All lesson materials are stored in Jupyter notebooks. The lectures are currently organized as follows (though subject to fairly frequent updating/modification):
- Lesson 01a: Installing jupyter
- Lesson 01b: Jupyter Basics: Python preparation
- Lesson 02a: Intro Python Sound
- Lesson 02b: Intro Lesson: Numpy
- Lesson 03: More Python and Numpy
- Lesson 04a: Sinusoids
- Lesson 04b: Functions Python
- Lesson 05: Working with Sound
- Lesson 6a: Synthesis Part 1
- Lesson 6b: Synthesis Part 2
- Lesson 07: Envelopes
- Lesson 08a: Signal Modulation Part 1
- Lesson 08b: Signal Modulation Part 2
- Lesson 09: Delay
- Lesson 10: Convolution
- Lesson 10: Frequency Content - Spectrum and Frequency Filtering
- Lesson 11: Pulse with Modulation
- Lesson 12: DFT Review
- Lesson 13: Frequency and pitch shifting
- Lesson 13: Psychoacoustic and Masking
- Lesson 14: DFT Review
- Lesson 15: STFT Part 1
- Lesson 16: STFT Part 2
- Lesson 17: Feature Extraction
- Lesson 18: Pandas Dataframe
- Lesson 19: Chromagrams
- Lesson 19: Data Science 1
- Lesson 19: Pitch Features
- Lesson 20: Energy and RMSE
- Lesson 20: Correlation and Key Finding
- Lesson 21: Autocorrelation
- Lesson 21: Intro Pandas Dataframes
- Lesson 22: Data Science 2
- Lesson 22: Statistical Modeling
- Lesson 23: Data Science 3
Activities relate to class lectures and offer opportunities for students to test out functions or practice skills in a clean Jupyter notebook with directives (without having to modify the lecture material notebooks).
Note that notebooks point to audio and image files from the separate directories. Renaming the directories will cause the notebooks to error. As such, it is advised not to change directory names.
Interactive web tools (originally created by Jiaying Li) are provided for additional reference and hands-on manipulation using a GUI without having to code any parameters. The interaction tools are available here: