Network analysis is a long-standing methodology used to understand the relationships between words and actors in the broader networks in which they exist. This course covers network analysis as it pertains to marketing data, specifically text datasets and social networks. Learners walk through a conceptual overview of network analysis and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project.
Este curso forma parte de Programa especializado: Text Marketing Analytics
ofrecido por
Programa especializado: Text Marketing AnalyticsUniversidad de Colorado en BoulderAcerca de este Curso
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Fechas límite flexibles
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Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 3 en
Nivel intermedio
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
Aprox. 10 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
Qué aprenderás
Describe the concept of network analysis and related terminology
Apply network analysis to marketing data via a peer-graded project
Visualize a network based on centrality and other statistics via homework
Extract marketing insights from a network via a peer-graded project
Habilidades que obtendrás
- Python Programming
- Network Analysis
- Text Datasets
- Marketing Analytics
- Social Network
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Curso 3 de 3 en
Nivel intermedio
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
Aprox. 10 horas para completar
Inglés (English)
Subtítulos: Inglés (English)
ofrecido por
Universidad de Colorado en Boulder
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
Comienza a trabajar para obtener tu maestría
Este curso es parte del Master of Science in Data Science completamente en línea de Universidad de Colorado en Boulder.
Si te aceptan en el programa completo, tus cursos cuentan para tu título de grado.
Programa - Qué aprenderás en este curso
1 hora para completar
Network Analysis Introduction and Terminology
In this module, we will learn the key concepts in network analysis and the key terminology, including semantic and social networks. We will also survey common network analyses in marketing.
1 hora para completar
2 videos (Total 32 minutos), 3 lecturas
1 hora para completar
Network Analysis Data Structures and Calculations
In this module, we will learn how networks are prepared and the common data formats that represent networks. We will learn the differences between different network calculations and how networks are presented visually.
1 hora para completar
2 videos (Total 20 minutos), 1 lectura, 1 cuestionario
4 horas para completar
Preparing and Visualizing Social Networks
In this module, we will learn how to parse tweet JSON, extract mentions and text, load connections into edge lists, and visualize the network in Google Colab.
4 horas para completar
1 video (Total 17 minutos), 2 lecturas, 2 cuestionarios
4 horas para completar
Preparing and Visualizing Semantic Networks
In this module, we will learn how to parse tweet JSON, process text into features, load connections into edge lists, and visualize the network in Google Colab.
4 horas para completar
1 video (Total 12 minutos), 2 lecturas, 2 cuestionarios
Acerca de Programa especializado: Text Marketing Analytics
Marketing data are complex and have dimensions that make analysis difficult. Large unstructured datasets are often too big to extract qualitative insights. Marketing datasets also often involve relational and connected and involve networks. This specialization tackles advanced advertising and marketing analytics through three advanced methods aimed at solving these problems: text classification, text topic modeling, and semantic network analysis. Each key area involves a deep dive into the leading computer science methods aimed at solving these methods using Python. This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.
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