Data Science: Text Analysis Using R

Every business today generates a massive amount of textual information or data, through its marketing, reporting, and customer interactions via social media and email. The data science of text analysis helps organisations quantify this data, identify broad trends and priority areas, and garner competitive insights using machine learning.

On the Data Science: Text Analysis Using R online certificate course from the London School of Economics and Political Science (LSE), you’ll gain a comprehensive, practical skill set for conducting effective text mining from start to finish. Guided by industry expert Professor Kenneth Benoit, you’ll learn how to prepare raw data, unpack and categorise it using clustering and topic modelling, conduct a sentiment analysis and evaluate document classification models, and apply these insights to social media data. You’ll also gain a grounding in Quanteda – an online library for deconstructing textual data, developed by Professor Benoit himself. Over the course of eight weeks, you’ll engage with a range of relevant case studies and real-world data sets, enhancing your ability to extract business-critical insights from textual data in your own organisation.

This course is technical in nature and makes use of coding in R. Some algebraic and calculus knowledge is strongly advised, but is not required. Training in tertiary-level statistics and knowledge of a functional or object-orientated language are also advantageous. HTML is not considered a programming language in this context.

Is this course for you?

This is a technical course using R programming language, best suited to individuals with data or analytical proficiency. The skills and insights available to participants will have broad applicability and appeal across a range of industries and sectors. Existing data science and analytics professionals, including data analysts, software engineers, application developers, and computer scientists, will enhance their understanding of text mining, validate their skills in R, and gain the knowledge to stay ahead of the latest innovations in this field. Businesses, systems, and research analysts who work with reviews, transcripts, reports, articles, and social media on a daily basis will improve the efficiency and accuracy of their data analysis. IT technicians and systems analysts will expand their ability to effectively work with large volumes of organisational data in relation to information databases. Additionally, data-driven managers of teams in areas such as marketing, sales, operations, and project management will benefit from an improved understanding of text analysis.