
A Practical Guide to Generative Music AI for Developers April 2025
Lancelot Blanchard
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£1499.00
(including tax)Session 1: An Introduction to AI Music
- Main Topics: AI Music Case Studies, Course Roadmap
- An Introduction to AI Music (50')
- Session 1 PDF handout
- Open Discussion
Session 2: Setting up your environment
- Main Topics: Environment Setup
- GitHub Repository
- Setting up your environment - Cloning the class repository (10')
- Hands On
- Setting up your environment - Hands On 1.1: Loading, visualizing, playing audio (10')
- Setting up your environment - Hands On 1.2: Extracting Audio Features, RMS and ZCR (13')
- Setting up your environment - Hands On 1.2: Extracting Audio Features, Spectrograms (13')
- Setting up your environment - Hands On 2: Manipulating MIDI Data (20')
Session 3: Core Machine Learning Concepts for Music and Audio
- Main Topics: Audio vs Symbolic Music, Basics of Generative AI, Data Acquisition and Ethics
- Statistical Basics of Generative Modeling in Artificial Intelligence (10')
- Variational Autoencoders (16')
- Hands On
- Hands On 1.1: Lakh MIDI Dataset (12')
- Hands On 1.2: Free Music Archive (6')
- Hands On 2: Using RAVE
Session 4: Real-Life Collaborations between Artists and Engineers with Guest Speaker Jordan Rudess
- Main Topics: Human-Computer Interaction, Iterative Design, Continuous Deployment
- Human-Computer Interaction & User-Centered Design
- Open Discussion with Jordan Rudess
Session 5: Representation Learning for Music
- Deep Dive into MIDI & Spectrograms
- Comparing Musical Representations & Encodec Deep Dive (14')
- Understanding RVQ in Encodec (12')
- Hands On
- Hands On: Encodec (29')
Session 6: Autoregressive Music Generation
- Main Topics: Autoregressive modeling, the Transformer architecture, HuggingFace Hub
- The Transformer architecture (15')
- Understanding Anticipatory Music Transformers (13')
- Hands On
- Hands On: Using AMT to generate MIDI data (Part 1) (18')
- Hands On: Using AMT to generate MIDI data (Part 2) (17')
Session 7: Autoregressive Music Generation (Part 2)
- Main Topics: MusicGen & Audio Generation with Transformers
- Understanding MusicGen (8')
- Hands On
- Hands On: Using MusicGen to generate audio (38')
Session 8: Diffusion Models for Music Generation
- Main Topics: Diffusion Models, Latent Diffusion Models
- Intro to Diffusion Models Part 1 (11')
- Intro to Diffusion Models Part 2 (14')
- Conditioning & Classifier-Free Guidance (10')
- The UNet Architecture (6')
- Inference-Time Optimization: DITTO (6')
- Hands On
- Hands On: Using Stable Audio Part 1 (15')
- Hands On: Using Stable Audio Part 2 (18')
Session 9: Real-Time Generative AI & Commercial Applications of Generative AI in Music [Guest: Christian Steinmetz]
- Introduction to TorchScript (18')
- 8-bit Linear Quantization (9')
- ONNX and Graph Optimizations (15')
- Main Topics: Landscape of companies in AI and Music, Available Commercial Products
- Demo
Session 10: Final Project Planning
- Main Topics: Setting up a project specification, timeline, and scope
- Training Part 1 (8')
- Training Part 2 (13')
- Training Part 3 (16')
- Peer Review & Feedback
Session 11: Final Project Lab
- Session 11
- Lab Session: Guided Coding & Troubleshooting
- Milestone Check-Ins
Session 12: Project Showcase & Next Steps
- Final Presentations
- Next Steps