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Overview
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 Text Marketing Analytics course offered by Coursera in partnership with University of Colorado Boulder 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.
Key facts
- 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.
Skills you'll gain
- Data Analysis
- Machine Learning
- Text marketing analytics
- Supervised Learning Outcomes
- Assess Marketing Problems
- Supervised Learning
- Classification Models
- Supervised Learning Process
Programme Structure
Courses include:
- Supervised Text Classification for Marketing Analytics
- Unsupervised Text Classification for Marketing Analytics
- Network Analysis for Marketing Analytics
Key information
Duration
- Part-time
- 1 months
- Flexible
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
Campus Location
- Mountain View, United States
Disciplines
Marketing Management Data Analytics View 179 other Short Courses in Data Analytics in United StatesWhat students do after studying
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Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Beginner level
- Recommended experience: Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
Tuition Fees
Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
Additional Details
- Coursera Plus: Subscribe to build job-ready skills from world-class institutions.
- $59/month, cancel anytime or $399/year with 14-day money-back guarantee
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.
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