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Alex Aklson
Este curso de proyecto final le dará una idea de lo que atraviesan los científicos de datos en la vida real cuando trabajan con datos. Aprenderá sobre datos de ubicación y diferentes proveedores de datos de ubicación, como Foursquare. Aprenderá cómo realizar...
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Este curso de proyecto final le dará una idea de lo que atraviesan los científicos de datos en la vida real cuando trabajan con datos. Aprenderá sobre datos de ubicación y diferentes proveedores de datos de ubicación, como Foursquare. Aprenderá cómo realizar llamadas de API RESTful a la API de Foursquare para recuperar datos sobre lugares en diferentes vecindarios de todo el mundo. También aprenderá a ser creativo en situaciones en las que los datos no están disponibles fácilmente al extraer datos web y analizar el código HTML. Utilizará Python y su biblioteca de pandas para manipular datos, lo que lo ayudará a refinar sus habilidades para explorar y analizar datos. Finalmente, se le pedirá que utilice la biblioteca Folium para obtener excelentes mapas de datos geoespaciales y para comunicar sus resultados y hallazgos. Si elige tomar este curso y obtener el certificado del curso de Coursera, también obtendrá una insignia digital de IBM al completar con éxito el curso. OFERTA POR TIEMPO LIMITADO: La suscripción cuesta solo $ 39 USD por mes para acceder a materiales calificados y un certificado.
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Builds a strong foundation in location data manipulation, a key skill for data scientists
Uses Python and its pandas library for data manipulation, adding to the learner's skillset
Teaches how to make API calls to Foursquare for real-world data, a relevant skill for many industries
Demonstrates how to extract data from web pages, a valuable skill for data scientists
Emphasizes the use of Folium for creating geospatial maps, an important tool for data visualization
Requires a paid subscription, which may pose a barrier for some learners

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Reviews summary

Hands-on capstone course in data science

This course is a hands-on capstone course in data science that provides a practical understanding of the work of data scientists. It covers topics such as location data, RESTful API calls, data manipulation with Python and pandas, and data visualization with Folium. The course is highly practical, with students working on a project that involves using various data science techniques. The course is challenging, but students appreciate the support they receive from their peers and the opportunity to learn from others' experiences. Overall, this course is a valuable learning experience for those interested in pursuing a career in data science.
Supportive community of learners.
"El apoyo de los compañeros en el foro ha sido muy importante."
Challenging but rewarding.
"Muy bueno, fue dificil pero muy satisfactorio."
Hands-on, project-based learning.
"Aprenderá sobre datos de ubicación y diferentes proveedores de datos de ubicación, como Foursquare."
"Utilizará Python y su biblioteca de pandas para manipular datos, lo que lo ayudará a refinar sus habilidades para explorar y analizar datos."
API utilizada está desactualizada.
"La API que hacen usar no funciona con la nueva versión."
"pudimos realizar el proyecto con ella lo cual me reto a buscar a mi mismo solucionar y llegar a conclusiones con el cambio."

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 Ciencia de Datos Aplicada - Curso Capstone with these activities:
Review spatial data basics
Review the basics of spatial data to ensure a strong foundation for the course.
Browse courses on Location Data
Show steps
  • Read through introductory materials on spatial data concepts and terminology.
  • Complete online tutorials or exercises on spatial data basics.
  • Review examples of spatial data and their applications.
Follow Foursquare API tutorials
Gain hands-on experience with the Foursquare API to prepare for the course.
Browse courses on Foursquare API
Show steps
  • Find and follow online tutorials or documentation on using the Foursquare API.
  • Complete practice exercises or projects that involve making API calls to Foursquare.
Practice data manipulation with Pandas
Strengthen your data manipulation skills with Pandas to enhance your ability to work with data in the course.
Browse courses on Pandas
Show steps
  • Complete coding exercises or challenges that involve data manipulation using Pandas.
  • Work on personal projects or datasets that require data manipulation with Pandas.
Four other activities
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Show all seven activities
Mentor junior data scientists or students
Reinforce your knowledge and skills by mentoring others in geospatial data analysis.
Browse courses on Mentoring
Show steps
  • Volunteer or connect with organizations that provide mentoring opportunities in data science.
  • Provide guidance and support to junior data scientists or students on geospatial analysis techniques and projects.
Create interactive maps with Folium
Develop your ability to create interactive maps and visualizations using Folium, which will be highly relevant to the course.
Browse courses on Folium
Show steps
  • Explore the Folium library and its features.
  • Create practice maps or visualizations using Folium.
  • Work on a project that involves creating interactive maps with Folium.
Write a blog post on geospatial analysis techniques
Deepen your understanding of geospatial analysis techniques and enhance your communication skills by writing a blog post.
Browse courses on Geospatial Analysis
Show steps
  • Research and learn about geospatial analysis techniques.
  • Write a blog post that explains a specific geospatial analysis technique or application.
Contribute to open-source geospatial projects
Gain practical experience in geospatial data analysis and contribute to the open-source community.
Browse courses on Open Source
Show steps
  • Identify open-source geospatial projects that align with your interests.
  • Find ways to contribute to these projects, such as bug reporting, documentation writing, or code contributions.

Career center

Learners who complete Ciencia de Datos Aplicada - Curso Capstone will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists use a variety of statistical techniques and machine learning algorithms to extract insights from data. This course will help you get started in your journey toward becoming a Data Scientist by providing you with the foundational skills in data analysis and manipulation. You will also become familiar with using Python to work with data on the web and how to use the Folium library to map data. While this course will provide you with a strong foundation for working as a Data Scientist, additional education or experience may be needed for this career.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make investment decisions. Many Quantitative Analysts work in the financial industry. This course will help you develop the skills you need to get started in your career as a Quantitative Analyst. You will learn how to use Python to collect and clean data, and you will also learn how to use the pandas library to analyze data. While this course will provide you with a strong foundation for working as a Quantitative Analyst, additional education or experience will likely be needed.
Business Analyst
Business Analysts use data analysis to help businesses make better decisions. This course will provide you with the skills you need to become a Business Analyst, including data collection, analysis, and visualization. You will learn how to use Python to collect and clean data, and you will also learn how to use the Folium library to create maps that can be used to communicate your findings. While this course will give you a strong foundation for a career as a Business Analyst, additional education or experience may be needed.
Market Researcher
Market Researchers are responsible for gathering and interpreting data that can be used to make informed marketing decisions. This course will help you learn about data collection and analysis techniques that you can use in your role as a Market Researcher. You will become proficient in using Python for web scraping and working with APIs to gather data, and you will also learn how to analyze data using the pandas library. This course will give you the skills you need to get started in your career as a Market Researcher.
Data Analyst
Data Analysts typically work in a variety of settings and they are responsible for ensuring data quality and presenting the data in a way that is accessible to decision-makers. This course can provide you with the skills that Data Analysts use to collect, clean, and analyze data. Using the programming language Python, you will become familiar with techniques such as web scraping and working with APIs. While this course will provide you with a broad introduction to data analysis, additional education or experience will likely be needed to work as a Data Analyst.
Data Engineer
Data Engineers are responsible for designing, building, and maintaining the infrastructure that is used to store and process data. This course may be useful for those interested in becoming Data Engineers. You will learn how to use Python and the pandas library to transform and manipulate data. You will also learn about data visualization techniques that can be used to communicate your findings. While this course will provide you with a broad introduction to data engineering, additional education or experience will likely be needed to work as a Data Engineer.
Epidemiologist
Epidemiologists investigate the causes of disease and other health problems in populations. This course may be useful for those interested in becoming Epidemiologists. You will learn about data collection and analysis techniques that can be used to investigate the causes of disease. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as an Epidemiologist.
UX Researcher
UX Researchers are responsible for conducting research to improve the user experience of websites and other products. This course may be useful for those interested in becoming UX Researchers. You will learn about data collection and analysis techniques that can be used to understand user behavior. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a UX Researcher.
Researcher
Researchers conduct original research to advance knowledge in a particular field. This course may be useful for those interested in becoming Researchers who will work with data. You will learn about data collection and analysis techniques that can be used to conduct research. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a Researcher.
Data Journalist
Data Journalists use data to tell stories and inform the public. This course may be useful for those interested in becoming Data Journalists. You will learn about data collection and analysis techniques that can be used to tell compelling stories. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a Data Journalist.
Statistician
Statisticians collect, analyze, and interpret data to help make informed decisions. This course may be useful for those interested in becoming Statisticians. You will learn about data collection and analysis techniques that can be used to make informed decisions. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a Statistician.
Software Engineer
Software Engineers design, build, and maintain software systems. This course may be useful for those interested in becoming Software Engineers who will work with data. You will learn how to use Python to work with data on the web and how to use the Folium library to map data. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a Software Engineer.
Financial Analyst
Financial Analysts use data to make investment decisions. This course may be useful for those interested in becoming Financial Analysts. You will learn about data collection and analysis techniques that can be used to make informed investment decisions. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a Financial Analyst.
Product Manager
Product Managers are responsible for the development and launch of new products. This course may be useful for those interested in becoming Product Managers who will work on data-driven products. You will learn about data collection and analysis techniques that can be used to make informed product decisions. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a Product Manager.
Consultant
Consultants provide advice and guidance to organizations on a variety of topics. This course may be useful for those interested in becoming Consultants who will work with data. You will learn about data collection and analysis techniques that can be used to provide informed advice. While this course will provide you with a basic introduction to data analysis, additional education or experience will likely be needed to work as a Consultant.

Reading list

We've selected ten 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 Ciencia de Datos Aplicada - Curso Capstone.
Provides a comprehensive overview of Python for data analysis, covering topics such as data manipulation, visualization, and machine learning.
A comprehensive guide to data mining techniques, covering a wide range of topics from data preprocessing to model evaluation.
A comprehensive overview of deep learning, covering a wide range of topics from convolutional neural networks to recurrent neural networks.
A comprehensive guide to geospatial analysis, covering a wide range of topics from spatial data acquisition to spatial decision making.

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