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Text Technologies for Data Science

Course code: INFR11145/INFR11229
Course details, including prerequisites, topics covered, and course objectives are: here

Note

The course material of this course is made publicly available for anyone interested to audit the course. This includes lectures slides, recordings, and labs below. However, CW submissions and lab support are provided only to those enrolled to the course.

 

Logistics

Lectures

Wednesdays, 15.00-17.30, Appleton Tower, Lecture Theatre 4.

Labs

Tuesdays, Appleton Tower, 6.06, 3 different slots: 10-11am, 11am:12pm, 1-2pm.

Piazza

Piazza discussion forum of the course is here

 

Lectures

Handouts will be posted on the day of the lecture. Recording of lectures will be available on Learn.

• Lecture 1: Introduction. slides
• Lecture 2: Definitions. slides

 

Labs

• Lab 0: How to read a text file from disk (optional): Lab

Lab Format

Doing labs in compulsory, but attending labs is optional. Labs will run in a self-learing and online/in-person support fashion as follows:

• After each lecture on Wednesday, related lab will be announced and posted online.
• Students will be responsible to start implementing lab directly on their own at home (or on DICE machines). If they have any related question to the lab, they should post it on Piazza and tag their question that it is related to which lab
• Demonstrators will be responsible to asnwer questions related to labs on Piazza. Other students are welcome to provide answers as well.
• Please check that your question has not been asked already by another student before posting yours
• A thread called "answers of Lab X" will be posted on Piazza so students can share their output of the lab.
• By the next Tuesday, if some students still need some help in their lab, you can then drop in to one of our labs, where demonstrators can answer your questions.

 

Coursework

To be announced.

 

Readings

• Textbook1: " Introduction to Information Retrieval", C.D. Manning, P. Raghavan and H. Schutze
• Textbook2: Search Engines: Information Retrieval in Practice (SE). [Tables of Contents]
• Information Retrieval, C.J. van Rijsbergen
• Managing Gigabytes, I.H. Witten, A. Moffat, T.C. Bell
• Recommended Reading for IR Research Students, A. Moffat, J. Zobel, D. Hawking

 

 

Course Coordinators: Walid Magdy and Bjorn Ross