Flexible learning
Online postgraduate courses
Natural Language Processing
The purpose of this course is to introduce students to the theory and practice of applying natural language processing (NLP) in economics and business. We cover all steps in the data science pipeline of transforming textual data into numbers that are relevant for decision making. We assume no prior knowledge concerning specific NLP related subjects and start off with a general introduction to text mining.
After the introduction, we cover the most used unsupervised, such as matrix factorization and topic modelling, and (semi-)supervised, such as document classification, and text mining methods. In addition, the course is designed to enable students to study the principles of constructing linear econometric time series models and how these models can be used in various practical contexts.
This module can be taken as part of a PG Certificate, PG Diploma or Full Masters Program.
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- 10 Credits
- 100 hours of study
- 15 contact hours
- 85 hours for private study
Faculty
Structure
Structure
Natural Language Processing is an elective 10 credit course and therefore students are expected to input approximately 100 hours of study into the course.
The total number of contact hours is 15 hours. This leaves 85 hours for private study.
Lectures
This module consists of 2- hour lectures per day for 5 days, plus a 1 - hour tutorial per day.
During their private study, students should read the course literature, work on practical exercises, and write a project report for the examination.
The dates of each lecture are confirmed closer to the start of each term. If you have any questions about dates, please contact edu@timberlake.co.uk.
Python
Module Programme
Explorative Textual Data Analysis
- Introduction to applications of NLP in economics and management
- Text as data
- Cleaning textual data
- Document feature matrix and word clouds
Categorizing documents
- Unsupervised topic models
- Supervised document classification
Sentiment analysis
- Definition of sentiment
- Lexicon-based approaches
- Improvements
Time series analysis with sentiment
- Sentiment aggregation into time series
- (Sparse) prediction and forecasting evaluation
- Introduction to the assignment
Prerequisites
English Language Requirements
Both Programmes are open to applicants anywhere in the world. We may ask applicants to provide a recognised English language qualification, dependent upon their nationality and where they have studied/worked previously.
The requirement is an IELTS (Academic) Test with an overall score of at least 6.5, and a minimum of 6.0 in each element of the test. We will also consider other English language qualifications. If their score is below our requirements, they may be eligible for one of Lancaster University's pre-sessional English language programmes.
Academic Requirements
Applicants to the Postgraduate Certificate of Achievement, Postgraduate Certificate, Postgraduate Diploma or full MSc in either programme require either an upper second-class degree in economics, econometrics or related subjects.
Learning Outcomes
- Relevant natural language programming techniques and their application to a wide range ofempirical issues
- Integration of natural language programming techniques in econom(etr)ic prediction models
- Use of the open source statistical software Python for solving NLP problems in economicsand business
- Engage in abstract thinking by extracting the essential features of large textual corpora tosolve economic and managerial problem
- Communicate and present complex arguments in oral and written form with clarity andsuccinctness
- Present, interpret and analyse information in numerical form
- Utilise effectively statistical and other packages
- Work effectively both individually and within a team environment
Frequently Asked Questions
All sessions are conducted live and online at a scheduled time, but are also recorded. Students may attend live and watch the recordings back to recap the material or watch the recordings only if unable to attend live. We always advise students to attend live where possible as this will allow them the best opportunity to engage with the content and ask the lecturer's questions.
All modules are examined through online coursework submissions, you will have the support of your module lecturer/tutor in this poccess.
No, all necessary software is provided to students.
All courses are recorded and available on the LUMS internet platform throughout the current academic year. They can therefore be viewed 24 hours a day.
Timberlake Consultants and Lancaster University Management School (LUMS) Economics department have a longstanding partnership; combining 40+ years of industry expertise with over 50 years of academic excellence. We are delighted to build on this with our micro-credential postgraduate courses.
Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education
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Flexible learning
Online postgraduate courses
Specialist courses
Best-in-field experts
Tailored learning
Career-oriented education