Basic Information
This Course Teaches The Development of Natural Language Processing Methods For Exploring and Reasoning About Text As Data. The Course Will Cover The Research Cycle# Problem Definition, Data Collection, Model Design and Implementation, Experimental Design And Implementation, Result Analysis and Oral and Written Presentation. In Particular, The Course Will Deal With Classification Or Text Generation Tasks That Can Be Done Thanks to The New Large Language Models That Have Been Introduced in Recent Years. We Will Learn About The Complexity of Defining The Research Problem and How This Definition Is Closely Related to The Data Collection Process. We Will Cover Various Protocols For Data Collection and in Particular Processes For Ensuring The Quality of The Data Collected. Later, We Will Learn About Choosing a Suitable Learning Algorithm For a Given Problem, and How It Is Possible to Analyze The Results of Such An Algorithm, Even in Complex Cases Where The Agreement Between People Is Only Partial. Finally, We Will Learn How to Present Research Results in Writing and Orally Using Various Means. Learning Outcomes# at The End of The Course Studetns Will Be Able To# At The End of The Course Students Will Be Able To# 1. Design New Text-based Research Problems.__ 2. Collect Data That Support Research On The Research Problem. 3. Design and Implement Advanced Nlp Algorithms to Solve The Research Problem. 4. Design and Implement an Experimental Setup to Evalate Their Soklution to The Research Problem. 5. Analyse The Results of Their Experiments Nad Present Their Conclusions in Both Oral and Written Manners.
Faculty: Data and Decision Sciences
|Undergraduate Studies
|Graduate Studies
Pre-required courses
97215 - Methods in Natural Language Processing or 97216 - Natural Language Processing