Text Mining for Business Analytics and Qualitative Researchs

Text Mining for Business Analytics and Qualitative Researchs
Text Mining for Business Analytics and Qualitative Research
.MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 48000 Hz, 2ch | 712 MB
Duration: 1 hours | Genre: eLearning Video | Language: English


Learn to conduct Text-Analytics on Qualitative Text Data without Coding

What you'll learn

Text-Mining

Business Analytics

Be able to operate computer and has internet connection.

Welcome to this course on applied text analytics.

What you'll learn
Text-Analysis
Text-Mining
Natural Language Processing
Business Analytics
Requirements
Be able to operate computer and has internet connection.
Description
Welcome to this course on applied text analytics. We have designed this course to be your best resource for learning how to analyse enormous amount of unstructured textual data within couple of minutes and achieve deeper insight into the hidden patterns, relationships, and missing links within your data.
We will start up with a basic introduction into what is text analysis, natural language processing, and machine learning. Then we will dive straight into software: From "how to install" to "how to create text-analytics models that generate rich visualisations" You will also find links to explanatory notes, useful resources, databases, and free to use tools.
Our goal is to make you confident in using text analytics for your project along with obtaining a love for analysing texts. The current edition of this course will cover text-analysis with NVivo 12. I plan to update this course soon with newer softwares, resources, and open source applications for you to learn and apply.
Who this course is for:
Business Analysts With No Programming Background Yet Want To Upscale their Business Fast With Text-Mining
Students and Professionals from Biological Sciences, Medicine, Arts, Humanities, and Social Science background, working in Academia, Business, and Government.
People who need to apply text-mining/natural language processing to solve their problems quick and smart.
People who do not have the technical knowledge, and time or interest to learn Python, or R programming languages to get started.
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