El objetivo del curso es lograr que los estudiantes apliquen los principios b谩sicos, las caracter铆sticas de la Anal铆tica y ciencias de datos as铆 como las etapas en el proceso de desarrollo de un proyecto de an谩lisis de datos. Los estudiantes tambi茅n se familiarizar谩n con el preprocesamiento de datos y ser谩n capaces de manejar a, nivel pr谩ctico, las principales t茅cnicas componentes de este, como el an谩lisis de faltantes, la detecci贸n de outliers, las t茅cnicas de normalizaci贸n, discretizaci贸n y reducci贸n dimensional.
Anal铆tica y ciencia de datos para negocios
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Anal铆tica y ciencia de datos para negocios
Instructor: Eduardo Carbajal L贸pez
5,820 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.2
(62 reviews)
Beginner level
No prior experience required
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Aplicaci贸n de principios b谩sicos y caracter铆sticas de la Anal铆tica y Ciencias de Datos en el desarrollo de proyectos de an谩lisis de datos.
Manejo de t茅cnicas de preprocesamiento de datos, como detecci贸n de outliers y normalizaci贸n.
Skills you'll gain
- R (Software)
- Business Analysis
- Big Data
- Data Processing
- Project Management Life Cycle
- Data Transformation
- Software Installation
- Business Analytics
- R Programming
- Data Analysis
- Analytics
- Data Quality
- Data Science
- Exploratory Data Analysis
- Data Cleansing
- Dimensionality Reduction
- Supervised Learning
- Anomaly Detection
- Statistical Programming
- Databases
Details to know
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Assessments
21 assignments
Taught in Spanish
See how employees at top companies are mastering in-demand skills
There are 5 modules in this course
Esta secci贸n presenta los conceptos esenciales para poder desarrollar el curso con 茅xito. Te invitamos a revisarlo todas las veces que lo consideres necesario.
What's included
24 videos1 reading5 assignments
En este m贸dulo, presentar茅 las principales t茅cnicas de business analytics, a partir de una revisi贸n general del universo de t茅cnicas de anal铆tica de datos y cu谩les son la s m谩s com煤nmente usadas en los modelos de anal铆tica aplicados en negocios.
What's included
20 videos2 readings4 assignments
En este M贸dulo se desarrolla el preprocesamiento de datos que corresponde a la etapa m谩s compleja y de mayor duraci贸n de tiempo dentro de un proyecto de anal铆tica de negocios. En particular, abordaremos todo lo referente al problema de los datos faltantes y las opciones de tratamiento frente a dicho problema.
What's included
19 videos2 readings6 assignments
En este m贸dulo, continuaremos aprendiendo sobre la etapa del preprocesamiento, pero ahora nos enfocaremos en la detecci贸n y el tratamiento de los valores at铆picos o extremos, llamados tambi茅n outliers.
What's included
13 videos2 readings3 assignments
En este 煤ltimo m贸dulo se continuar谩 explicando la etapa del preprocesamiento, pero ahora nos enfocaremos en las t茅cnicas de transformaci贸n y la reducci贸n dimensional de datos.
What's included
23 videos3 readings3 assignments
Instructor
Instructor ratings
4.4 (17 ratings)Offered by
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EA
5
Reviewed on Feb 25, 2024
Sumamente valioso este curso para los que comenzamos en R, muchas gracias por compartirlo.
HL
5
Reviewed on Jun 7, 2024
Estupendo curso y super recomendado para entender las diferentes t茅cnicas de an谩lisis en R
AS
5
Reviewed on May 28, 2024
un curso muy completo para el analisis de datos, aprendes una buena aplicaci贸n de R para datos faltantes
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