OpenCourser brand icon
Sign in
We may earn an affiliate commission when you visit our partners.
Course image
Course image
Coursera logo

ETL pipelines con Python

recopila datos de Spotify

Pablo Agustin Martinez

Este Proyecto Guiado ETL pipelines con Python: recopila datos de Spotify es para aquellos apasionados por descubrir los secretos musicales ocultos en la vasta biblioteca de Spotify. En este curso basado en proyectos de 1.5 horas de duración, aprenderás cómo: Extraer y transformar datos detallados sobre preferencias musicales desde la API de Spotify utilizando Python y aplicar técnicas de visualización para comunicar claramente los insights musicales a través de gráficos y presentaciones interactivas. Para lograr esto, trabajaremos a través de las siguientes tareas: Configuración del entorno de desarrollo con Python, Obtención de credenciales de la API de Spotify y consultas iniciales, Prácticas para explorar datos extraídos, identificar patrones y tendencias y Ejercicios sobre el uso de herramientas de Business Intelligence para crear visualizaciones interactivas y presentar insights musicales.

Read more

Este Proyecto Guiado ETL pipelines con Python: recopila datos de Spotify es para aquellos apasionados por descubrir los secretos musicales ocultos en la vasta biblioteca de Spotify. En este curso basado en proyectos de 1.5 horas de duración, aprenderás cómo: Extraer y transformar datos detallados sobre preferencias musicales desde la API de Spotify utilizando Python y aplicar técnicas de visualización para comunicar claramente los insights musicales a través de gráficos y presentaciones interactivas. Para lograr esto, trabajaremos a través de las siguientes tareas: Configuración del entorno de desarrollo con Python, Obtención de credenciales de la API de Spotify y consultas iniciales, Prácticas para explorar datos extraídos, identificar patrones y tendencias y Ejercicios sobre el uso de herramientas de Business Intelligence para crear visualizaciones interactivas y presentar insights musicales.

Este proyecto es único porque no solo te sumergirás en el mundo de la programación y el análisis de datos, sino que lo harás a través de la lente musical de Spotify. Para tener éxito, se recomienda tener conocimientos básicos de Python y un interés genuino en descubrir las historias que los datos musicales tienen para contar. ¡Prepárate para explorar y analizar la música desde una perspectiva única!

Enroll now

Here's a deal for you

Save money when you learn with a deal that may be relevant to this course.
All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.
Valid until March 12, 2027
Save 40% Off 3 Months
Access thousands of top-rated learning programs with a Coursera Plus monthly subscription and take 40% off 3 months for a limited time.
Take
40%
off
Get offer

What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Se enfoca en el análisis de datos musicales de Spotify, lo cual es de interés particular para los entusiastas de la música
Brinda una visión general del proceso ETL (Extracción, Transformación y Carga) de datos en Python, una habilidad esencial en el análisis de datos
Enseña técnicas de visualización de datos para comunicar los resultados del análisis de forma clara y atractiva
Requiere conocimientos básicos de Python, lo que puede ser una barrera para los principiantes absolutos

Save this course

Create your own learning path. Save this course to your list so you can find it easily later.
Save

Reviews summary

Proyecto práctico etl con python y spotify

Según los estudiantes, este curso de ETL con Python es un proyecto guiado muy práctico y útil para aplicar conocimientos existentes. Muchos learners lo encuentran ideal para consolidar habilidades en manejo de datos y uso de APIs, destacando la integración con la API de Spotify como un punto fuerte y motivador. Las instrucciones son claras y fáciles de seguir, permitiendo una experiencia de aprendizaje eficiente. Sin embargo, algunos indican que el ritmo puede ser un poco rápido y que se asumen conocimientos básicos de Python, lo que podría ser un desafío para principiantes absolutos. La cobertura de la visualización de datos y BI es introductoria, lo cual es esperable para su corta duración.
Los pasos son fáciles de seguir y el instructor explica bien.
"Los pasos son claros y el instructor explica muy bien. Ideal para consolidar conocimientos de Python..."
"La guía es precisa y el ejemplo de Spotify es muy motivador."
"La configuración del entorno es sencilla de seguir."
"El paso a paso es muy intuitivo y el uso de la API de Spotify es genial para ver aplicaciones reales..."
La integración con la API de Spotify es muy atractiva.
"La parte de la API de Spotify fue lo más interesante."
"Me encanta la aplicación real con Spotify. ¡Totalmente recomendable para quien busca un proyecto práctico!"
"La forma de obtener datos de Spotify es clara y útil para ver aplicaciones reales de Python en data science."
Ideal para aplicar Python en un escenario real de ETL.
"Excelente proyecto guiado. En poco tiempo, logré entender el proceso ETL con Python usando una API real."
"Magnífico curso para practicar ETL. La guía es precisa y el ejemplo de Spotify es muy motivador."
"Corto pero útil. Lo mejor es que es práctico. No es para aprender Python desde cero, sino para aplicar lo que ya sabes."
"Me encantó la dinámica del proyecto. El paso a paso es muy intuitivo y el uso de la API de Spotify es genial..."
La sección de visualización es introductoria, no profundiza.
"Me hubiera gustado un poco más de profundidad en la visualización, pero para 1.5 horas, es completo."
"Muy superficial en la parte de BI. Siento que solo muestra lo básico sin ir a fondo. Para una introducción, está bien."
Asume conocimientos previos de Python; puede ser rápido para novatos.
"Un poco rápido para mi gusto. Asume que sabes bastante de Python, y aunque lo dice, me costó seguir algunas partes."
"No es para aprender Python desde cero, sino para aplicar lo que ya sabes."
"Si buscas algo más allá de lo básico, necesitarás otros recursos."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in ETL pipelines con Python: recopila datos de Spotify with these activities:
Review Python basics
Refreshes foundational knowledge of Python programming concepts and prepares you for subsequent coursework.
Browse courses on Python
Show steps
  • Review Python data types, variables, and operators.
  • Practice writing simple Python programs.
  • Review Python control flow and functions.
Explore Spotify's API documentation
Gain insights into the capabilities of the Spotify API to effectively navigate and utilize it for data extraction.
Browse courses on Spotify API
Show steps
  • Visit the Spotify Developers website and access API documentation.
  • Review authentication methods and API endpoints.
  • Follow guided tutorials to make API requests and handle responses.
Formar un grupo de estudio
Participar en un grupo de estudio con tus compañeros te permitirá colaborar, compartir ideas y obtener apoyo adicional para las tareas del proyecto.
Show steps
  • Conectar con otros estudiantes del curso y formar un grupo de estudio.
  • Establecer un horario regular para las sesiones de estudio.
  • Compartir notas, discutir conceptos y trabajar juntos en ejercicios de práctica.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Explore the Spotify API
Develops proficiency in using the Spotify API to extract musical data directly from the source.
Browse courses on Spotify API
Show steps
  • Follow official Spotify API documentation.
  • Experiment with API calls to retrieve different types of musical data.
  • Build a small Python script that utilizes the API.
Extract and transform musical data from Spotify
Provides hands-on experience in extracting and transforming raw musical data from Spotify to prepare it for analysis.
Browse courses on Data Extraction
Show steps
  • Write Python code to connect to the Spotify API.
  • Retrieve data on specific artists, albums, or tracks.
  • Clean and preprocess the extracted data for analysis.
Develop data visualizations to communicate musical insights
Fosters skills in communicating complex musical data clearly and effectively through interactive visualizations.
Browse courses on Data Visualization
Show steps
  • Choose appropriate data visualization techniques for the insights you want to convey.
  • Use Python libraries to create interactive visualizations.
  • Present your visualizations in a clear and engaging manner.
Develop an interactive dashboard of musical insights
Demonstrate your understanding of data presentation by creating a dynamic and engaging dashboard that showcases key musical trends and insights.
Show steps
  • Identify key metrics and trends to display on the dashboard.
  • Select appropriate visualization techniques to effectively convey insights.
  • Use Python libraries such as Plotly or Dash to create the interactive dashboard.
Crear una presentación sobre los insights musicales
Crear una presentación que comunique los insights musicales extraídos de los datos de Spotify te permitirá consolidar tu comprensión y mejorar tus habilidades de comunicación.
Show steps
  • Analizar los datos transformados para identificar patrones, tendencias e insights musicales.
  • Diseñar una presentación clara e impactante, utilizando herramientas de visualización como gráficos, tablas y mapas de calor.
  • Preparar un discurso conciso y atractivo que guíe a la audiencia a través de los insights musicales.

Career center

Learners who complete ETL pipelines con Python: recopila datos de Spotify will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to provide insights to businesses. This course can help build a foundation for a career as a Data Analyst by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as data exploration and pattern identification, which are essential skills for Data Analysts.
See salaries and explore the career path for Data Analyst
Data Engineer
A Data Engineer is responsible for designing, building, and maintaining data pipelines. This course can help build a foundation for a career as a Data Engineer by providing learners with experience in extracting, transforming, and loading data. The course also covers topics such as data integration and data quality, which are essential skills for Data Engineers.
See salaries and explore the career path for Data Engineer
Data Scientist
A Data Scientist is responsible for using data to solve business problems. This course can help build a foundation for a career as a Data Scientist by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as machine learning and statistical modeling, which are essential skills for Data Scientists.
See salaries and explore the career path for Data Scientist
Business Analyst
A Business Analyst is responsible for understanding and improving business processes. This course can help build a foundation for a career as a Business Analyst by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as process mapping and requirements gathering, which are essential skills for Business Analysts.
See salaries and explore the career path for Business Analyst
Market Researcher
A Market Researcher is responsible for collecting and analyzing data about consumers and markets. This course can help build a foundation for a career as a Market Researcher by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as survey design and data analysis, which are essential skills for Market Researchers.
See salaries and explore the career path for Market Researcher
Product Manager
A Product Manager is responsible for developing and managing products. This course can help build a foundation for a career as a Product Manager by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as user research and product development, which are essential skills for Product Managers.
See salaries and explore the career path for Product Manager
Sales Analyst
A Sales Analyst is responsible for analyzing sales data to identify trends and opportunities. This course can help build a foundation for a career as a Sales Analyst by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as sales forecasting and data mining, which are essential skills for Sales Analysts.
See salaries and explore the career path for Sales Analyst
Financial Analyst
A Financial Analyst is responsible for analyzing financial data to make investment decisions. This course can help build a foundation for a career as a Financial Analyst by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as financial modeling and data analysis, which are essential skills for Financial Analysts.
See salaries and explore the career path for Financial Analyst
Operations Research Analyst
An Operations Research Analyst is responsible for using data to solve operational problems. This course can help build a foundation for a career as an Operations Research Analyst by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as optimization and simulation, which are essential skills for Operations Research Analysts.
See salaries and explore the career path for Operations Research Analyst
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software applications. This course can help build a foundation for a career as a Software Engineer by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as software design and data structures, which are essential skills for Software Engineers.
See salaries and explore the career path for Software Engineer
Web Developer
A Web Developer is responsible for designing and developing websites. This course can help build a foundation for a career as a Web Developer by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as web design and programming, which are essential skills for Web Developers.
See salaries and explore the career path for Web Developer
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. This course can help build a foundation for a career as a Database Administrator by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as database design and data security, which are essential skills for Database Administrators.
See salaries and explore the career path for Database Administrator
Network Administrator
A Network Administrator is responsible for managing and maintaining computer networks. This course may be useful for building a foundation for a career as a Network Administrator by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as network design and security, which are essential skills for Network Administrators.
See salaries and explore the career path for Network Administrator
Computer Systems Analyst
A Computer Systems Analyst is responsible for analyzing and designing computer systems. This course may be useful for building a foundation for a career as a Computer Systems Analyst by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as systems analysis and design, which are essential skills for Computer Systems Analysts.
See salaries and explore the career path for Computer Systems Analyst
Technical Writer
A Technical Writer is responsible for creating technical documentation. This course may be useful for building a foundation for a career as a Technical Writer by providing learners with experience in extracting, transforming, and visualizing data. The course also covers topics such as technical writing and information design, which are essential skills for Technical Writers.
See salaries and explore the career path for Technical Writer

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in ETL pipelines con Python: recopila datos de Spotify.
Cover image
Hands-On Data Analysis with Pandas
Save
Este libro práctico guía a los estudiantes a través del análisis de datos con Pandas, la biblioteca principal utilizada en este proyecto. Proporciona una base sólida para la manipulación, exploración y visualización de datos, lo que es esencial para extraer insights musicales significativos.
(English) Hands-On Data Analysis with Pandas - Second Edition...
Paperback
$$
(English) Hands-On Data Analysis with Pandas: Efficiently...
Kindle Edition
$$
Cover image
The Data Science Handbook
Save
Este manual completo cubre una amplia gama de temas de ciencia de datos, desde el procesamiento de datos hasta el modelado estadístico. Proporciona una referencia valiosa para los estudiantes que buscan profundizar su comprensión de los conceptos y técnicas subyacentes al proyecto.
(English) The Data Science Handbook: Advice and Insights from...
Paperback
$$
Cover image
Python for Data Analysis
Save
Este libro es una guía esencial para el uso de Python para el análisis de datos. Proporciona una base sólida para los estudiantes que son nuevos en Python o desean mejorar sus habilidades, lo que les permite aprovechar al máximo las capacidades de Python para la manipulación y el análisis de datos.
Python for Data Analysis
Paperback
Check
Python for Data Analysis
Kindle Edition
Check
Cover image
Beautiful Data
Save
Este libro inspirador explora el arte y la ciencia de la visualización de datos. Proporciona una visión única sobre cómo comunicar de manera efectiva los insights de los datos a través de visualizaciones atractivas y fáciles de entender.
(English) Beautiful Data: The Stories Behind Elegant Data...
Kindle Edition
$$
Cover image
Python Web Scraping
Save
Este libro proporciona una introducción integral a las herramientas de código abierto para el análisis de datos. Es una guía valiosa para los estudiantes que buscan aprovechar las capacidades de software gratuito y de código abierto para sus proyectos de análisis de datos.
(English) Python Web Scraping - Second Edition: Hands-on data...
Paperback
$$
(English) Web Scraping With Python: Scrape Data from Any...
Paperback
$$
(English) Python web scraping (Korean Edition)
Paperback
$$$
(English) Python Web Scraping: Hands-on data scraping and...
Kindle Edition
$$
(English) Web Scraping with Python (Community Experience...
Kindle Edition
$$
Cover image
Python for Everybody
Save
Este libro es una introducción completa a Python. Proporciona una base sólida para los estudiantes que son nuevos en Python o desean repasar los conceptos básicos, lo que les permite aprovechar eficazmente las capacidades de Python para el análisis de datos.
(English) Python for Everybody: Exploring Data in Python 3
Paperback
$$
Data Mining
Save
Este libro de texto clásico proporciona una cobertura integral de los conceptos y técnicas de minería de datos. Es una referencia valiosa para los estudiantes que buscan profundizar su comprensión de los métodos y algoritmos utilizados para extraer patrones e insights a partir de grandes conjuntos de datos.
(English) Data Mining: Concepts and Techniques (The Morgan...
Kindle Edition
$$$
(English) Data Mining: Concepts and Techniques (The Morgan...
Hardcover
$$$
(English) Data Mining: Concepts and Techniques, Second...
Hardcover
$$
(English) Data Mining: Know It All
Hardcover
$$$
Cover image
Automate the Boring Stuff with Python, 3rd Edition
Save
Este libro es una guía práctica para automatizar tareas con Python. Proporciona una base valiosa para los estudiantes que son nuevos en la automatización o desean mejorar sus habilidades, lo que les permite automatizar los procesos repetitivos relacionados con la extracción y el procesamiento de datos.
(English) Automate the Boring Stuff with Python, 3rd Edition
Kindle Edition
$$
Cover image
Data Science for Business
Save
Este libro proporciona una introducción completa a la ciencia de datos desde una perspectiva empresarial. Ofrece una base sólida para comprender los conceptos y técnicas fundamentales de la ciencia de datos, lo que es beneficioso para contextualizar el proyecto y aplicar los insights a escenarios del mundo real.
(English) Data Science for Business: What You Need to Know...
Paperback
$$
(English) Data Science for Business: What You Need to Know...
Kindle Edition
$$
Machine Learning Con Pytorch Y Scikit Lean
Save
Este libro es una guía práctica para el uso de Python para el aprendizaje automático. Aunque no es directamente relevante para el proyecto, proporciona una base valiosa para los estudiantes que estén interesados en explorar más a fondo los algoritmos y técnicas de aprendizaje automático.
Machine Learning con PyTorch y Scikit-Learn:...
Paperback
$$$
Cover image
Statistical Rethinking
Save
Este libro ofrece una introducción al razonamiento bayesiano y su aplicación en el análisis de datos. Aunque no es directamente relevante para el proyecto, proporciona una base valiosa para los estudiantes que estén interesados en explorar más a fondo los métodos bayesianos para el análisis de datos.
Statistical Rethinking
Paperback
Check
Statistical Rethinking
Kindle Edition
Check

Share

Help others find this course page by sharing it with your friends and followers:
Facebook
LinkedIn
Reddit
X
Link
Email

Similar courses

Here are nine courses similar to ETL pipelines con Python: recopila datos de Spotify.
Fundamentals of Data Analytics in the Public Sector with R
Most relevant
App Dev: Adding User Authentication to your Application -...
Most relevant
Processing IoT Hub data streams with Azure Stream...
Most relevant
Using Python to Interact with the Operating System
Most relevant
Configuring your IDE for absolute beginners with AWS...
Most relevant
Software Developer Career Guide and Interview Preparation
Most relevant
Juniper Networks Automation Using Python and PyEZ
Most relevant
Problem Solving Using Computational Thinking
Most relevant
Business Intelligence and Visual Analytics
Most relevant

Coursera Buyer Protection & Guarantee

Verified partner policies & purchase protections

Accredited University Partner
Free Trial & Audit

7-Day Free Trial & Free Audit

7-day free trial on monthly Coursera Plus subscriptions; free audit option available on most individual courses to explore video lectures and readings at no charge.

Return & Refund Policy

14-Day Refund Guarantee

14-day refund window on annual Coursera Plus subscriptions and single-course purchases prior to certificate issuance. Monthly subscriptions do not offer refunds once billed.

Buyer Protections

Verified Academic & Industry Partner

Accredited university and industry certifications (e.g. Stanford, Google, IBM, Yale), secure SSL payment processing, and verifiable digital certificate links.

Key Purchase Protections
14-day refund window on annual Coursera Plus and single courses
7-day free trial on monthly Coursera Plus subscriptions
Free course audit option for lectures and readings
Verified certificates from top universities & companies
OpenCourser Verified Partner Policy details last reviewed: 2026-10-22
Course image
Effort
1 hora, 30 minutos
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Pablo Agustin Martinez
Language
Español
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Se enfoca en el análisis de datos musicales de Spotify, lo cual es de interés particular para los entusiastas de la música
Brinda una visión general del proceso ETL (Extracción, Transformación y Carga) de datos en Python, una habilidad esencial en el análisis de datos
Enseña técnicas de visualización de datos para comunicar los resultados del análisis de forma clara y atractiva
Requiere conocimientos básicos de Python, lo que puede ser una barrera para los principiantes absolutos
Share this
Share to help others discover this course.
Facebook LinkedIn X Reddit Link Email
Begin learning today
Enroll now to gain full access to ETL pipelines con Python.
Enroll now
Save for later
Add this course to your list. Find it anytime.
Save
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser