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Ahmad Varasteh
In this 2-hour course, we'll learn to analyze customer reviews for an online women's clothing shop. Our task is determining which clothing category (Tops, Bottoms, Jackets, Dresses, or Intimate) has higher customer satisfaction. The data consists of text reviews, and we'll use Python with pandas for data manipulation and the NLTK module for text preprocessing and sentiment analysis. Prior knowledge of Python and pandas is required. By the end of the course, learners will gain practical experience in text data analysis and customer sentiment evaluation. This project is aimed at learners interested in Natural Language Processing (NLP) using Python.
Register for this course and see more details by visiting:
OpenCourser.com/course/4vwcar/python
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What's inside
Syllabus
Project Overview
In this 2-hour course, we'll learn to analyze customer reviews for an online women's clothing shop. Our task is to determine which clothing category (Tops, Bottoms, Jackets, Dresses, or Intimate) has higher customer satisfaction. The data consists of text reviews, and we'll use Python with pandas for data manipulation and the NLTK module for text preprocessing and sentiment analysis. Prior knowledge of Python and pandas is required. By the end of the course, learners will gain practical experience in text data analysis and customer sentiment evaluation. This project is aimed at learners interested in Natural Language Processing (NLP) using Python.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Ahmad Varasteh, who is an expert in Natural Language Processing (NLP) and text analysis
Analyzes real-world customer reviews, providing practical experience in text data analysis and customer sentiment evaluation
Utilizes Python with pandas and the NLTK module, industry-standard tools for data manipulation and text preprocessing
Develops practical skills in using NLP for analyzing customer feedback and improving product or service offerings
Suitable for learners interested in pursuing Natural Language Processing (NLP) using Python
Requires prior knowledge of Python and pandas
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Save Python NLTK for Beginners: Customer Satisfaction Analysis to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Python NLTK for Beginners: Customer Satisfaction Analysis with these
activities:
Review natural language processing concepts
Show steps
Familiarize yourself with or strengthen your foundational knowledge of natural language processing and text analysis techniques to facilitate easier learning during the course.
Browse courses on
Natural Language Processing
Show steps
-
Review core NLP concepts such as tokenization, stemming, and lemmatization.
-
Go over different NLP tasks such as sentiment analysis, text classification, and named entity recognition.
-
Explore popular NLP libraries like NLTK, spaCy, and gensim.
Read 'Natural Language Processing with Python'
Show steps
Supplement your course learning with a comprehensive book that provides an in-depth exploration of NLP concepts, techniques, and applications.
View
Natural Language Processing with Python:...
on Amazon
Show steps
-
Read chapters relevant to the course topics.
-
Work through the book's exercises to practice NLP techniques.
Attend NLP workshops
Show steps
Gain exposure to the latest NLP advancements and best practices by attending workshops led by industry experts and practitioners.
Browse courses on
NLP
Show steps
-
Research and identify NLP workshops that cover relevant topics.
-
Register for the workshops and actively participate in the sessions.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in discussion forums
Show steps
Engage with your peers to discuss course concepts, ask questions, and share insights to foster deeper learning and understanding amongst the group.
Show steps
-
Ask questions in the discussion forums to clarify concepts.
-
Respond to your classmates' questions to reinforce your own understanding.
-
Share your insights on course topics to contribute to the collective learning experience.
Explore NLTK tutorials
Show steps
Enhance your understanding of NLP techniques by completing NLTK tutorials to reinforce your learning from the course.
Browse courses on
NLTK
Show steps
-
Complete NLTK's interactive tutorials on text classification, stemming, and sentiment analysis.
-
Explore NLTK's documentation to learn about its other features and capabilities.
Solve NLP coding challenges
Show steps
Reinforce your understanding of NLP concepts by attempting coding challenges that require you to apply NLP techniques to solve real-world problems.
Browse courses on
NLP
Show steps
-
Find NLP coding challenges on platforms like HackerRank or LeetCode.
-
Attempt the challenges and debug your code.
-
Review solutions and learn from others' approaches.
Develop a sentiment analysis model
Show steps
Apply your NLP skills by building a sentiment analysis model to deepen your understanding of text analysis and classification.
Browse courses on
Sentiment Analysis
Show steps
-
Gather a dataset of labeled customer reviews.
-
Preprocess the reviews using NLP techniques.
-
Train a machine learning model for sentiment analysis.
-
Evaluate the model's performance.
Participate in an NLP hackathon
Show steps
Enhance your NLP skills and gain practical experience by working on a project or participating in a competition that requires you to apply NLP techniques to solve a specific challenge.
Browse courses on
NLP
Show steps
-
Find an NLP hackathon or competition that aligns with your interests.
-
Form a team or work individually on the project.
-
Develop an NLP solution to address the challenge.
-
Submit your project for evaluation and feedback.
Review natural language processing concepts
Show steps
Familiarize yourself with or strengthen your foundational knowledge of natural language processing and text analysis techniques to facilitate easier learning during the course.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Review core NLP concepts such as tokenization, stemming, and lemmatization.
- Go over different NLP tasks such as sentiment analysis, text classification, and named entity recognition.
- Explore popular NLP libraries like NLTK, spaCy, and gensim.
Read 'Natural Language Processing with Python'
Show steps
Supplement your course learning with a comprehensive book that provides an in-depth exploration of NLP concepts, techniques, and applications.
View
Natural Language Processing with Python:...
on Amazon
Show steps
Show steps
Show steps
- Read chapters relevant to the course topics.
- Work through the book's exercises to practice NLP techniques.
Attend NLP workshops
Show steps
Gain exposure to the latest NLP advancements and best practices by attending workshops led by industry experts and practitioners.
Browse courses on
NLP
Show steps
Show steps
Show steps
- Research and identify NLP workshops that cover relevant topics.
- Register for the workshops and actively participate in the sessions.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in discussion forums
Show steps
Engage with your peers to discuss course concepts, ask questions, and share insights to foster deeper learning and understanding amongst the group.
Show steps
Show steps
Show steps
- Ask questions in the discussion forums to clarify concepts.
- Respond to your classmates' questions to reinforce your own understanding.
- Share your insights on course topics to contribute to the collective learning experience.
Explore NLTK tutorials
Show steps
Enhance your understanding of NLP techniques by completing NLTK tutorials to reinforce your learning from the course.
Browse courses on
NLTK
Show steps
Show steps
Show steps
- Complete NLTK's interactive tutorials on text classification, stemming, and sentiment analysis.
- Explore NLTK's documentation to learn about its other features and capabilities.
Solve NLP coding challenges
Show steps
Reinforce your understanding of NLP concepts by attempting coding challenges that require you to apply NLP techniques to solve real-world problems.
Browse courses on
NLP
Show steps
Show steps
Show steps
- Find NLP coding challenges on platforms like HackerRank or LeetCode.
- Attempt the challenges and debug your code.
- Review solutions and learn from others' approaches.
Develop a sentiment analysis model
Show steps
Apply your NLP skills by building a sentiment analysis model to deepen your understanding of text analysis and classification.
Browse courses on
Sentiment Analysis
Show steps
Show steps
Show steps
- Gather a dataset of labeled customer reviews.
- Preprocess the reviews using NLP techniques.
- Train a machine learning model for sentiment analysis.
- Evaluate the model's performance.
Participate in an NLP hackathon
Show steps
Enhance your NLP skills and gain practical experience by working on a project or participating in a competition that requires you to apply NLP techniques to solve a specific challenge.
Browse courses on
NLP
Show steps
Show steps
Show steps
- Find an NLP hackathon or competition that aligns with your interests.
- Form a team or work individually on the project.
- Develop an NLP solution to address the challenge.
- Submit your project for evaluation and feedback.
Career center
Learners who complete Python NLTK for Beginners: Customer Satisfaction Analysis will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are responsible for developing and implementing data-driven solutions to business problems. They use their skills in data analysis, machine learning, and artificial intelligence to help businesses make better decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Data Scientists who want to be able to extract meaningful insights from customer feedback.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and implementing machine learning models to solve business problems. They use their skills in machine learning, artificial intelligence, and data science to help businesses make better decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Machine Learning Engineers who want to be able to extract meaningful insights from customer feedback.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers are responsible for developing and implementing artificial intelligence solutions to business problems. They use their skills in artificial intelligence, machine learning, and data science to help businesses make better decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Artificial Intelligence Engineers who want to be able to extract meaningful insights from customer feedback.
Natural Language Processing Specialist
Natural Language Processing Specialist
Natural Language Processing Specialists are responsible for developing and implementing natural language processing solutions to business problems. They use their skills in natural language processing, machine learning, and data science to help businesses make better decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Natural Language Processing Specialists who want to be able to extract meaningful insights from customer feedback.
Text Mining Specialist
Text Mining Specialist
Text Mining Specialists are responsible for developing and implementing text mining solutions to business problems. They use their skills in text mining, machine learning, and data science to help businesses make better decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Text Mining Specialists who want to be able to extract meaningful insights from customer feedback.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. They work with marketing teams to create and implement marketing strategies, and to track and measure the results of marketing campaigns. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Marketing Managers who want to be able to understand customer feedback and develop marketing campaigns that meet those needs.
Operations Manager
Operations Manager
Operations Managers are responsible for overseeing the day-to-day operations of a business. They work with teams across the business to ensure that operations are efficient and effective. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Operations Managers who want to be able to understand customer feedback and develop operations strategies that meet those needs.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with their products or services. They work with customers to identify and resolve problems, and to provide support and training. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Customer Success Managers who want to be able to understand customer feedback and develop solutions that meet those needs.
Market Researcher
Market Researcher
Market Researchers conduct research to understand consumer behavior and trends. They use this information to help businesses develop new products and services, and to improve marketing and advertising campaigns. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Market Researchers who want to be able to extract meaningful insights from customer feedback.
Investment Analyst
Investment Analyst
Investment Analysts are responsible for analyzing investment opportunities to help clients make informed decisions. They use this information to help clients develop investment portfolios, and to make investment recommendations. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Investment Analysts who want to be able to extract meaningful insights from customer feedback.
Product Manager
Product Manager
Product Managers are responsible for developing and managing products. They work with engineers, designers, and marketers to ensure that products meet the needs of customers. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Product Managers who want to be able to understand customer feedback and develop products that meet those needs.
Sales Manager
Sales Manager
Sales Managers are responsible for leading and managing sales teams. They work with sales teams to develop and implement sales strategies, and to track and measure the results of sales campaigns. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Sales Managers who want to be able to understand customer feedback and develop sales strategies that meet those needs.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems by analyzing data and developing solutions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Business Analysts who want to be able to understand customer needs and develop solutions that meet those needs.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Data Analysts who want to be able to extract meaningful insights from customer feedback.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data to help businesses make informed decisions. They use this information to help businesses make investment decisions, and to develop financial plans. This course can help you develop the skills you need to succeed in this role by providing you with a foundation in data analysis techniques, including data manipulation, text preprocessing, and sentiment analysis. These skills are essential for Financial Analysts who want to be able to extract meaningful insights from customer feedback.
For more career information including salaries, visit:
OpenCourser.com/course/4vwcar/python
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Python NLTK for Beginners: Customer Satisfaction Analysis.
Provides a comprehensive overview of natural language processing, with a focus on Python and the NLTK library. It covers topics such as text preprocessing, tokenization, stemming, lemmatization, and sentiment analysis.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data manipulation, data visualization, and statistical modeling. It valuable resource for learners who want to gain a deeper understanding of the programming language used in this course.
Provides a comprehensive introduction to machine learning, covering topics such as supervised learning, unsupervised learning, and model evaluation. It valuable resource for learners who want to gain a deeper understanding of the techniques used in this course.
Provides a comprehensive introduction to natural language processing, covering topics such as text preprocessing, tokenization, stemming, and sentiment analysis. It valuable resource for learners who want to gain a deeper understanding of the techniques used in this course.
Provides a comprehensive introduction to deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for learners who want to gain a deeper understanding of the techniques used in this course.
Provides a comprehensive overview of machine learning, with a focus on R. It covers topics such as data preprocessing, feature engineering, model selection, and evaluation.
Provides a practical guide to deep learning, with a focus on Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/4vwcar/python
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ahmad Varasteh
Language
English
Good to know
Taught by Ahmad Varasteh, who is an expert in Natural Language Processing (NLP) and text analysis
Analyzes real-world customer reviews, providing practical experience in text data analysis and customer sentiment evaluation
Utilizes Python with pandas and the NLTK module, industry-standard tools for data manipulation and text preprocessing
Develops practical skills in using NLP for analyzing customer feedback and improving product or service offerings
Suitable for learners interested in pursuing Natural Language Processing (NLP) using Python
Requires prior knowledge of Python and pandas
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