Text Mining and Analytics
Master statistical approaches for mining and analyzing text data to discover patterns and extract insights using natural language processing.
Master statistical approaches for mining and analyzing text data to discover patterns and extract insights using natural language processing.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Mining Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.5
(725 ratings)
71,396 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 3 more
Powered by
What you'll learn
Master statistical techniques for text mining and analysis
Implement natural language processing methods for text data
Develop skills in topic modeling and text clustering
Perform sentiment analysis and opinion mining
Apply probabilistic models to text analysis
Create practical text mining solutions
Skills you'll gain
This course includes:
9.5 Hours PreRecorded video
14 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Closed caption
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
There are 7 modules in this course
This comprehensive course covers major techniques for text mining and analysis, emphasizing statistical approaches that can be applied to any natural language text data. Students learn fundamental concepts in natural language processing, text representation, word association mining, topic analysis, clustering, categorization, and sentiment analysis. The curriculum includes practical applications using probabilistic models and hands-on programming assignments.
Orientation
Module 1 · 2 Hours to complete
Week 1
Module 2 · 3 Hours to complete
Week 2
Module 3 · 4 Hours to complete
Week 3
Module 4 · 10 Hours to complete
Week 4
Module 5 · 4 Hours to complete
Week 5
Module 6 · 4 Hours to complete
Week 6
Module 7 · 4 Hours to complete
Fee Structure
Instructor
Pioneer in Information Retrieval and Text Mining Research
Dr. ChengXiang Zhai serves as Donald Biggar Willett Professor in Engineering at the University of Illinois Urbana-Champaign's Department of Computer Science, with joint appointments at the Institute for Genomic Biology, Department of Statistics, and School of Information Sciences. His groundbreaking research in information retrieval and text mining has earned him numerous prestigious honors, including the ACM SIGIR Gerard Salton Award (2021), ACM Fellowship (2017), and the Presidential Early Career Award for Scientists and Engineers (PECASE). After earning his initial degrees from Nanjing University and a PhD from Carnegie Mellon University, he has published over 200 papers with an H-index of 58, significantly advancing the fields of natural language processing, machine learning, and bioinformatics. His work has received multiple ACM SIGIR Test of Time Awards, reflecting his lasting impact on the field. Through his courses "Text Mining and Analytics," "Text Retrieval and Search Engines," and "Data Mining Project" on Coursera, he continues to shape the next generation of computer scientists while maintaining editorial roles with major journals and conference leadership positions in his field
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
4.5 course rating
725 ratings
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.