/Data Science: Text Analysis Using R
Provided by: LSE
Course Area: South East
Course Type: Short Course
Start date: 20220216
End date: 20220419
Subjects: Computer Science, Data Analytics, Data Science
Price: £500 to £2,000
Delivery Method: Online
Course 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.
Who is this course for
- 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
What will I learn
- 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