Online Certificate Course

Data Science: Text Analysis Using R

Gain the in-depth technical skills to prepare, process, and interpret textual data and obtain meaningful and relevant insights.

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Key details

  • Programme type
    Online Certificate Course
  • Location
    Online
  • Start date
    Feb 16, 2022
  • Duration
    8 weeks
  • Commitment
    8 - 10 hours per week
  • Department
    Department of Methodology

Overview

Organisations today work with vast quantities of unstructured textual information – from email and social media engagements to web server logs and call-centre notes. Across industries, there is a strong need for companies to analyse this text and make it quantifiable, in order to generate insights, respond to trends, and remain competitive.

The Data Science: Text Analysis Using R online certificate course provides a comprehensive, practical grounding in the process of textual data mining. Guided by industry expert Professor Kenneth Benoit, you’ll learn how to conduct a text analysis from start to finish, including preparing raw text, unpacking and categorising it, and evaluating the final analytics using R programming language. You’ll also learn how to effectively use Quanteda – an online library for the quantitative analysis of textual data, developed by Professor Benoit.

Throughout the course, a combination of real-world case studies and regular practise in Jupyter notebooks and R will help fine-tune your data analytics skill set. At the end of the eight weeks, you’ll walk away with a holistic understanding of effective text analysis techniques, and an improved ability to derive critical insights from data in your own organisation.

Impact

  • Grow your analytical skill set with text analysis techniques, such as tokenization, clustering, topic modelling, and document classification
  • Identify semantic structures and subjective information through sentiment analysis and enhance your ability to decode the meaning and emotions behind textual data at scale
  • Gain practical experience using prominent programming software in a ‘sandbox’ environment, using Jupyter notebooks and Quanteda
  • Develop an in-depth understanding of the real-world applications of text analysis through various relevant case studies utilising topical data sets
  • Understand the entire text analysis process from start to finish, including working with raw data, and interpreting and evaluating final analytics

Programme content

This online certificate course is 8 weeks (excluding orientation week) with a time commitment of 8-10 hours per week.

Who attends?

  • Professionals working in the fields of data science or analytics, who wish to enhance their text-mining abilities in order to extract insights from vast quantities of textual data, as well as improve their literacy in R programming language
  • Data analysts working in finance or operations, IT professionals or software engineers, and data-driven managers of teams in sales, marketing, or project management
  • Digital marketing professionals with a proficiency in data analytics looking to gain an improved understanding of text analysis
  • Individuals who have an interest in analysing large sums of text, accumulated in the form of documents or social media posts

Why LSE?

LSE Online builds on our 125 year tradition of exploring the interconnected, multidisciplinary nature of our world that shape society and business globally. Since our inception in 1895, LSE has been a pioneer in providing courses for professional development. Our founding commitment is to understand the causes of things for the betterment of society. Never has this been a more important goal than in these times of unparalleled change. We provide you with the insights and skills to think critically and independently. To make the connections, see the greater picture. To shape the future by understanding today. Whatever stage you are in your life and career. Wherever you are in the world.

Faculty

The design of this online certificate course is guided by LSE faculty, as well as industry experts, who will share their experience and in-depth knowledge with you throughout the course.

Kenneth Benoit

Professor Kenneth Benoit

Professor of Computational Social Science

Department overview

The Department of Methodology is an internationally recognised centre of excellence in research and teaching in the area of social science research methodology. The disciplinary backgrounds of the staff include political science, statistics, sociology, social psychology, anthropology and criminology.

Fees and entry requirements

Tuition fees: £1,800

Upon successful completion of the course, you will receive an LSE certificate of competence.

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. No specific software is required.

 

 

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