Introduction to Text Analysis with Python
In Person
This two-class course is for people who have some experience coding in Python and would like to expand their capabilities to include the library Natural Language Toolkit (NLTK). Text analysis, a dynamic field within data science and linguistics, involves the systematic examination of textual data to uncover patterns, extract insights, and derive meaningful information. This process encompasses a range of techniques, from basic tasks like tokenization and stemming to more advanced methods such as sentiment analysis and named entity recognition. By leveraging tools like NLTK researchers can explore the structure and content of text, enabling a deeper understanding of language patterns and context. In this course, we are going to cover the basics of text analysis from pre-process corpora to simple analysis. If you are interested in further developing your text analysis skills, you can attend the Introduction to Topic Modelling with Bert course.
This is an intermediate-level course. You will need to already understand programming with Python. You will need to be familiar with interacting with notebooks, with importing and wrangling data and with applying functions. It will be sufficient for students to have taken the Introduction to Programming with Python course.
Previous knowledge of NLP is not required.
This course will be taught by Xan Cochran.
Those who have registered to take part will receive an email with full details on how to get ready for the course.
After taking part in this event, you may decide that you need some further help in applying what you have learnt to your research. If so, you can book a Data Surgery meeting with one of our training fellows.
More details about Data Surgeries.
If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event.
Learning Outcomes
Understand how text analysis libraries work in Python and what they can and cannot do.
Perform a series of basic text analysis techniques on real-world datasets.
Understand the wrangling steps necessary to prepare texts for distant reading.
If you're interested in other training on text analysis, have a look at the following:
- Silent Disco: Introduction to Sentiment Analysis
- Digital Method of the Month: Text Analysis
- Introduction to Topic Modelling with Bert
- Silent Disco: Understanding and Creating Word Embeddings
- Introduction to Network Analysis with Gephi
- Digital Method of the Month: What LLM Can and Cannot Do
- Beyond Social Networks: Advanced Uses of Gephi in Humanities Research
- Advanced Uses of LLM
- Silent Disco: Hackers' Guide to Language Models
Return to the Training Homepage to see other available events.
Room 4.35, Edinburgh Futures Institute
This room is on Level 4, in the North East side of the building.
When you enter via the level 2 East entrance on Middle Meadow Walk, the room will be on the 4th floor straight ahead.
When you enter via the level 2 North entrance on Lauriston Place underneath the clock tower, the room will be on the 4th floor to your left.
When you enter via the level 0 South entrance on Porters Walk (opposite Tribe Yoga), the room will be on the 4th floor to your right.
