intermediate

Music Player With Smart Recommendations in Python

Build a smart, data-powered music recommendation system from the ground up. You’ll use Python, Pandas, and scikit-learn to analyze track metadata, log user sessions, and generate personalized song suggestions using similarity scoring and predictive models.

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Verified skills you'll gain

DEVELOPING

API Integration, Design, & Development

INTERMEDIATE

Server-Side Programming

Tools you'll use

Flask

Pandas

Python

sklearn

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Course 2

Embedding-Based Recommendation with Similarity Scoring

4 lessons

16 practices

Dive into the world of smart recommendations! You'll learn to transform music track features like genre, mood, and tempo into numerical vectors (embeddings). Then, you'll create user profiles based on their listening history and use cosine similarity to find and suggest new tracks they might love. You'll also explore clustering techniques to group similar songs.

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Course 3

Learning to Predict User Preferences

4 lessons

15 practices

Take your recommendation engine to the next level with supervised machine learning! You'll learn how to prepare training data from user listening logs, train a classification model (like Logistic Regression) to predict track affinity, and use these predictions to offer even more personalized music suggestions.

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Course 4

Building the Interactive Music Recommendation Dashboard

3 lessons

10 practices

In this final course, learners will complete the Smart Music Player by integrating a clean, interactive frontend interface and enhancing the recommendation engine with session-aware logic. This course focuses on adding backend intelligence through recent session trend analysis and dynamic context-based recommendations.

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I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

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From our community

Hear what our customers have to say about CodeSignal Learn

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11

I love that it's personalized. When I'm stuck, I don't have to hope my Google searches come out successful. The AI mentor Cosmo knows exactly what I need.

Faith Yim

Software Engineer

+14

It's an amazing product and exceeded my expectations, helping me prepare for my job interviews. Hands-on learning requires you to actually know what you are doing.

Alex Bush

Full Stack Engineer

I'm really impressed by the AI tutor Cosmo's feedback about my code. It's honestly kind of insane to me that it's so targeted and specific.

Abbey Helterbran

Tech consultant

I tried Leetcode but it was too disorganized. CodeSignal covers all the topics I'm interested in and is way more structured.

Jonathan Miller

Senior Machine Learning Engineer

+12

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11