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.
Ce cours fait partie de la Spécialisation Text Marketing Analytics
Offert par
Spécialisation Text Marketing AnalyticsUniversité du Colorado à BoulderÀ propos de ce cours
2 565 consultations récentes
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 3 dans le
Niveau intermédiaire
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
Approx. 10 heures pour terminer
Anglais
Sous-titres : Anglais
Ce que vous allez apprendre
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
Compétences que vous acquerrez
- Python Programming
- Network Analysis
- Text Datasets
- Marketing Analytics
- Social Network
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 3 sur 3 dans le
Niveau intermédiaire
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
Approx. 10 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Université du Colorado à 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.
Commencez à travailler pour obtenir votre master
Ce cours fait partie du diplôme intégralement en ligne Master of Science in Data Science de Université du Colorado à Boulder.
Si vous êtes admis(e) au programme complet, vos cours sont pris en compte dans votre apprentissage diplômant.
Programme de cours : ce que vous apprendrez dans ce cours
1 heure pour terminer
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 heure pour terminer
2 vidéos (Total 32 min), 3 lectures
1 heure pour terminer
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 heure pour terminer
2 vidéos (Total 20 min), 1 lecture, 1 quiz
4 heures pour terminer
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 heures pour terminer
1 vidéo (Total 17 min), 2 lectures, 2 quiz
4 heures pour terminer
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 heures pour terminer
1 vidéo (Total 12 min), 2 lectures, 2 quiz
À propos du Spécialisation 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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