Big Data: capstone project (Coursera)

Big Data: capstone project (Coursera)

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.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

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.
Course 5 of 5 in the Big Data – Introducción al uso práctico de datos masivos Specialization.

Syllabus

WEEK 1
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
Exploración de datos
En esta semana vamos a conocer el proyecto y a hacer una primera exploración de algunos de los datos con los que iremos trabajando. Nos familiarizamos con el contenido de estos ficheros y haremos el trabajo preliminar para poderlo luego aplicar a grandes volumenes de datos.

WEEK 2
Modelo de Datos
En esta semana aprenderemos a cargar los datos en Hive, construir su modelo de datos y entender la tarea de clasificar una galaxia según su forma.

WEEK 3
Clasificación
Esta semana vamos a normalizar un modelo de datos, estudiaremos con profundidad los votos que nos han proporcionado los usuarios y generaremos la información necesaria para construir un clasificador automàtico.

WEEK 4
Machine Learning
Esta semana introduciremos el dataset de imágenes galácticas y prepararemos dos algoritmos de Inteligencia Artificial para la clasificación automática de galaxias a partir de una imagen.

WEEK 5
Trabajo Final
Es el momento de preparar el informe final con el trabajo realizado hasta ahora. Necesitaréis tener a mano los trabajos realizados las semanas anteriores.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Foundations of Data Science: K-Means Clustering in Python (Coursera) Coursera
University of London,Goldsmiths, University of London

Foundations of Data Science: K-Means Clustering in Python (Coursera)

This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Science courses. It focuses on the basic mathematics, statistics and programming skills that are necessary for typical data analysis tasks.

Nov 30th 2026
5-12 Weeks
Machine Learning Algorithms (Coursera) Coursera
Sungkyunkwan University - SKKU

Machine Learning Algorithms (Coursera)

In this course you will: understand the naïve Bayesian algorithm; understand the Support Vector Machine algorithm; understand the Decision Tree algorithm; understand the Clustering. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Nov 23rd 2026
4 Weeks
Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera) Coursera
Icahn School of Medicine at Mount Sinai

Big Data Science with the BD2K-LINCS Data Coordination and Integration Center (Coursera)

In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is served as RESTful APIs. Most importantly, the course covers computational methods including: data clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizen-science projects where students can work together in teams to extract expression signatures from public databases and then query such collections of signatures against LINCS data for predicting small molecules as potential therapeutics.

Nov 16th 2026
5-12 Weeks
Machine Learning (Coursera) Coursera
Stanford University

Machine Learning (Coursera)

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Nov 16th 2026
5-12 Weeks
Getting Started with Machine Learning at the Edge on Arm (Coursera) Coursera
Arm

Getting Started with Machine Learning at the Edge on Arm (Coursera)

The age of machine learning has arrived! Arm technology is powering a new generation of connected devices with sophisticated sensors that can collect a vast range of environmental, spatial and audio/visual data. Typically this data is processed in the cloud using advanced machine learning tools that are enabling new applications reshaping the way we work, travel, live and play.

Nov 23rd 2026
5-12 Weeks
Preparing for the Google Cloud Professional Data Engineer Exam em Português Brasileiro (Coursera) Coursera
Google Cloud

Preparing for the Google Cloud Professional Data Engineer Exam em Português Brasileiro (Coursera)

Por que fazer o curso: "A melhor forma de se preparar para o exame é ser competente nas habilidades necessárias ao trabalho." Este curso usa uma abordagem "top-down". Ele identifica as habilidades que você já tem e apresenta novas informações e áreas para ampliar seus conhecimentos. Use este curso para criar seu plano de preparação personalizado. Ele ajudará você a identificar o que sabe e o que precisa estudar mais, além de desenvolver e praticar as habilidades necessárias às competências do cargo.

Nov 23rd 2026
1 Week
Probabilistic Graphical Models 3: Learning (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 3: Learning (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Nov 23rd 2026
5-12 Weeks
New Technologies for Business Leaders (Coursera) Coursera
Rutgers University

New Technologies for Business Leaders (Coursera)

This introductory course is developed for high-level business people (and those on their way) who want a broad understanding of new Information Technologies and understand their potential for business functions (e.g. marketing, supply change management, finance). This is not a course for people looking for guidance on how to become a deep technical expert or implement these technologies.

Nov 23rd 2026
5-12 Weeks
Remote Sensing Image Acquisition, Analysis and Applications (Coursera) Coursera
UNSW Sydney - University of New South Wales

Remote Sensing Image Acquisition, Analysis and Applications (Coursera)

Welcome to Remote Sensing Image Acquisition, Analysis and Applications, in which we explore the nature of imaging the earth's surface from space or from airborne vehicles. This course covers the fundamental nature of remote sensing and the platforms and sensor types used. It also provides an in-depth treatment of the computational algorithms employed in image understanding, ranging from the earliest historically important techniques to more recent approaches based on deep learning.

Nov 30th 2026
13-24 Weeks
Introdução ao Big Data (Coursera) Coursera
FIA Business School

Introdução ao Big Data (Coursera)

Este curso é indicado para profissionais que desejam entender de forma fácil o que é Big Data, conhecer algumas tecnologias de Big Data, ter acesso a algumas aplicações de Analytics, Internet das Coisas - IOT e de Big Data. Ao final do curso você será capaz de participar de um projeto de Big Data contribuindo com estratégias e direcionando o projeto para a escolha da adequada técnica de análise de dados.

Nov 30th 2026
4 Weeks
Preparing for the Google Cloud Professional Data Engineer Exam en Español (Coursera) Coursera
Google Cloud

Preparing for the Google Cloud Professional Data Engineer Exam en Español (Coursera)

En este curso, se emplea un enfoque descendente a fin de identificar las habilidades y los conocimientos adquiridos, así como poner en evidencia la información y las áreas de habilidades que requieren una preparación adicional. Puede aprovechar este curso para crear su propio plan de preparación personalizado. Lo ayudará a distinguir lo que sabe de lo que no. Además, le permitirá desarrollar y practicar las habilidades que se les exigen a los profesionales que realizan este trabajo.

Nov 30th 2026
1 Week