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Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender todo lo que necesitas saber acerca de como crear e integrar modelos de autoML en Power BI. No solo aprenderás, de manera practica, a generar y evaluar los modelos. Sino que además aprenderás a integrar y utilizarlos dentro de tus dashboards de Power BI.
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OpenCourser.com/course/3f2d0a/automated
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What's inside
Syllabus
automated Machine Learning en Microsoft Power BI
En este curso se aprenderá a utilizar Pycaret para generar modelos de autoML y a utilizar esos modelos en Power BI
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Dirigido a estudiantes que buscan comprender e implementar el Aprendizaje Automático Automatizado (AutoML) en Power BI
Especialmente beneficioso para aquellos con poca o ninguna experiencia previa en AutoML o Power BI
Proporciona una base sólida en AutoML con Pycaret y su integración con Power BI
Puede requerir conocimientos básicos de Python o programación en general
El uso de Pycaret limita la integración con otros frameworks u herramientas de AutoML
La versión de Power BI utilizada en el curso puede no ser la más reciente
Save this course
Save Automated Machine Learning en Microsoft Power BI to your list so you can find it easily later:
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Reviews summary
Power bi automl - mixed reviews
This course on Automated Machine Learning in Microsoft Power BI has mixed reviews. One reviewer found the explanations to be disorganized while another found the concepts to be explained in a simple and clear manner.
Concepts explained clearly
"...explica muy bien cada concepto de forma simple y muy clara."
Explanations could be disorganized
"La explicación de todos los ejercicios son muy desorganizadas"
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 Automated Machine Learning en Microsoft Power BI with these
activities:
Leer 'Machine Learning para principiantes' de Sebastian Raschka
Show steps
Este libro proporciona una base sólida en los conceptos de ML, preparando a los alumnos para el autoML.
View
Machine Learning con PyTorch y Scikit-Learn
on Amazon
Show steps
-
Leer los capítulos sobre autoML
-
Realizar los ejercicios prácticos
Seguir tutoriales de autoML en el canal de YouTube de Microsoft
Show steps
Los tutoriales de Microsoft proporcionan instrucciones paso a paso para integrar el autoML en Power BI.
Browse courses on
AutoML
Show steps
-
Ver los tutoriales sobre generación e integración de modelos de autoML
-
Seguir los pasos para crear e implementar modelos en sus propios proyectos
Crear un modelo de autoML y utilizarlo en Power BI
Show steps
Este proyecto te permite poner en práctica todo lo aprendido en el curso, creando e integrando un modelo de autoML en Power BI.
Browse courses on
Power BI
Show steps
-
Generar un modelo de autoML utilizando PyCaret
-
Integrar el modelo en Power BI
-
Usar el modelo para mejorar la toma de decisiones
Five other activities
Expand to see all activities and additional details
Show all eight activities
Resolver ejercicios de autoML en Kaggle
Show steps
Kaggle ofrece desafíos prácticos que permiten practicar y mejorar las habilidades de autoML.
Browse courses on
AutoML
Show steps
-
Participar en competiciones de autoML
-
Resolver notebooks de autoML compartidos por la comunidad
Asistir a un taller de autoML organizado por Microsoft
Show steps
Los talleres de Microsoft brindan capacitación práctica y oportunidades para interactuar con expertos en autoML.
Browse courses on
AutoML
Show steps
-
Inscribirse en un taller relevante
-
Asistir al taller y participar activamente
Buscar un mentor con experiencia en autoML en Power BI
Show steps
Un mentor puede proporcionar orientación personalizada y apoyo para acelerar el aprendizaje.
Show steps
-
Identificar posibles mentores a través de redes sociales
-
Contactar a los mentores y programar una reunión
Desarrollar una solución de autoML para un problema empresarial
Show steps
Esta actividad desafiante permite a los alumnos aplicar sus habilidades para resolver problemas del mundo real.
Browse courses on
AutoML
Show steps
-
Identificar un problema empresarial donde el autoML pueda aportar valor
-
Recopilar datos y prepararlos para el modelado
-
Generar e implementar un modelo de autoML en Power BI
-
Evaluar el rendimiento del modelo y realizar ajustes según sea necesario
Contribuir al repositorio de Power BI AutoML en GitHub
Show steps
Contribuir a proyectos de código abierto mejora las habilidades y el conocimiento de la comunidad.
Browse courses on
AutoML
Show steps
-
Identificar problemas o áreas de mejora
-
Fork y clon el repositorio
-
Realizar cambios y enviar una solicitud de extracción
Leer 'Machine Learning para principiantes' de Sebastian Raschka
Show steps
Este libro proporciona una base sólida en los conceptos de ML, preparando a los alumnos para el autoML.
View
Machine Learning con PyTorch y Scikit-Learn
on Amazon
Show steps
Show steps
Show steps
- Leer los capítulos sobre autoML
- Realizar los ejercicios prácticos
Seguir tutoriales de autoML en el canal de YouTube de Microsoft
Show steps
Los tutoriales de Microsoft proporcionan instrucciones paso a paso para integrar el autoML en Power BI.
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Ver los tutoriales sobre generación e integración de modelos de autoML
- Seguir los pasos para crear e implementar modelos en sus propios proyectos
Crear un modelo de autoML y utilizarlo en Power BI
Show steps
Este proyecto te permite poner en práctica todo lo aprendido en el curso, creando e integrando un modelo de autoML en Power BI.
Browse courses on
Power BI
Show steps
Show steps
Show steps
- Generar un modelo de autoML utilizando PyCaret
- Integrar el modelo en Power BI
- Usar el modelo para mejorar la toma de decisiones
Five other activities
Expand to see all activities and additional details
Show all eight activities
Resolver ejercicios de autoML en Kaggle
Show steps
Kaggle ofrece desafíos prácticos que permiten practicar y mejorar las habilidades de autoML.
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Participar en competiciones de autoML
- Resolver notebooks de autoML compartidos por la comunidad
Asistir a un taller de autoML organizado por Microsoft
Show steps
Los talleres de Microsoft brindan capacitación práctica y oportunidades para interactuar con expertos en autoML.
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Inscribirse en un taller relevante
- Asistir al taller y participar activamente
Buscar un mentor con experiencia en autoML en Power BI
Show steps
Un mentor puede proporcionar orientación personalizada y apoyo para acelerar el aprendizaje.
Show steps
Show steps
Show steps
- Identificar posibles mentores a través de redes sociales
- Contactar a los mentores y programar una reunión
Desarrollar una solución de autoML para un problema empresarial
Show steps
Esta actividad desafiante permite a los alumnos aplicar sus habilidades para resolver problemas del mundo real.
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Identificar un problema empresarial donde el autoML pueda aportar valor
- Recopilar datos y prepararlos para el modelado
- Generar e implementar un modelo de autoML en Power BI
- Evaluar el rendimiento del modelo y realizar ajustes según sea necesario
Contribuir al repositorio de Power BI AutoML en GitHub
Show steps
Contribuir a proyectos de código abierto mejora las habilidades y el conocimiento de la comunidad.
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Identificar problemas o áreas de mejora
- Fork y clon el repositorio
- Realizar cambios y enviar una solicitud de extracción
Career center
Learners who complete Automated Machine Learning en Microsoft Power BI will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
A Data Analyst will greatly benefit from understanding the principles and applications of Automated Machine Learning (AutoML), particularly in the context of Microsoft Power BI. By integrating AutoML models into Power BI dashboards, Data Analysts can provide business stakeholders with deeper insights and more accurate predictions. This course provides essential knowledge and skills in Pycaret and Power BI, which are invaluable tools for Data Analysts
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are increasingly leveraging AutoML to automate and streamline their work. This course provides a practical introduction to AutoML using Pycaret and Power BI, allowing Machine Learning Engineers to harness the power of AutoML within a familiar business intelligence tool. By mastering these techniques, Machine Learning Engineers can enhance their skillset and contribute more effectively to data-driven decision-making.
Data Scientist
Data Scientist
Data Scientists can benefit greatly from understanding how to integrate AutoML models into Power BI dashboards. This course offers valuable hands-on experience in using Pycaret and Power BI to build and deploy AutoML models, empowering Data Scientists to deliver more accurate predictions and actionable insights to stakeholders. By mastering these techniques, Data Scientists can strengthen their skillset and excel in their field.
Business Analyst
Business Analyst
Business Analysts can benefit from the ability to use AutoML to generate and evaluate models within Power BI. This course provides a comprehensive introduction to Pycaret and Power BI, allowing Business Analysts to leverage AutoML to gain deeper insights from data and make more informed recommendations to stakeholders. By mastering these techniques, Business Analysts can enhance their analytical abilities and drive data-driven decision-making.
Data Visualization Engineer
Data Visualization Engineer
Data Visualization Engineers can benefit from the ability to incorporate AutoML models into Power BI dashboards. This course provides practical experience in using Pycaret and Power BI to build and deploy AutoML models, enabling Data Visualization Engineers to create more interactive and informative dashboards. By mastering these techniques, Data Visualization Engineers can enhance their skillset and deliver more valuable insights to stakeholders.
Business Intelligence Developer
Business Intelligence Developer
Business Intelligence Developers can benefit from the ability to build and deploy AutoML models within Power BI dashboards. This course provides hands-on experience with Pycaret and Power BI, enabling Business Intelligence Developers to create more interactive and informative dashboards that provide deeper insights to decision-makers. By mastering these techniques, Business Intelligence Developers can enhance their skillset and contribute to the development of data-driven solutions that drive business growth.
Software Engineer
Software Engineer
Software Engineers can benefit from the ability to use AutoML to automate and streamline the development of data-driven applications. This course provides hands-on experience with Pycaret and Power BI, enabling Software Engineers to integrate AutoML models into their applications and deliver more efficient and accurate results. By mastering these techniques, Software Engineers can enhance their skillset and contribute to the development of innovative data-driven solutions
Data Architect
Data Architect
Data Architects can benefit from the ability to design and implement data pipelines that incorporate AutoML models. This course provides practical experience with Pycaret and Power BI, allowing Data Architects to understand how to integrate AutoML models into data pipelines and ensure the integrity and reliability of data-driven insights. By mastering these techniques, Data Architects can enhance their skillset and contribute to the development of robust and scalable data-driven systems.
Statistician
Statistician
Statisticians can benefit from the ability to use AutoML to automate and streamline the analysis of complex data sets. This course provides hands-on experience with Pycaret and Power BI, enabling Statisticians to apply AutoML models to a variety of statistical problems, such as hypothesis testing, regression analysis, and forecasting. By mastering these techniques, Statisticians can enhance their skillset and contribute to the development of data-driven solutions that drive informed decision-making.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts can benefit from the ability to use AutoML to develop and optimize mathematical models for solving complex business problems. This course provides hands-on experience with Pycaret and Power BI, enabling Operations Research Analysts to apply AutoML models to a variety of optimization problems, such as scheduling, routing, and inventory management. By mastering these techniques, Operations Research Analysts can enhance their skillset and contribute to the development of efficient and effective data-driven solutions.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts can benefit from the ability to use AutoML to automate and streamline the development of financial models. This course provides hands-on experience with Pycaret and Power BI, enabling Quantitative Analysts to apply AutoML models to a variety of financial problems, such as risk assessment, portfolio optimization, and trading strategies. By mastering these techniques, Quantitative Analysts can enhance their skillset and contribute to the development of innovative data-driven solutions that drive financial performance.
Data Management Analyst
Data Management Analyst
Data Management Analysts can benefit from the ability to use AutoML to improve the quality and accuracy of data in a data warehouse. This course provides hands-on experience with Pycaret and Power BI, enabling Data Management Analysts to apply AutoML models to detect and correct data errors and inconsistencies. By mastering these techniques, Data Management Analysts can enhance their skillset and contribute to the development of robust and reliable data-driven systems.
Database Administrator
Database Administrator
Database Administrators can benefit from the ability to use AutoML to improve the performance and efficiency of databases. This course provides hands-on experience with Pycaret and Power BI, enabling Database Administrators to apply AutoML models to a variety of database tasks, such as indexing, query optimization, and performance tuning. By mastering these techniques, Database Administrators can enhance their skillset and contribute to the development of high-performance data-driven applications.
System Analyst
System Analyst
System Analysts can benefit from the ability to use AutoML to improve the design and efficiency of business systems. This course provides hands-on experience with Pycaret and Power BI, enabling System Analysts to apply AutoML models to a variety of systems analysis tasks, such as process modeling, requirements gathering, and system evaluation. By mastering these techniques, System Analysts can enhance their skillset and contribute to the development of effective and efficient data-driven systems.
Data Engineer
Data Engineer
Data Engineers can benefit from the ability to use AutoML to automate and streamline the development of data pipelines. This course provides hands-on experience with Pycaret and Power BI, enabling Data Engineers to apply AutoML models to a variety of data engineering tasks, such as data cleaning, transformation, and integration. By mastering these techniques, Data Engineers can enhance their skillset and contribute to the development of robust and efficient data-driven systems.
For more career information including salaries, visit:
OpenCourser.com/course/3f2d0a/automated
Reading list
We've selected seven 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
Automated Machine Learning en Microsoft Power BI.
Este libro proporciona una base sólida en Python para el análisis de datos. Cubre conceptos y técnicas esenciales, como la manipulación de datos, el análisis estadístico y la visualización de datos, que son valiosos para aquellos que desean ampliar sus conocimientos más allá de Power BI.
Este libro es una introducción práctica a la automatización de tareas con Python. Aunque no se centra específicamente en Power BI o el aprendizaje automático, proporciona habilidades valiosas en programación y automatización que pueden mejorar la eficiencia del flujo de trabajo.
Este libro presenta el aprendizaje automático con R. Aunque no cubre Power BI específicamente, proporciona una base sólida en los conceptos y técnicas de aprendizaje automático, lo que es beneficioso para aquellos que buscan ampliar sus conocimientos más allá de la interfaz de usuario de Power BI.
Este libro es un recurso práctico para el aprendizaje automático con bibliotecas de Python como Scikit-Learn, Keras y TensorFlow. Cubre una amplia gama de técnicas y algoritmos, lo que proporciona una comprensión más profunda del funcionamiento interno de los modelos de aprendizaje automático.
Este libro se centra en el aprendizaje profundo con Python. Aunque no es directamente relevante para el aprendizaje automático automatizado en Power BI, proporciona una visión general de los conceptos y algoritmos de aprendizaje profundo, lo que amplía los conocimientos de los estudiantes interesados en explorar técnicas más avanzadas.
Este libro es un texto clásico sobre el aprendizaje por refuerzo. Aunque no está relacionado directamente con el curso, proporciona una base teórica para aquellos que buscan comprender los principios fundamentales del aprendizaje por refuerzo.
Este libro presenta los modelos gráficos probabilísticos, que son una herramienta poderosa para representar y razonar sobre datos complejos. Aunque no es directamente relevante para el curso, proporciona una base teórica para aquellos que buscan profundizar en los aspectos estadísticos del aprendizaje automático.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3f2d0a/automated
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Effort
2 horas
Level
Intermediate
Via
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Institution
Coursera Project Network
Instructor
Leire Ahedo
Language
Español
Good to know
Dirigido a estudiantes que buscan comprender e implementar el Aprendizaje Automático Automatizado (AutoML) en Power BI
Especialmente beneficioso para aquellos con poca o ninguna experiencia previa en AutoML o Power BI
Proporciona una base sólida en AutoML con Pycaret y su integración con Power BI
Puede requerir conocimientos básicos de Python o programación en general
El uso de Pycaret limita la integración con otros frameworks u herramientas de AutoML
La versión de Power BI utilizada en el curso puede no ser la más reciente
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