Acerca de este Curso

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Resultados profesionales del estudiante

29%

comenzó una nueva carrera después de completar estos cursos

30%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

10%

consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Aprox. 6 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Japonés

Qué aprenderás

  • Differentiate between various types of data pulls

  • Describe the basic data analysis iteration

  • Explore datasets to determine if data is appropriate for a project

  • Use statistical findings to create convincing data analysis presentations

Habilidades que obtendrás

Data AnalysisCommunicationInterpretationExploratory Data Analysis

Resultados profesionales del estudiante

29%

comenzó una nueva carrera después de completar estos cursos

30%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

10%

consiguió un aumento de sueldo o ascenso
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Aprox. 6 horas para completar
Inglés (English)
Subtítulos: Inglés (English), Japonés

ofrecido por

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Universidad Johns Hopkins

Programa - Qué aprenderás en este curso

Calificación del contenidoThumbs Up95%(6,395 calificaciones)Info
Semana
1

Semana 1

6 horas para completar

Managing Data Analysis

6 horas para completar
19 videos (Total 144 minutos), 17 lecturas, 7 cuestionarios
19 videos
Data Analysis Iteration8m
Stages of Data Analysis1m
Six Types of Questions6m
Characteristics of a Good Question6m
Exploratory Data Analysis Goals & Expectations11m
Using Statistical Models to Explore Your Data (Part 1)13m
Using Statistical Models to Explore Your Data (Part 2)5m
Exploratory Data Analysis: When to Stop6m
Making Inferences from Data: Introduction5m
Populations Come in Many Forms4m
Inference: What Can Go Wrong7m
General Framework8m
Associational Analyses10m
Prediction Analyses10m
Inference vs. Prediction12m
Interpreting Your Results10m
Routine Communication in Data Analysis6m
Making a Data Analysis Presentation5m
17 lecturas
Pre-Course Survey10m
Course Textbook: The Art of Data Science10m
Conversations on Data Science10m
Data Science as Art10m
Epicycles of Analysis10m
Six Types of Questions10m
Characteristics of a Good Question10m
EDA Check List10m
Assessing a Distribution10m
Assessing Linear Relationships10m
Exploratory Data Analysis: When Do We Stop?10m
Factors Affecting the Quality of Inference10m
A Note on Populations10m
Inference vs. Prediction10m
Interpreting Your Results10m
Routine Communication10m
Post-Course Survey10m
7 ejercicios de práctica
Data Analysis Iteration10m
Stating and Refining the Question16m
Exploratory Data Analysis10m
Inference10m
Formal Modeling, Inference vs. Prediction10m
Interpretation10m
Communication10m

Revisiones

Principales revisiones sobre MANAGING DATA ANALYSIS

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