This course is being offered as part of Enhanced Training Support Package (ETSP). Click here for more ETSP courses.
Listen to what others are saying about your brand! With Text Mining, you can understand the conversations that matter the most, and draw valuable insights to improve your strategy and operations.
In this two-day introductory course, you will learn the fundamentals of Text Mining – the technology and know-how to make sense of unstructured text content – and how you can analyse customers’ feedback and use them to improve your product and services. As part of the course, you will also learn how to use an open-source data mining tool to process and analyze your text data.
Laptops will be provided for the duration of the course.
Who should attend?
This course is relevant for business managers, business executives and analysts who may desire to analyse textual information in documents, database or social media using open-source analytics platform solutions.
Upon completion of this course, you will learn the following:
- Terms in text analytics
- Basic Text Processing Pipeline
- Analytics Tools available in the market
- Use-cases of text analytics
- Text Pre-Processing using tokenization, stemming, stopwords, word cloud, etc
- Text Clustering for grouping similar texts
- Text Classification for categorizing text into groups
- Use open-source Data Mining tool for hands-on exercises
Basic IT proficiency and a keen interest in data and sentiment analysis
Participants will be awarded the Certificate of Attendance by Republic Polytechnic upon meeting 80% of attendance requirement.
Fees for ETSP
Companies sending their employees for training enjoy 90% course fee funding.
|Full Course Fee (Others)
||Enhanced Training Support Package (ETSP) Scheme
Note: Fees for ETSP are 10% of full course fees
Republic Polytechnic reserves the right to make changes to the course fee and application closing dates without prior notice. The commencement of each course Is subject to sufficient number of participants.
All information is accurate at time publishing.