Trabalho de conclusão de Ciência de Dados Aplicada (Coursera)

Offered by IBM,
Trabalho de conclusão de Ciência de Dados Aplicada (Coursera)

Este curso do projeto de conclusão mostrará um pouco do que os cientistas de dados passam na vida real ao trabalhar com dados. Você aprenderá sobre dados de localização e diferentes provedores de dados de localização, como o Foursquare. Você aprenderá como fazer chamadas de API RESTful para a API do Foursquare a fim de recuperar dados sobre locais em diferentes bairros do mundo. Você também aprenderá como usar a criatividade quando os dados não estiverem disponíveis na hora, coletando dados da Web e analisando o código HTML.

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

Você utilizará Python e sua biblioteca do Pandas para manipular dados, o que ajudará você a refinar suas habilidades para explorar e analisar dados.
Por fim, você deverá usar a biblioteca Folium para obter excelentes mapas de dados geoespaciais e para comunicar seus resultados e descobertas.
Se optar por fazer este curso e obter o certificado de conclusão de curso do Coursera, você também poderá ganhar um selo digital da IBM.

Syllabus

WEEK 1
Introdução
Neste módulo, você aprenderá sobre o escopo deste curso de conclusão e o contexto do projeto em que estará trabalhando. Você aprenderá sobre diferentes provedores de dados de localização e o que geralmente compõe esses dados. Por fim, será necessário enviar um link para um novo repositório em sua conta do Github dedicado a este curso.

WEEK 2
API do Foursquare
Neste módulo, você aprenderá em detalhes sobre o Foursquare, que é o provedor de dados de localização que usaremos neste curso, e sua API. Basicamente, você aprenderá como criar uma conta de desenvolvedor do Foursquare e como usar suas credenciais para pesquisar locais próximos de um tipo específico, explorar um local específico e pesquisar locais populares em uma localização.

WEEK 3
Segmentação e clustering de bairros
Neste módulo, você aprenderá sobre cluster k-means, que é uma forma de aprendizado não supervisionado. Em seguida, você usará o clustering e a API do Foursquare para segmentar e agrupar os bairros na cidade de Nova York. Além disso, você aprenderá como extrair dados de sites e analisar código HTML usando o pacote Python Beautifulsoup, e converter dados em um dataframe do Pandas.

WEEK 4
A Batalha dos Bairros
Neste módulo, você começará a trabalhar no projeto de conclusão. Você definirá um problema com clareza e discutirá os dados que usará para resolvê-lo.

WEEK 5
A Batalha dos Bairros (continuação)
Neste módulo, você executará todo o trabalho restante para terminar o seu projeto de conclusão. Você enviará um relatório do seu projeto para uma avaliação de um colega.

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

Related Courses

Statistics and Data Analysis with Excel, Part 1 (Coursera) Coursera
University of Colorado Boulder

Statistics and Data Analysis with Excel, Part 1 (Coursera)

Designed for students with no prior statistics knowledge, this course will provide a foundation for further study in data science, data analytics, or machine learning. Topics include descriptive statistics, probability, and discrete and continuous probability distributions. Assignments are conducted in Microsoft Excel (Windows or Mac versions). Designed to be taken with the follow-up course, “Statistics and Data Analysis with Excel, Part 2.”

Sep 28th 2026
5-12 Weeks
Big Data Analysis Deep Dive (Coursera) Coursera
Alibaba Cloud Academy

Big Data Analysis Deep Dive (Coursera)

The job market for architects, engineers, and analytics professionals with Big Data expertise continues to increase. The Academy’s Big Data Career path focuses on the fundamental tools and techniques needed to pursue a career in Big Data. This course includes: data processing with python, writing and reading SQL queries, transmitting data with MaxCompute, analyzing data with Quick BI, using Hive, Hadoop, and spark on E-MapReduce, and how to visualize data with data dashboards. Work through our course material, learn different aspects of the Big Data field, and get certified as a Big Data Professional!

Sep 28th 2026
5-12 Weeks
Ethical Issues in Data Science (Coursera) Coursera
University of Colorado Boulder

Ethical Issues in Data Science (Coursera)

Computing applications involving large amounts of data – the domain of data science – impact the lives of most people in the U.S. and the world. These impacts include recommendations made to us by internet-based systems, information that is available about us online, techniques that are used for security and surveillance, data that is used in health care, and many more. In many cases, they are affected by techniques in artificial intelligence and machine learning.

Sep 28th 2026
5-12 Weeks
Machine Translation (Coursera) Coursera
Karlsruhe Institute of Technology - KIT

Machine Translation (Coursera)

Welcome to the CLICS-Machine Translation MOOC. This MOOC explains the basic principles of machine translation. Machine translation is the task of translating from one natural language to another natural language. Therefore, these algorithms can help people communicate in different languages. Such algorithms are used in common applications, from Google Translate to apps on your mobile device.

Sep 28th 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.

Sep 28th 2026
4 Weeks
Learn CSS Variables (Coursera) Coursera
Scrimba

Learn CSS Variables (Coursera)

CSS Custom Properties represent a significant advancement for front-end developers, introducing the concept of variables to CSS. This innovation substantially reduces redundancy, enhances code legibility, and augments overall flexibility. Notably, CSS Variables distinguish themselves from their CSS preprocessor counterparts by seamlessly integrating into the Document Object Model (DOM), offering a plethora of advantages.

Sep 28th 2026
1 Week
HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Administrative/IT Perspective) (Coursera) Coursera
Columbia University

HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Administrative/IT Perspective) (Coursera)

HI-FIVE (Health Informatics For Innovation, Value & Enrichment) Training is an approximately 10-hour online course designed by Columbia University in 2016, with sponsorship from the Office of the National Coordinator for Health Information Technology (ONC). The training is role-based and uses case scenarios. No additional hardware or software are required for this course. Our nation’s healthcare system is changing at a rapid pace.

Sep 28th 2026
4 Weeks
Analyzing and Visualizing Data in Looker (Coursera) Coursera
Google Cloud

Analyzing and Visualizing Data in Looker (Coursera)

In this course, you learn how to do the kind of data exploration and analysis in Looker that would formerly be done primarily by SQL developers or analysts. Upon completion of this course, you will be able to leverage Looker's modern analytics platform to find and explore relevant content in your organization’s Looker instance, ask questions of your data, create new metrics as needed, and build and share visualizations and dashboards to facilitate data-driven decision making.

Sep 28th 2026
2 Weeks
Empathy, Data, and Risk (Coursera) Coursera
University of Illinois at Urbana-Champaign

Empathy, Data, and Risk (Coursera)

Risk Management and Innovation develops your ability to conduct empathy-driven and data-driven analysis in the domain of risk management. This course introduces empathy as a professional competency. It explains the psychological processes that inhibit empathy-building and the processes that determine how organizational stakeholders respond to risk.

Sep 28th 2026
4 Weeks
Business Intelligence and Competitive Analysis (Coursera) Coursera
Rutgers University

Business Intelligence and Competitive Analysis (Coursera)

By the end of 2019, it is clear that American Airlines (AAL), the world’s largest airline group, is in trouble. With the growth rate of its stock price ranked at the bottom of all major US airlines and going in the opposite direction from the SP500 index, AAL needs to find out what is going on, and how to turn the company and its stock price around.

Sep 28th 2026
4 Weeks
Data Visualization with Python & R for Engineers (Coursera) Coursera
Northeastern University

Data Visualization with Python & R for Engineers (Coursera)

The primary objective of this course is to offer students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. This course covers basics of data mining and visualization, and Python. It also introduces students to static visualization charts and techniques that reveal information, patterns, interactions.

Sep 28th 2026
4 Weeks
Population Health: Predictive Analytics (Coursera) Coursera
Leiden University

Population Health: Predictive Analytics (Coursera)

Predictive analytics has a longstanding tradition in medicine. Developing better prediction models is a critical step in the pursuit of improved health care: we need these tools to guide our decision-making on preventive measures, and individualized treatments. In order to effectively use and develop these models, we must understand them better. In this course, you will learn how to make accurate prediction tools, and how to assess their validity. First, we will discuss the role of predictive analytics for prevention, diagnosis, and effectiveness. Then, we look at key concepts such as study design, sample size and overfitting.

Sep 28th 2026
4 Weeks