TTDS: Text Technologies for Data Science

Welcome to Text Technologies for Data Science

Learning Outcomes

On completion of this course, the student will be able to:

• Build basic search engines from scratch, and use IR tools for searching massive collections of text documents
• Build feature extraction modules for text classification
• Implement evaluation scripts for IR and text classification
• Understand how web search engines (such as Google) work
• Work effectively in a team to produce working systems

This course teaches the basic technologies required for text processing, focussing mainly on information retrieval and text classification. It gives a detailed overview of information retrieval and describes how search engines work. It also covers basic knowledge of the main steps for text classification.

This course is a highly practical course, where at least 50% of what is taught in the course will be implemented from scratch in course works and labs, and students are required to complete a final project in small groups. All lectures, labs, and two course works will take place in Semester 1. The final group project will be due early Semester 2 by week 3 or 4.

Course lecturers:

• Walid Magdy
• Björn Ross
• Tj Elmas