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.
CERTIFICATEKatılım Sertifikası
FORMAT100% Online
DURATION2 ay
What you'll learn
Supervised Learning
Python Programming
Model Evaluation
Scikit Learn (Machine Learning Library)
Tensorflow
Machine Learning Algorithms
Data Manipulation
Data-Driven Marketing
Embeddings
Data Preprocessing
Predictive Modeling
Text Mining
Course Content
3 topics
Kurs 1Supervised Text Classification for Marketing Analytics
Kurs 2Unsupervised Text Classification for Marketing Analytics
Kurs 3Network Analysis for Marketing Analytics
Details
ProviderUniversity of Colorado Boulder
TypeCourse
CategoryData Science & AI
LevelBeginner
Duration2 ay
LanguageEnglish
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