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Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender a generar modelos de Machine Learning en un entorno de Big Data con PySpark en proyectos sanitarios.
Read more
Este proyecto es un curso práctico y efectivo para aprender a generar modelos de Machine Learning en un entorno de Big Data con PySpark en proyectos sanitarios.
Read more
Este proyecto es un curso práctico y efectivo para aprender a generar modelos de Machine Learning en un entorno de Big Data con PySpark en proyectos sanitarios.
Te enseñaremos desde cero las bases de PySpark hasta las funciones más complejas. Y finalmente acabarás desarrollando un modelo completo y avanzado con Spark en Jupyter Notebooks.
Register for this course and see more details by visiting:
OpenCourser.com/course/whwp4s/machine
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What's inside
Syllabus
Machine Learning con Pyspark aplicado al campo sanitario
En este curso se aprenderá a generar modelos de Machine Learning con Spark (MLlib) del sector de salud
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Dirigido a profesionales sanitarios interesados en aplicar Machine Learning en el ámbito de la salud
Desarrolla modelos de Machine Learning avanzados con Spark en Jupyter Notebooks
Basado en el framework PySpark, ampliamente utilizado en la industria
Impartido por expertos en Machine Learning y análisis de datos en el sector sanitario
Requiere conocimientos previos en programación y Machine Learning
El curso no está actualizado con las últimas versiones de software
Save this course
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Reviews summary
Well-received health-care machine learning course
This course on Machine Learning with PySpark for health-care applications is well-received. Students appreciate the focus on practical applications and hands-on learning with Spark in Jupyter Notebooks. The course covers everything from the basics to advanced functions of PySpark. Overall, students recommend this course for those interested in health-sector Machine Learning.
Hands-on learning with Jupyter Notebooks
"...acabaras desarrollando un modelo completo y avanzado con Spark en Jupyter Notebooks..."
Covers both basics and advanced concepts
"...Te enseñaremos desde cero las bases de PySpark hasta las funciones más complejas..."
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 Machine Learning con Pyspark aplicado al campo sanitario with these
activities:
Revisar conceptos de Machine Learning
Show steps
Repasar los conceptos básicos de Machine Learning te ayudará a comprender mejor las técnicas y algoritmos que aprenderás en este curso.
Browse courses on
Machine Learning
Show steps
-
Leer artículos o libros introductorios sobre Machine Learning
-
Completar ejercicios o tutoriales online sobre algoritmos de Machine Learning
Practicar ejercicios de programación con Spark
Show steps
La práctica regular de programación en Spark te permitirá desarrollar fluidez y confianza en el uso de esta herramienta para el procesamiento de Big Data.
Browse courses on
Apache Spark
Show steps
-
Resolver problemas de programación con Spark en sitios web como LeetCode o HackerRank
-
Participar en desafíos de programación organizados por la comunidad de Spark
Crear una presentación o documento técnico sobre una aplicación avanzada de Spark en el sector sanitario
Show steps
Crear una presentación o documento técnico te permitirá sintetizar y compartir tus conocimientos sobre una aplicación avanzada de Spark en el sector sanitario.
Show steps
-
Investigar y recopilar información sobre una aplicación avanzada de Spark en el sector sanitario
-
Diseñar la presentación o documento técnico con una estructura clara y concisa
-
Presentar los resultados y conclusiones de manera efectiva
One other activity
Expand to see all activities and additional details
Show all four activities
Contribuir a proyectos de código abierto relacionados con Spark
Show steps
Participar en proyectos de código abierto relacionados con Spark te permitirá profundizar tus conocimientos y colaborar con la comunidad.
Browse courses on
Apache Spark
Show steps
-
Identificar proyectos de código abierto relacionados con Spark en plataformas como GitHub
-
Estudiar el código fuente y comprender su arquitectura
-
Contribuir con mejoras o nuevas funcionalidades al proyecto
Revisar conceptos de Machine Learning
Show steps
Repasar los conceptos básicos de Machine Learning te ayudará a comprender mejor las técnicas y algoritmos que aprenderás en este curso.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Leer artículos o libros introductorios sobre Machine Learning
- Completar ejercicios o tutoriales online sobre algoritmos de Machine Learning
Practicar ejercicios de programación con Spark
Show steps
La práctica regular de programación en Spark te permitirá desarrollar fluidez y confianza en el uso de esta herramienta para el procesamiento de Big Data.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Resolver problemas de programación con Spark en sitios web como LeetCode o HackerRank
- Participar en desafíos de programación organizados por la comunidad de Spark
Crear una presentación o documento técnico sobre una aplicación avanzada de Spark en el sector sanitario
Show steps
Crear una presentación o documento técnico te permitirá sintetizar y compartir tus conocimientos sobre una aplicación avanzada de Spark en el sector sanitario.
Show steps
Show steps
Show steps
- Investigar y recopilar información sobre una aplicación avanzada de Spark en el sector sanitario
- Diseñar la presentación o documento técnico con una estructura clara y concisa
- Presentar los resultados y conclusiones de manera efectiva
One other activity
Expand to see all activities and additional details
Show all four activities
Contribuir a proyectos de código abierto relacionados con Spark
Show steps
Participar en proyectos de código abierto relacionados con Spark te permitirá profundizar tus conocimientos y colaborar con la comunidad.
Browse courses on
Apache Spark
Show steps
Show steps
Show steps
- Identificar proyectos de código abierto relacionados con Spark en plataformas como GitHub
- Estudiar el código fuente y comprender su arquitectura
- Contribuir con mejoras o nuevas funcionalidades al proyecto
Career center
Learners who complete Machine Learning con Pyspark aplicado al campo sanitario will develop knowledge and skills
that may be useful to these careers:
Clinical Data Analyst
Clinical Data Analyst
Clinical data analysts use data to help improve the quality and efficiency of clinical care. They may use their knowledge of clinical data and analytics techniques to identify trends and patterns in data. This course may be helpful to a Clinical Data Analyst because it will help build a foundation in using PySpark in a big data setting.
Health Data Analyst
Health Data Analyst
Health data analysts use data to help improve the quality and efficiency of healthcare. They may use their knowledge of healthcare data and analytics techniques to identify trends and patterns in data. This course may be helpful to a Health Data Analyst because it will help build a foundation in using PySpark in a big data setting.
Health Informatics Specialist
Health Informatics Specialist
Health informatics specialists use data to improve the quality and efficiency of healthcare. They may use their knowledge of health informatics tools and techniques to identify trends and patterns in data. This course may be helpful to a Health Informatics Specialist because it will help build a foundation in using PySpark in a big data setting.
Data Engineer
Data Engineer
Data engineers build and maintain data pipelines that collect, clean, and store data. They may use their knowledge of data engineering tools and techniques to solve problems for businesses and organizations. This course may be helpful to a Data Engineer because it will help build a foundation in using PySpark in a big data setting.
Epidemiologist
Epidemiologist
Epidemiologists study the distribution and determinants of health-related states and events in specified populations. They may use their knowledge of epidemiology and biostatistics to identify trends and patterns in data. This course may be helpful to an Epidemiologist because it will help build a foundation in using PySpark in a big data setting.
Biostatistician
Biostatistician
Biostatisticians use statistical methods to solve problems in the life sciences. They may use their knowledge of biostatistics and data analysis to identify trends and patterns in data. This course may be helpful to a Biostatistician because it will help build a foundation in using PySpark in a big data setting.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning systems. They use their knowledge of machine learning algorithms and data science to solve problems for businesses. This course may be helpful to a Machine Learning Engineer because it will help build a foundation in using PySpark in a big data setting.
Medical Researcher
Medical Researcher
Medical researchers conduct research to improve the prevention, diagnosis, and treatment of diseases. They may use their knowledge of medicine and research methods to identify trends and patterns in data. This course may be helpful to a Medical Researcher because it will help build a foundation in using PySpark in a big data setting.
Data Scientist
Data Scientist
Data scientists work on teams to gather and analyze data to solve business problems. They may use their scientific knowledge to develop new methods for data processing, analysis, and modeling. This course may be helpful to a Data Scientist because it will help build a foundation in using PySpark in a big data setting.
Healthcare Consultant
Healthcare Consultant
Healthcare consultants advise healthcare providers on how to improve the quality and efficiency of care. They may use their knowledge of healthcare and business to identify trends and patterns in data. This course may be helpful to a Healthcare Consultant because it will help build a foundation in using PySpark in a big data setting.
Statistician
Statistician
Statisticians use mathematical and statistical methods to collect, analyze, and interpret data. They may use their knowledge of statistics to solve problems for businesses and organizations. This course may be helpful to a Statistician because it will help build a foundation in using PySpark in a big data setting.
Data Analyst
Data Analyst
Data analysts collect, clean, and analyze data to help businesses make informed decisions. They may use their statistical and programming skills to uncover trends and patterns in data. This course may be helpful to a Data Analyst because it will help build a foundation in using PySpark in a big data setting.
Business Intelligence Analyst
Business Intelligence Analyst
Business intelligence analysts use data to help businesses make better decisions. They may use their knowledge of business intelligence tools and techniques to identify trends and patterns in data. This course may be helpful to a Business Intelligence Analyst because it will help build a foundation in using PySpark in a big data setting.
Database Administrator
Database Administrator
Database administrators maintain and optimize databases. They may use their knowledge of database management systems to solve problems for businesses and organizations. This course may be helpful to a Database Administrator because it will help build a foundation in using PySpark in a big data setting.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software systems. They may use their knowledge of programming languages and software engineering principles to solve problems for businesses and organizations. This course may be helpful to a Software Engineer because it will help build a foundation in using PySpark in a big data setting.
For more career information including salaries, visit:
OpenCourser.com/course/whwp4s/machine
Reading list
We've selected six 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
Machine Learning con Pyspark aplicado al campo sanitario.
Este libro proporciona una introducción completa a Machine Learning con Apache Spark, cubriendo temas fundamentales como el procesamiento de datos, la selección de características y la evaluación de modelos.
Si bien este libro tiene un alcance más amplio que el Machine Learning, proporciona una visión general completa de la Inteligencia Artificial en el cuidado de la salud, lo que lo convierte en un recurso valioso para comprender las tendencias y aplicaciones emergentes.
Provides a comprehensive overview of Spark, it covers topics such as dataframes, transformations, and actions.
Este libro proporciona una base sólida en el pensamiento estadístico, que es esencial para comprender y aplicar Machine Learning en entornos de investigación clínica.
Una guía para principiantes que proporciona una introducción completa a Machine Learning con Python, lo que lo convierte en un recurso útil para aquellos que buscan una base sólida en el campo.
Este libro ofrece un enfoque práctico para Machine Learning utilizando bibliotecas populares como Scikit-Learn, Keras y TensorFlow, lo que lo convierte en un recurso valioso para aquellos interesados en implementaciones prácticas.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/whwp4s/machine
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Effort
2 horas
Level
Advanced
Via
Coursera
Institution
Coursera Project Network
Instructor
Leire Ahedo
Language
Español
Good to know
Dirigido a profesionales sanitarios interesados en aplicar Machine Learning en el ámbito de la salud
Desarrolla modelos de Machine Learning avanzados con Spark en Jupyter Notebooks
Basado en el framework PySpark, ampliamente utilizado en la industria
Impartido por expertos en Machine Learning y análisis de datos en el sector sanitario
Requiere conocimientos previos en programación y Machine Learning
El curso no está actualizado con las últimas versiones de software
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