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via Udemy |
Go to Course: https://www.udemy.com/course/analisis-de-datos-con-python-desde-excel/
Certainly! Here's a detailed review and recommendation for the Coursera course based on the provided information: --- **Course Review: Data Analysis with Python integrated into Excel** This innovative course on Coursera offers a comprehensive introduction to data analysis by combining two powerful tools: Python and Excel. As data analysis becomes an increasingly vital skill in the modern workplace, this course equips learners with the necessary techniques to leverage both platforms effectively. **Course Content & Learning Outcomes:** The course is designed to guide students through a wide range of data analysis tasks, starting with integrating Python into Excel. Learners will: - Learn how to invoke Python scripts directly from Excel, enabling seamless workflows. - Develop foundational skills in Python, including creating variables, understanding data types, casting variables, and using mathematical and logical operators. - Manipulate datasets using Pandas, creating DataFrames, Series, and performing functions like count(), std(), head(), sum(), nunique(), agg(), and groupby(). - Generate and customize various types of charts such as bar, box, KDE, line, area, hexbin, pie, histograms, and scatter plots, using Pandas and matplotlib. - Utilize advanced data handling functions such as loc[], get(), map(), and create pivot tables. - Handle string data and perform string-based analyses for comprehensive data insights. - Apply numerical functions and create arrays using NumPy for numerical computations. - Import data from various sources including Access databases, CSV, XML, and Excel files. **Strengths:** - The course covers both programming and visual representation, ensuring learners can analyze and present data effectively. - It emphasizes practical skills with real-time applications, providing downloadable files for hands-on practice. - The integration of Python into Excel makes it highly relevant for analysts who frequently work with spreadsheets. - The inclusion of data import/export skills broadens the scope for applying these techniques to diverse datasets. **Prerequisites & Target Audience:** - Basic knowledge of Excel and mathematics is required, making it suitable for data analysts, students, and professionals looking to enhance their data analysis capabilities. - The course is ideal for those working in roles related to data analysis, project management, or anyone interested in expanding their technical skills in data processing. **Rating & Recommendations:** Considering the comprehensive content, practical focus, and relevance to current data analysis trends, I highly recommend this course for professionals and students who want to deepen their understanding of data analysis within Excel using Python. It is especially valuable for those who prefer a blended approach of spreadsheet familiarity with programming power. **Final Verdict:** If you're looking to modernize your data analysis toolkit, gain proficiency in Python within the familiar environment of Excel, and learn how to visualize data effectively, this course is an excellent choice. It bridges the gap between beginner and intermediate skills, preparing you for real-world data analysis tasks. --- Let me know if you'd like a condensed summary or assistance in enrolling!
Una de las tendencias en el mundo del trabajo es el análisis de datos. Python, uno de los lenguajes más populares, ha sido integrado en Excel, la poderosa herramienta actual, tiene en su ecosistema las librerías para realizarlo. Los objetivos de este curso son, el alumno:Aprenderá a llamar a Python desde Excel, creará variables y tipos de datos, casteo de variables, operadores matemáticos, lógicos, de asignación y varManipulará los datos con Pandas, creará un DataFrame, métodos count(), std(), head(), creará series, iloc[], sum(), nunique(), agg(), groupby(), renomCreará gráficos desde Python con Padas, como gráficas de barra, de caja, kde, de líneas, áreas, hexbin, pie, histogramas y gráficas de dispersión (scaUtilizará las fuciones de gregado, loc[], get(), map() creará una tabla pivote, búsqueda de cadenas y el manejo de las cadenas para el análisis de datAplicará las funciones numéricas y de manejo y creación de arreglos por medio de la librería Numpy.Aprenderá la librería matplotlib para la creación de gráficas y gráficas enfocadas en el análisis de datos.Aprenderá a crear gráficas para el análisis de datos o estadísticas, así como lel cambio estético de las mismas.Aprenderá a importar archivos de datos de la base de datos Acces, de archivos en formato CSV, XML y Excel.Por ejemplo: Definición de las funciones y responsabilidades de un gestor de proyectos.Para este curso necesitas: Conocimientos generales de Excel (y Excel)Conocimientos generales de matemáticas.Este curso está dirigido a analistas de datos usando Python desde Excel. En todo momento contarás con los archivos de trabajo del mismo.