- Data Analysis
- Machine Learning
- text marketing analytics
- Assess Marketing Problems
- Supervised Learning Process
- Supervised Learning
- Classification Models
- Supervised Learning Outcomes
- Topic Model
- Python Programming
- Unsupervised Text Classification
- Data Structure
Text Marketing Analytics 专项课程
在数据科学领域工作. Master strategies in text marketing analytics
Text Marketing Analytics 专项课程科罗拉多大学波德分校您将学到的内容有
Understand the concepts of topic modeling, text classification, and network analysis
Learn to use topic modeling on large unstructured text datasets
Learn to use network analysis to create network graphs, produce network statistics, and extract qualitative insights
Describe text classification and related terminology (e.g., supervised machine learning)
您将获得的技能
关于此 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.
应用的学习项目
Learners explore conceptual overviews of text classification, text topic modeling, and semantic network analysis and dive into real-world datasets through instructor-led tutorials. Learners also conduct a major project for each of the three key methods.
可分享的证书
完成后获得证书
100% 在线课程
立即开始，按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
初级
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
完成课程大约需要 4 个月
建议进度：3 小时/周
英语（English）
字幕：英语（English）
可分享的证书
完成后获得证书
100% 在线课程
立即开始，按照自己的计划学习。
灵活的计划
设置并保持灵活的截止日期。
初级
Basic Python proficiency, including Python's built-in functions, logic, and data structures, is recommended.
完成课程大约需要 4 个月
建议进度：3 小时/周
英语（English）
字幕：英语（English）
专项课程的运作方式
加入课程
Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习，请直接注册专项课程，或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时，您将自动订阅整个专项课程。您可以只完成一门课程，您可以随时暂停学习或结束订阅。访问您的学生面板，跟踪您的课程注册情况和进度。
实践项目
每个专项课程都包括实践项目。您需要成功完成这个（些）项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程，则需要在开始之前完成其他所有课程。
获得证书
在结束每门课程并完成实践项目之后，您会获得一个证书，您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。
此专项课程包含 3 门课程
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, students learn how to use supervised deep learning to train algorithms to tackle text classification tasks. Students walk through a conceptual overview of supervised machine learning and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project.
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 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.
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 network analysis as it pertains to marketing data, specifically text datasets and social networks. Learners walk through a conceptual overview of network analysis and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project.
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 专项课程 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。
常见问题
退款政策是如何规定的？
我可以只注册一门课程吗？
有助学金吗？
我可以免费学习课程吗？
此课程是 100% 在线学习吗？是否需要现场参加课程？
完成专项课程后我会获得大学学分吗？
还有其他问题吗？请访问 学生帮助中心。
