1. Introduction
  - Background and motivation
  - Objectives of the project
2. Literature Review
  - Overview of recommendation systems
  - Existing approaches in music recommendation
3. Data Collection and Preprocessing
  - Acquisition of music listening data
  - Data cleaning and preprocessing
4. Recommendation System Design
  - Selection of machine learning algorithms
  - Feature engineering and model design
5. Implementation and Testing
  - Development of the recommendation engine
  - Evaluation and testing of the system