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*Please note that once the maximum class size is reached, the online registration will be closed. You may register your interest and be notified if there is a new run.
Customer feedback serves as important sources of information for the businesses and organisations to reassess, re-plan and refine their products and services.
The proposed course aims to impart essential ideas, concepts and skillsets in Natural Language Processing with an aim to applying these skills to analyse customer feedback data.
In this course, participants will learn to apply Natural Language Processing (NLP) techniques and tools in Python to derive useful insights from text-based customer feedback data. They will learn basic text pre-processing and apply this to recognize patterns in customer reviews and derive actionable insights through sentiment analysis and text summarization. Participants will also have the opportunity to apply the skillsets to a real data set, through a mini-project, towards the end of the course.
By the end of the course, participants will be able to:
• Apply NLP techniques such as n-gram analysis, text visualisation using word cloud, and topic-modelling to identify key topics and derive hidden patterns from customer reviews
• Apply sentiment analysis and text summarisation to extract actionable insights from customer reviews
Topics to be covered
1. Introduction to Customer Feedback Analysis with NLP
2. Basics of NLP – Text Pre-processing with Python
3. Recognising Patterns in Customer Reviews
4. Actionable Insights through Sentiment Analysis and Text Summarisation
With support from Intel, selected content from Intel® Digital Readiness Program material is included in this short course as supplementary content to enhance the relevance of this course to the Industry and to better support learners in appreciation of the applicability of the concepts covered.