This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).
This course is part of the Applied Data Science with Python Specialization
Offered By
About this Course
What you will learn
Understand how text is handled in Python
Apply basic natural language processing methods
Write code that groups documents by topic
Describe the nltk framework for manipulating text
Skills you will gain
- Natural Language Toolkit (NLTK)
- Text Mining
- Python Programming
- Natural Language Processing
Offered by

University of Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Syllabus - What you will learn from this course
Module 1: Working with Text in Python
Module 2: Basic Natural Language Processing
Module 3: Classification of Text
Module 4: Topic Modeling
Reviews
- 5 stars55.07%
- 4 stars25.23%
- 3 stars12.01%
- 2 stars4.34%
- 1 star3.33%
TOP REVIEWS FROM APPLIED TEXT MINING IN PYTHON
Quite challenging but also quite a sense of accomplishment when you finish the course. I learned a lot and think this was the course I preferred of the entire specialization. I highly recommend it!
Would love to see these courses have more practice questions in each weeks lesson. Would be helpful for repetition sake, and learning vs only doing each question once in the assignments.
Good course to take although I felt the course could have been better in terms of practice. But overall, would recommend to others if they wish to pursue data analysis.
A little bit stretched my python skill, but learned a lot. Forum is a good place, and maybe next I will join some study group online or offline to have more discussions.
About the Applied Data Science with Python Specialization
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.

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