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.
Text Marketing Analytics 专项课程科罗拉多大学波德分校课程信息
3,520 次近期查看
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 2 门课程（共 3 门）
中级
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
完成时间大约为13 小时
英语（English）
字幕：英语（English）
您将学到的内容有
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
您将获得的技能
- Topic Model
- Machine Learning
- Python Programming
- Unsupervised Text Classification
- Data Structure
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 2 门课程（共 3 门）
中级
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
完成时间大约为13 小时
英语（English）
字幕：英语（English）
提供方
科罗拉多大学波德分校
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.
立即开始攻读硕士学位
此 课程 隶属于 科罗拉多大学波德分校 提供的 100% 在线 Master of Science in Data Science。
如果您被录取参加全部课程，您的课程将计入您的学位学习进程。
授课大纲 - 您将从这门课程中学到什么
完成时间为 4 小时
What is topic modeling?
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.
完成时间为 4 小时
1 个视频 （总计 20 分钟）, 3 个阅读材料, 1 个测验
完成时间为 4 小时
The Assumptions of a Topic Model, Bag of Words, and Natural Language Processing
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.
完成时间为 4 小时
2 个视频 （总计 24 分钟）, 1 个阅读材料, 2 个测验
完成时间为 1 小时
Prepping Amazon Review Data
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.
完成时间为 1 小时
2 个视频 （总计 27 分钟）, 2 个阅读材料, 1 个测验
完成时间为 2 小时
Pre-Processing Text and Training a Topic Model
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.
完成时间为 2 小时
2 个视频 （总计 29 分钟）, 2 个阅读材料, 1 个测验
关于 Text Marketing Analytics 专项课程
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 often involve relational and connected and involve networks. 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.
常见问题
我什么时候能够访问课程视频和作业？
我订阅此专项课程后会得到什么？
有助学金吗？
还有其他问题吗？请访问 学生帮助中心。
