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Juan Pablo Yepes

En este proyecto guiado obtendrás experiencia práctica trabajando con la librería Pandas y creando tu propio cuaderno de Jupyter Lab. Los conocimientos básicos que obtengas te permitirán trabajar con cualquier base de datos para analizar la información. Al final de este proyecto serás capaz de crear tus propios cuadernos con análisis estadísticos de diferentes bases de datos.

Nota: Este curso está dirigido a personas que buscan iniciarse en el mundo de la ciencia de datos o el machine learning.

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What's inside

Syllabus

Análisis exploratorio de datos con Python y Pandas
En este proyecto guiado obtendrás experiencia práctica en el análisis exploratorio de datos usando diferentes librerías con la librerías como Numpy y Pandas para crear tu propio cuaderno de Jupyter Lab. Los conocimientos básicos que obtengas te permitirán trabajar con cualquier base de datos para analizar la información. Al final de este proyecto serás capaz de crear tus propios cuadernos con análisis estadísticos de diferentes set de datos.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Dirigido a personas que buscan iniciarse en el mundo de la ciencia de datos o el machine learning
Proporciona experiencia práctica en el análisis exploratorio de datos utilizando librerías como Numpy y Pandas
Permite crear cuadernos propios con análisis estadísticos de diferentes bases de datos
Recurre a un enfoque práctico con un proyecto guiado

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Reviews summary

Practical pandas project

The course is simple but well-explained and offers an excellent practice environment using Pandas and Jupyter Notebooks.
Offers a very practical experience.
"Excelente práctica"
Simple but well-explained course.
"El curso es sencillo pero bien explicado"

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 Análisis exploratorio de datos con Python y Pandas with these activities:
Asiste a un encuentro local o virtual sobre ciencia de datos o análisis de datos
Conecta con otros profesionales y amplía tus conocimientos asistiendo a eventos relacionados con el campo.
Show steps
  • Busca eventos en plataformas de redes sociales o sitios web específicos de la industria
  • Asiste al evento y participa en discusiones o sesiones de preguntas y respuestas
  • Conecta con otras personas que compartan tus intereses en ciencia de datos o análisis de datos
Participa en un hackathon o competición de análisis de datos
Pon a prueba tus habilidades en un entorno competitivo y obtén comentarios de expertos participando en un hackathon o competición de análisis de datos.
Show steps
  • Busca hackathons o competiciones de análisis de datos en línea o en tu área local
  • Forma un equipo o participa individualmente
  • Trabaja en un proyecto de análisis de datos dentro del plazo especificado
  • Presenta tu solución y recibe comentarios de los jueces
Contribuye a un proyecto de código abierto relacionado con Pandas o análisis de datos
Participa en la comunidad de código abierto y profundiza tu comprensión de Pandas contribuyendo a proyectos relevantes.
Browse courses on Pandas
Show steps
  • Busca proyectos de código abierto relacionados con Pandas o análisis de datos en plataformas como GitHub
  • Identifica un área en la que puedes contribuir y envía una solicitud de extracción
  • Colabora con los mantenedores del proyecto para mejorar el código o agregar nuevas funciones
Show all three activities

Career center

Learners who complete Análisis exploratorio de datos con Python y Pandas will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst takes raw data and transforms it into formats that can be easily interpreted and understood, usually through the use of dashboards and visualizations. This course on exploratory data analysis with Python and Pandas can help you become more proficient in working with data and uncovering insights from it, which is a core part of being a successful Data Analyst.
Data Scientist
Data Scientists are responsible for developing and implementing data-driven solutions to business problems. This course on exploratory data analysis with Python and Pandas can help build a foundation in working with data, which is essential for success in this role.
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models to solve business problems. This course on exploratory data analysis with Python and Pandas can help build a foundation in working with data, as well as an understanding of how to prepare data for machine learning models.
Market Researcher
Market Researchers conduct research to understand consumer behavior and trends. This course on exploratory data analysis with Python and Pandas can help develop skills in data analysis and interpretation, which are essential for this role.
Business Analyst
Business Analysts use data to identify and solve business problems. This course on exploratory data analysis with Python and Pandas can provide foundational skills in data analysis, allowing you to gather, clean, and interpret data to make recommendations for business improvements.
Statistician
Statisticians collect, analyze, interpret, and present data. This course on exploratory data analysis with Python and Pandas can help provide foundational skills in data analysis and statistics, preparing you for success in this field.
Data Engineer
Data Engineers design and build systems to store, process, and analyze data. This course on exploratory data analysis with Python and Pandas can provide foundational skills in data handling and analysis, preparing you for success in this field.
Financial Analyst
Financial Analysts use data to make recommendations on investments and financial decisions. This course on exploratory data analysis with Python and Pandas can help build a foundation in financial data analysis, a critical skill for this role.
Auditor
Auditors examine financial records to ensure accuracy and compliance. This course on exploratory data analysis with Python and Pandas may be useful for developing skills in data analysis and identifying anomalies, which can be helpful in this role.
Operations Analyst
Operations Analysts use data to identify inefficiencies and improve business processes. This course on exploratory data analysis with Python and Pandas provides foundational knowledge in data analysis, which can be useful for this role.
Actuary
Actuaries assess risk and uncertainty to develop financial plans. This course on exploratory data analysis with Python and Pandas may be useful for understanding data analysis concepts, which can be helpful in this role.
Systems Analyst
Systems Analysts design and implement computer systems to meet business needs. This course on exploratory data analysis with Python and Pandas may provide some helpful skills in data analysis, which can be useful for understanding user needs and requirements.
User Experience Researcher
User Experience Researchers conduct research to understand how users interact with products and services. This course on exploratory data analysis with Python and Pandas may provide helpful skills in data analysis and interpretation, which can be useful in this role.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course on exploratory data analysis with Python and Pandas may provide helpful skills in data analysis and problem-solving, which can be useful in this role.
Project Manager
Project Managers plan and execute projects to achieve specific goals. This course on exploratory data analysis with Python and Pandas may provide helpful skills in data analysis and problem-solving, which can be useful in this role.

Reading list

We've selected nine 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 Análisis exploratorio de datos con Python y Pandas.
Este libro es una guía práctica para usar Python para el análisis de datos. Cubre temas como la instalación y configuración de Python, la manipulación y limpieza de datos, el análisis exploratorio de datos y la visualización.
Provides a comprehensive introduction to machine learning with Python. It covers topics such as data preprocessing, model selection, model evaluation, and deployment.
Provides a comprehensive introduction to deep learning with Python. It covers topics such as neural networks, convolutional neural networks, recurrent neural networks, and deep learning models.
Provides a comprehensive introduction to data science for business. It covers topics such as data collection, data cleaning, data analysis, and data visualization.
Provides a comprehensive introduction to natural language processing with Python. It covers topics such as text processing, natural language understanding, and natural language generation.

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