Data Science: Text Analysis Using R
offered by LSE

Public University
1 Campus
Estd. 1900

Data Science: Text Analysis Using R
at
LSE
Overview

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

Duration	8 weeks
Total fee	₹1.84 Lakh
Mode of learning	Online
Course Level	UG Certificate

Data Science: Text Analysis Using R
at
LSE
Highlights

Earn a certificate of completion from The London School of Economics and Political Science

Data Science: Text Analysis Using R
at
LSE
Course details

Skills you will learn

Data mining R Statistics Data visualization Data Science

Who should do this course?

For Professionals working in the fields of data science or analytics
For Data analysts working in finance or operations, IT professionals or software engineers
For Digital marketing professionals with a proficiency in data analytics
For Individuals who have an interest in analysing large sums of text,

What are the course deliverables?

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

More about this course

The Data Science: Text Analysis Using R online certificate course provides a comprehensive, practical grounding in the process of textual data mining
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 practice in Jupyter notebooks and R will help fine-tune your data analytics skill set

Data Science: Text Analysis Using R
at
LSE
Curriculum

Module 1

Working with textual data in R

Module 2

Cleaning, processing, and transforming text

Module 3

Data visualisation and descriptive statistics for text

Module 4

Clustering methods for words and documents

Module 5

Topic models

Module 6

Sentiment analysis

Module 7

Document classification

Module 8

Social media analysis

Data Science: Text Analysis Using R
at
LSE
Faculty details

Professor Kenneth Benoit, Professor of Computational Social Science

Kenneth is Director of the Data Science Institute at LSE. His research focuses on quantitative methods for processing large amounts of textual and other forms of big data – mainly political texts and social media – and the methodology behind text mining. Kenneth is the creator and co-author of several popular R packages for text analysis, including Quanteda, Spacyr, and Readtext.