About this Specialization
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.
From | University of Colorado Boulder via Coursera |
---|---|
Hours | 64 |
Instructors | Chris J. Vargo, Scott Bradley |
Language | English |
Subjects | Data Science Programming Mathematics |
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Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).
Teacher: Computer Science $55k
Instructor - Computer Science $72k
Lecturer of Computer Science $72k
Computer Science educator $78k
Computer Science Specialist $87k
Lecturer (Computer Science) $98k
MS Computer Science $106k
Professor Computer Science $109k
Computer Science R&D $129k
Associate Computer Science $133k
Professor - Computer Science $138k
MS in Computer Science $141k
Courses in this Specialization
Listed in the order in which they should be taken
Starts | Course Information | |
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Jun |
Supervised Text Classification for Marketing Analytics Marketing data often requires categorization or labeling. In today’s age, marketing data can also be very big, or larger than what humans can reasonably tackle. In this course,... Coursera | University of Colorado Boulder |
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Jun |
Unsupervised Text Classification for Marketing Analytics Marketing data is often so big that humans cannot read or analyze a representative sample of it to understand what insights might lie within. In this course, learners use... Coursera | University of Colorado Boulder |
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Jun |
Network Analysis for Marketing Analytics 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... Coursera | University of Colorado Boulder |
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From | University of Colorado Boulder via Coursera |
---|---|
Hours | 64 |
Instructors | Chris J. Vargo, Scott Bradley |
Language | English |
Subjects | Data Science Programming Mathematics |
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).
Teacher: Computer Science $55k
Instructor - Computer Science $72k
Lecturer of Computer Science $72k
Computer Science educator $78k
Computer Science Specialist $87k
Lecturer (Computer Science) $98k
MS Computer Science $106k
Professor Computer Science $109k
Computer Science R&D $129k
Associate Computer Science $133k
Professor - Computer Science $138k
MS in Computer Science $141k
Similar Courses
Sorted by relevance