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 are relational and connected. 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.
Monthly Subscription Starting at AED 99 + VAT
- Level Foundation
- المدة
- الطبع بواسطة University of Colorado Boulder
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Offered by
عن
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 are relational and connected. 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.Auto Summary
"Text Marketing Analytics" is a dynamic course offered through Coursera, focusing on advanced advertising and marketing analytics within the realm of Data Science & AI. The course is designed to tackle the complexities of marketing data, which often come in large, unstructured, and relational forms, making qualitative analysis challenging. Learners will delve into three sophisticated methods to address these issues: text classification, text topic modeling, and semantic network analysis. Each area emphasizes the application of leading computer science techniques using Python, providing hands-on experience and practical skills. The course is part of CU Boulder’s Master of Science in Data Science (MS-DS) degree, which is available on Coursera. This interdisciplinary degree features faculty from diverse departments such as Applied Mathematics, Computer Science, and Information Science. With a performance-based admission process and no application requirements, the MS-DS program is accessible to individuals from various educational and professional backgrounds in fields like computer science, information science, mathematics, and statistics. Although the course does not have a specified duration, it offers flexible subscription options, including a Starter plan, making it an ideal foundational course for aspiring data scientists and marketing professionals looking to enhance their analytical skills. For more information about the MS-DS program, visit [CU Boulder’s MS-DS on Coursera](https://www.coursera.org/degrees/master-of-science-data-science-boulder).
Chris J. Vargo
Scott Bradley