Applied Data Science Lab: Predicting Spotify Likes

Hands-on Machine Learning with Music Data
Join us for an interactive, hands-on lab, where we’ll explore how machine learning can be used to predict whether a song will be “liked” based on its audio features. This four-part lab will guide you through the entire ML pipeline—from data exploration and model evaluation to deployment—using Spotify’s song data.

We’ll use Python, Pandas, Matplotlib, and Scikit-learn to build our model.

Who Should Join?
These labs are designed for data enthusiasts and aspiring data scientists looking to gain hands-on experience with real-world projects. These labs are typically held over four sessions.
Prerequisites: A basic understanding of Python will help you get the most out of the labs. Familiarity with Pandas is beneficial, but we’ll start with a brief review in the first session to ensure everyone has a solid foundation.
Install: Anaconda

Format:
🔹 Session 1: Project Overview and Dataset Introduction
🔹 Session 2: Exploratory Data Analysis (EDA) and Feature Engineering
🔹 Session 3: Machine Learning: Model Development and Evaluation
🔹 Session 4: Model Deployment and Final Insights

Goal of the Applied Data Science Labs
The goal of these labs is to provide a supportive, hands-on environment where learners can practice, experiment, and apply their data science knowledge with guidance from mentors and peers. Whether you're new to the field or looking to strengthen your skills, these labs offer the opportunity to work with real-world datasets and explore key areas like data wrangling, statistical analysis, data visualization, and machine learning. Through guided projects and collaborative exercises, participants can develop a portfolio that showcases their growing proficiency while building confidence in using popular data science tools.

We hope you join us!

AGENDA

• 6:00 p.m. – Welcome
• 6:05 p.m. – Applied Data Science Labs
• 6:20 p.m. – Spotify Project Overview and Dataset Introduction
• 6:35 p.m. – Pandas Review: Interviewing the Spotify Dataset
• 7:10 p.m. – Preview of the next session
• 7:20 p.m. – Questions/Discussion
• 7:30 p.m. – End