RiseUpp Logo
Educator Logo

Applied Text Mining in Python

Master text mining and NLP techniques using Python, from basic text processing to advanced topic modeling.

Master text mining and NLP techniques using Python, from basic text processing to advanced topic modeling.

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 Applied Data Science with Python 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.

4.2

(3,807 ratings)

1,44,551 already enrolled

English

پښتو, বাংলা, اردو, 2 more

Powered by

Provider Logo
Applied Text Mining in Python

This course includes

25 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

What you'll learn

  • Handle and manipulate text data in Python

  • Implement natural language processing techniques

  • Build text classification systems

  • Develop topic modeling solutions

  • Master text cleaning and preprocessing

  • Create practical text mining applications

Skills you'll gain

Natural Language Processing
Python Programming
NLTK
Text Classification
Topic Modeling
Regular Expressions
Text Analysis
Machine Learning
Sentiment Analysis
Information Extraction

This course includes:

4.2 Hours PreRecorded video

7 quizzes

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

Get a Completion Certificate

Share your certificate with prospective employers and your professional network on LinkedIn.

Provided by

Certificate

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.

icon-0icon-1icon-2icon-3icon-4

There are 4 modules in this course

This comprehensive course covers text mining and natural language processing using Python. Starting with basic text handling and manipulation, students progress through natural language processing tasks, text classification, and topic modeling. The curriculum includes hands-on experience with NLTK framework, regular expressions, and advanced text analysis techniques. Students learn to apply machine learning methods for text classification and develop practical skills in processing and analyzing textual data.

Working with Text in Python

Module 1 · 7 Hours to complete

Basic Natural Language Processing

Module 2 · 5 Hours to complete

Classification of Text

Module 3 · 6 Hours to complete

Topic Modeling

Module 4 · 5 Hours to complete

Fee Structure

Instructor

V. G. Vinod Vydiswaran
V. G. Vinod Vydiswaran

4.2 rating

3,809 Reviews

1,51,881 Students

2 Courses

Innovator in Health Informatics and Natural Language Processing

Dr. V. G. Vinod Vydiswaran is an Assistant Professor at the University of Michigan, holding positions in both the Medical School's Department of Learning Health Sciences and the School of Information. His research focuses on critical areas such as information trustworthiness, large-scale text mining, natural language processing (NLP), and machine learning. Dr. Vydiswaran's current work involves mining and analyzing health information from diverse sources, including scientific literature, community health forums, and social networks, with a particular emphasis on assessing the credibility of online medical information and its implications for healthcare.In addition to his research endeavors, Dr. Vydiswaran teaches courses on applied text mining and information extraction in health contexts, equipping students with essential skills to navigate and analyze health data effectively. His innovative applications of algorithmic models aim to tackle real-world challenges in healthcare, making significant contributions to the field of health informatics and enhancing the understanding of how information impacts patient care and health outcomes

Applied Text Mining in Python

This course includes

25 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free course

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.

4.2 course rating

3,807 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.