Informações sobre o curso
4.1
1,014 ratings
201 reviews
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 should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Intermediate Level

Nível intermediário

Clock

Sugerido: 8 hours/week

Aprox. 17 horas restantes
Comment Dots

English

Legendas: English

O que você vai aprender

  • Check
    Apply basic natural language processing methods
  • Check
    Describe the nltk framework for manipulating text
  • Check
    Understand how text is handled in Python
  • Check
    Write code that groups documents by topic

Habilidades que você terá

Text MiningNatural Language ToolkitNatural Language ProcessingPython Programming
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Intermediate Level

Nível intermediário

Clock

Sugerido: 8 hours/week

Aprox. 17 horas restantes
Comment Dots

English

Legendas: English

Programa - O que você aprenderá com este curso

1

Seção
Clock
8 horas para concluir

Module 1: Working with Text in Python

...
Reading
5 vídeos (Total de 56 min), 4 leituras, 3 testes
Video5 videos
Handling Text in Python18min
Regular Expressions16min
Demonstration: Regex with Pandas and Named Groups5min
Internationalization and Issues with Non-ASCII Characters12min
Reading4 leituras
Course Syllabus10min
Help us learn more about you!10min
Notice for Auditing Learners: Assignment Submission10min
Resources: Common issues with free text10min
Quiz2 exercícios práticos
Practice Quiz8min
Module 1 Quiz12min

2

Seção
Clock
6 horas para concluir

Module 2: Basic Natural Language Processing

...
Reading
3 vídeos (Total de 36 min), 3 testes
Video3 videos
Basic NLP tasks with NLTK16min
Advanced NLP tasks with NLTK16min
Quiz2 exercícios práticos
Practice Quiz4min
Module 2 Quiz10min

3

Seção
Clock
7 horas para concluir

Module 3: Classification of Text

...
Reading
7 vídeos (Total de 94 min), 2 testes
Video7 videos
Identifying Features from Text8min
Naive Bayes Classifiers19min
Naive Bayes Variations4min
Support Vector Machines24min
Learning Text Classifiers in Python15min
Demonstration: Case Study - Sentiment Analysis9min
Quiz1 exercício prático
Module 3 Quiz14min

4

Seção
Clock
6 horas para concluir

Module 4: Topic Modeling

...
Reading
4 vídeos (Total de 58 min), 2 leituras, 3 testes
Video4 videos
Topic Modeling8min
Generative Models and LDA13min
Information Extraction18min
Reading2 leituras
Additional Resources & Readings10min
Post-Course Survey10min
Quiz2 exercícios práticos
Practice Quiz4min
Module 4 Quiz10min
4.1
Direction Signs

20%

comecei uma nova carreira após concluir estes cursos
Briefcase

83%

consegui um benefício significativo de carreira com este curso
Money

10%

recebi um aumento ou promoção

Melhores avaliações

por CCAug 27th 2017

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!

por BKJun 26th 2018

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.

Instrutores

V. G. Vinod Vydiswaran

Assistant Professor
School of Information

Sobre 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....

Sobre o Programa de cursos integrados Applied Data Science with Python

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 basic a 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. Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate....
Applied Data Science with Python

Perguntas Frequentes – FAQ

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.