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This course is part of Text Marketing Analytics Specialization
Instructors: Chris J. Vargo
Included with
Recommended experience
Intermediate level
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
Recommended experience
Intermediate level
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
Describe the concept of topic modeling and related terminology (e.g., unsupervised machine learning)
Apply topic modeling to marketing data via a peer-graded project
Apply topic modeling to a variety of popular marketing use cases via homework assignments
Evaluate, tune and improve the performance the topic model you create for your project
Add to your LinkedIn profile
2 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
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 unsupervised deep learning to train algorithms to extract topics and insights from text data. Learners walk through a conceptual overview of unsupervised machine learning and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project.
This course uses Jupyter Notebooks and the coding environment Google Colab, a browser-based Jupyter notebook environment. Files are stored in Google Drive. This course 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.
In this module, we will cover the fundamental concepts of topic modeling, also known as unsupervised machine learning on unstructured text documents. We will contrast unsupervised methods to supervised ones and survey common applications of topic modeling.
1 video4 readings1 programming assignment1 discussion prompt
In this module, we will go under the hood inside a topic modeling approach and understand what assumptions drive topic model fit. We will also uncover how bag-of-words approaches to topic modeling work, and the natural language processing required to produce meaningful topic modeling features.
2 videos1 reading1 assignment1 programming assignment
In this module, we will cover how to parse through JSON-like data and segment it to create a corpus that is ready for the topic modeling process. We will cover how the data for your project is structured and its taxonomy.
2 videos2 readings1 assignment
In this module, we will take Amazon review data and load it into a corpus to preprocess it. We will cover how to build topic models from the data and also save those topic models.
2 videos2 readings1 peer review
In this module, we will learn how to evaluate the fit of topic models and use the best topic model to classify documents. We will also cover how to build topic models with pre-trained neural networks.
3 videos3 readings1 peer review
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.
University of Colorado Boulder
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University of Colorado Boulder
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O.P. Jindal Global University
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University of Colorado Boulder
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This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
This course is part of the following degree program(s) offered by University of Colorado Boulder. If you are admitted and enroll, your completed coursework may count toward your degree learning and your progress can transfer with you.¹
University of Colorado Boulder
Degree · 2 years
University of Colorado Boulder
Degree · 2 years
University of Colorado Boulder
Degree · 24 months
¹Successful application and enrollment are required. Eligibility requirements apply. Each institution determines the number of credits recognized by completing this content that may count towards degree requirements, considering any existing credits you may have. Click on a specific course for more information.
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