase Estimation
- 14 Quantum Matrix Inversion
- Here is the link for Quantum Computing Since Democritus by Scott Aaronson. Please check the suggested reading list in that webpage.