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Big Data

capstone project

Francesc Torradeflot, Nadia Tonello, Pau Tallada, and Jorge Carretero

En este último curso de la Especialización Big Data el estudiante tendrá la oportunidad de aplicar algunas de las herramientas y métodos aprendidos en los cursos anteriores en un caso práctico.

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En este último curso de la Especialización Big Data el estudiante tendrá la oportunidad de aplicar algunas de las herramientas y métodos aprendidos en los cursos anteriores en un caso práctico.

El objetivo de este Capstone Project es mostrar un ejemplo del trabajo que se realiza diariamente en el departamento de Cosmología del Port d’Informació Científica, en Barcelona. Se trata de crear un clasificador para imágenes de galaxias, a partir de datos del proyecto GalaxyZoo e imágenes y datos del telescopio Sloan Digital Sky Survey. Los trabajos y ejercicios guiados llevarán al estudiante a la exploración y analisis de estos datos, hasta realizar una herramienta automática de Machine Learning.

El proceso seguido por los estudiantes en este curso se podría aplicar en cualquier otra disciplina, por ejemplo en las ciencias sociales, en un estudio de mercado o en cualquier ámbito que comporte toma de decisiones a partir de un gran volumen de datos.

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What's inside

Syllabus

INTRODUCCIÓN
LA MÁQUINA VIRTUAL
ATENCIÓN: Si ya te instalaste la máquina virtual en el curso anterior de la Especialización no es necesario que vuelvas a hacerlo. En caso contrario, en este apartado te explicamos cómo descargar e instalar dicha máquina virtual en tu ordenador.

La MV-Cloudera requiere disponer de un equipo con las siguientes características: (1) máquina de 64 bits, (2) mínimo 6G de memoria (recomendable 8G), y (3) 20G disponibles en disco.

Ten en cuenta que bajar e instalar la máquina virtual te llevará tiempo dado el tamaño y complejidad de la misma
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
El curso ofrece una aplicación práctica de herramientas y métodos aprendidos en cursos anteriores
Proporciona un ejemplo del trabajo diario en el departamento de Cosmología del Port d'Informació Científica
Desarrolla habilidades de exploración de datos, modelo de datos, clasificación y aprendizaje automático
Utiliza datos del proyecto GalaxyZoo y del telescopio Sloan Digital Sky Survey
El proceso seguido es aplicable en diversas disciplinas, como las ciencias sociales y los estudios de mercado

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Reviews summary

Proyecto capstone útil con retos de vm

Los estudiantes comentan que este proyecto capstone es muy interesante y bien guiado (positive), ayudando a consolidar conocimientos (positive) de la especialización Big Data y a poner en práctica lo aprendido (positive) en cursos anteriores. Sin embargo, un punto recurrente y principal de frustración es la instalación y el uso de la máquina virtual Cloudera (negative), que ha causado bastantes problemas (negative) a muchos, llegando incluso a impedir completar el curso a algunos (negative). La experiencia con el soporte y los foros (warning) parece mixta. En general, es un curso valioso si ya has cursado la especialización (neutral).
Diseñado como culminación de la especialización.
"ayuda a consolidar conocimientos de la especialización"
"permite poner en práctica los conocimientos aprendidos en los cursos anteriores"
"Es un curso que vale la pena si has hecho la especialización."
El proyecto capstone es valioso y bien diseñado.
"Un proyecto muy interesante y bien guiado que ayuda a consolidar conocimientos de la especialización."
"Excelente proyecto, realmente permite poner en práctica los conocimientos aprendidos en los cursos anteriores y consolidar los conceptos."
"El proyecto es genial, me hizo repasar todo lo aprendido de las 4 partes anteriores y me ayudo a consolidar el conocimiento."
"Buen curso... El proyecto es interesante."
Un revisor sugiere que el material está obsoleto.
"El material del curso parece desactualizado"
La ayuda en foros y el soporte es inconsistente.
"Los compañeros del foro son muy activos y ayudan mucho."
"la ayuda en los foros es escasa"
"no hay soporte efectivo."
La instalación y uso de la VM presenta dificultades.
"Muchos problemas con la máquina virtual."
"No he podido instalar la máquina virtual. Sin ella, no se puede hacer el curso."
"La máquina virtual me dio bastantes problemas al principio, pero al final funcionó."
"La máquina virtual da algún problema, pero nada insalvable."
"El único inconveniente es la máquina virtual, pero se solventa con un poco de esfuerzo."
"la máquina virtual es un incordio."

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 Big Data: capstone project with these activities:
Refresher course on Cloud Computing
By refreshing your knowledge on Cloud Computing, you will solidify your understanding of the fundamental concepts necessary to succeed in this course.
Browse courses on Cloud Computing
Show steps
  • Review the fundamental concepts of Cloud Computing, such as its architecture, types of cloud services, and deployment models.
  • Explore the services and resources offered by the major cloud providers.
  • Create a simple cloud computing environment and experiment with different cloud services.
Read "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" by Aurélien Géron
This book provides a comprehensive overview of machine learning and deep learning techniques and will help you to build a strong foundation in these areas.
View Aprende Machine Learning con Scikit-Learn,... on Amazon
Show steps
  • Read the book from cover to cover.
  • Work through the exercises at the end of each chapter.
  • Implement the techniques that you learn in your own projects.
Tutorial on using the Apache Spark framework
Apache Spark is a powerful tool for data processing, and this tutorial will give you hands-on experience using it. This will enhance your understanding of the concepts covered in the course.
Browse courses on Apache Spark
Show steps
  • Follow the Apache Spark tutorial on their official website.
  • Create a simple Spark application to perform data analysis tasks.
  • Explore the different Spark libraries and modules.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Mentor other students in the course
Mentoring others is a great way to reinforce your own knowledge and to help others succeed in the course.
Show steps
  • Identify a student who is struggling and offer your help.
  • Meet with the student regularly to provide guidance and support.
  • Review the student's work and provide feedback.
  • Encourage the student to ask questions and seek help when needed.
Practice exercises on data modeling and machine learning algorithms
Practice is key to mastering data modeling and machine learning algorithms. These exercises will provide you with the opportunity to apply your knowledge and solidify your understanding.
Browse courses on Data Modeling
Show steps
  • Complete the practice exercises at the end of each module in the course.
  • Find additional practice exercises online or in textbooks.
  • Participate in online forums or discussion groups to discuss your solutions and learn from others.
  • Use a tool like Kaggle to participate in data science competitions.
Create a portfolio of data science projects
Creating a portfolio of data science projects will showcase your skills and knowledge to potential employers or clients. It will also help you to reflect on your progress and identify areas for improvement.
Browse courses on Data Science Projects
Show steps
  • Identify a data science problem that you are interested in solving.
  • Collect and prepare the necessary data.
  • Build and evaluate a machine learning model.
  • Create a presentation or report that summarizes your findings.
  • Add the project to your portfolio and share it with others.
Create a data science blog or podcast
Creating a data science blog or podcast is a great way to share your knowledge with others and establish yourself as an expert in the field.
Show steps
  • Choose a topic for your blog or podcast that you are passionate about.
  • Create high-quality content that is informative and engaging.
  • Promote your blog or podcast on social media and other channels.
  • Network with other data scientists and collaborate on content.

Career center

Learners who complete Big Data: capstone project will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists seek to discover actionable insights from data. This course will help build the foundation for a Data Scientist, as they will gain familiarity and hands-on experience in data exploration, model construction, and machine learning.
See salaries and explore the career path for Data Scientist
Machine Learning Engineer
Machine Learning Engineers oversee the development, deployment, and maintenance of ML models. This course will help build foundational skills as a Machine Learning Engineer, as they will gain experience in processing real-world datasets, creating and optimizing models, and evaluating and interpreting model performance.
See salaries and explore the career path for Machine Learning Engineer
Data Analyst
Data Analysts translate data into actionable insights for businesses. This course will help build the foundation for a Data Analyst, as they will gain experience in data exploration, data visualization, and statistical analysis.
See salaries and explore the career path for Data Analyst
Software Engineer
Software Engineers design, develop, test, and maintain software systems. This course may be helpful for Software Engineers who want to build their expertise in big data technologies, such as Hadoop and Spark.
See salaries and explore the career path for Software Engineer
Data Architect
Data Architects design and build data architectures that meet the needs of an organization. This course may be helpful for Data Architects who want to gain experience in designing and implementing big data solutions.
See salaries and explore the career path for Data Architect
Database Administrator
Database Administrators are responsible for the management and maintenance of databases. This course may be helpful for Database Administrators who want to gain experience in managing and maintaining big data systems.
See salaries and explore the career path for Database Administrator
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. This course may be helpful for Business Intelligence Analysts who want to gain experience in using big data to solve business problems.
See salaries and explore the career path for Business Intelligence Analyst
Statistician
Statisticians collect, analyze, and interpret data. This course may be helpful for Statisticians who want to gain experience in using big data to solve statistical problems.
See salaries and explore the career path for Statistician
Operations Research Analyst
Operations Research Analysts use mathematical models to solve business problems. This course may be helpful for Operations Research Analysts who want to gain experience in using big data to solve operations research problems.
See salaries and explore the career path for Operations Research Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to assess risk and make investment decisions. This course may be helpful for Quantitative Analysts who want to gain experience in using big data to solve financial problems.
See salaries and explore the career path for Quantitative Analyst
Actuary
Actuaries use mathematical and statistical models to assess risk and make insurance decisions. This course may be helpful for Actuaries who want to gain experience in using big data to solve insurance problems.
See salaries and explore the career path for Actuary
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior. This course may be helpful for Market Researchers who want to gain experience in using big data to solve marketing problems.
See salaries and explore the career path for Market Researcher
Epidemiologist
Epidemiologists investigate the causes and distribution of diseases. This course may be helpful for Epidemiologists who want to gain experience in using big data to solve public health problems.
See salaries and explore the career path for Epidemiologist
Astronomer
Astronomers study the universe and its contents. This course may be helpful for Astronomers who want to gain experience in using big data to solve astrophysics problems.
See salaries and explore the career path for Astronomer
Chemist
Chemists study the composition and properties of matter. This course may be helpful for Chemists who want to gain experience in using big data to solve chemistry problems.
See salaries and explore the career path for Chemist

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 Big Data: capstone project.
Cover image
Mining of Massive Data Sets
Save
Este libro se centra en los algoritmos y técnicas para el procesamiento y análisis de conjuntos de datos masivos. Proporciona una base sólida en los métodos computacionales utilizados para extraer información de grandes cantidades de datos.
(English) Mining of Massive Datasets
Hardcover
$$$
Cover image
Deep Learning
Save
Este libro es una referencia completa sobre el aprendizaje profundo, que cubre una amplia gama de temas, desde los fundamentos hasta las aplicaciones avanzadas. Proporciona información en profundidad sobre los algoritmos y técnicas esenciales para el aprendizaje automático.
(English) Deep Learning
Paperback
$$$
(English) Deep Learning (Adaptive Computation and Machine...
Hardcover
$$$
(English) Deep Learning (Adaptive Computation and Machine...
Kindle Edition
$$$
Cover image
Principles of Database Management
Save
Este libro proporciona una guía práctica para el análisis de macrodatos, cubriendo temas como la preparación de datos, el análisis exploratorio y el modelado predictivo. Es una valiosa referencia para los estudiantes que buscan desarrollar habilidades prácticas en el procesamiento y análisis de macrodatos.
(English) Principles of Database Management: The Practical...
Hardcover
$$$
(English) Principles of Database Management: The Practical...
Kindle Edition
$$$
Data Mining
Save
Este libro es una referencia clásica sobre minería de datos, que cubre una amplia gama de técnicas y algoritmos para el análisis de datos. Proporciona una base sólida en los fundamentos y aplicaciones de la minería 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
Foundations of Machine Learning, second edition
Save
Esta obra proporciona una base matemática sólida para el aprendizaje automático, cubriendo conceptos como la teoría de la probabilidad, la optimización y el análisis estadístico. Es una lectura valiosa para los estudiantes que buscan una comprensión más profunda de los fundamentos teóricos del aprendizaje automático.
Foundations of Machine Learning, second edition
Paperback
Check
Foundations of Machine Learning, second edition
Kindle Edition
Check
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Esta obra proporciona una guía práctica para utilizar bibliotecas populares de aprendizaje automático, como Scikit-Learn, Keras y TensorFlow. Es una valiosa referencia para los estudiantes que buscan desarrollar habilidades prácticas en la implementación de algoritmos de aprendizaje automático.
(English) Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
(English) Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
(English) Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Data Science for Business
Save
Esta obra es un recurso valioso para aprender sobre las aplicaciones práticas de la ciencia de datos en el ámbito empresarial. Proporciona una comprensión sólida de los procesos y técnicas involucrados en el análisis de datos y la toma de decisiones basada en datos.
(English) Data Science for Business: What You Need to Know...
Paperback
$$
(English) Data Science for Business: What You Need to Know...
Kindle Edition
$$
Cover image
Python for Data Analysis
Save
Esta obra proporciona una guía práctica para utilizar la biblioteca Pandas en Python para el análisis y la manipulación de datos. Es una valiosa referencia para los estudiantes que buscan desarrollar habilidades prácticas en el procesamiento y análisis de datos.
(English) Python for Data Analysis: Data Wrangling with...
Paperback
$$
(English) Python for Data Analysis
Kindle Edition
$$
(English) Python for Data Analysis: Data Wrangling with...
Paperback
$$$
Cover image
Machine Learning in Action
Save
Este libro se centra en la implementación práctica del aprendizaje automático utilizando Python. Proporciona ejemplos y ejercicios prácticos que ayudan a los estudiantes a aplicar los conceptos de aprendizaje automático a proyectos del mundo real.
(English) Machine Learning in Action
Paperback
$$
(中文) 机器学习实战 (图灵程序设计丛书 72) (Chinese Edition)
Kindle Edition
$
Cover image
Probabilistic Machine Learning
Save
Esta obra ofrece un enfoque probabilístico del aprendizaje automático, cubriendo temas como modelos gráficos, métodos bayesianos y teoría de la información. Es una lectura valiosa para los estudiantes interesados en comprender los fundamentos teóricos del aprendizaje automático.
(English) Probabilistic Machine Learning: Advanced Topics...
Hardcover
$$$$
Cover image
Big Data
Save
Este libro proporciona una visión general completa de los desafíos y oportunidades de los macrodatos, y ayuda a comprender el impacto de los macrodatos en varios aspectos de nuestras vidas y sociedades.
(English) Big Data: A Revolution That Will Transform How We...
Kindle Edition
$$
(English) Learning With Big Data (Kindle Single): The Future...
Kindle Edition
$
(Italiano) Big data. Una rivoluzione che trasformerà il nostro...
Hardcover
$$
Big data: La revolución de los datos masivos...
Kindle Edition
$$
(Deutsch) Lernen mit Big Data: Die Zukunft der Bildung
Paperback
$$
(Deutsch) Big Data: Die Revolution, die unser Leben verändern...
Hardcover
$$
Aprender con big data
Paperback
$$
Learning with Big Data: The Future of...
Hardcover
$$

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Course image
Effort
12 hours to complete
Level
Advanced
Via
Coursera
Institution
Universitat Autònoma de Barcelona
Instructors
Francesc Torradeflot
Nadia Tonello
Pau Tallada
Jorge Carretero
Language
Español
This course belongs to a collection called Big Data – Introducción al uso práctico de datos masivos . It's comprised of five courses:
  1. Big Data: capstone project (viewing)
  2. Big Data: el impacto de los datos masivos en la sociedad actual
  3. Big Data: visualización de datos
  4. Big Data: procesamiento y análisis
  5. Big Data: adquisición y almacenamiento de datos
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
El curso ofrece una aplicación práctica de herramientas y métodos aprendidos en cursos anteriores
Proporciona un ejemplo del trabajo diario en el departamento de Cosmología del Port d'Informació Científica
Desarrolla habilidades de exploración de datos, modelo de datos, clasificación y aprendizaje automático
Utiliza datos del proyecto GalaxyZoo y del telescopio Sloan Digital Sky Survey
El proceso seguido es aplicable en diversas disciplinas, como las ciencias sociales y los estudios de mercado
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