Teaching

Natural Langauge Processing, spring 2023

Undergraduate course, Tel-Aviv University, School of CS
Start date: 2024-05-01

Advanced undergraduate course in Natural Language Processing, covering topics from classic unigram methods to most advanced large pretrained language models, instruction finetuning and alignment. In this class students learn to read papers from the frontier of the field and implement them in practice, as well as develop their own research projects in the field of NLP.

Syllabus

Natural Language Processing (NLP) aims to develop methods for processing, analyzing and understanding natural language. The goal of this class is to provide a thorough overview of modern methods in the field of Natural Language Processing. The class will not assume prior knowledge in NLP. Among others, we will cover word representations, language modeling, sequence models, and self-supervision, focusing on the interface between structured prediction and deep learning. Course website

Natural Langauge Processing, fall 2023

Undergraduate course, Tel-Aviv University, School of CS
Start date: 2024-01-01

Advanced undergraduate course in Natural Language Processing, covering topics from classic unigram methods to most advanced large pretrained language models, instruction finetuning and alignment.

Syllabus

Natural Language Processing (NLP) aims to develop methods for processing, analyzing and understanding natural language. The goal of this class is to provide a thorough overview of modern methods in the field of Natural Language Processing. The class will not assume prior knowledge in NLP. Among others, we will cover word representations, language modeling, sequence models, and self-supervision, focusing on the interface between structured prediction and deep learning. Course website

Natural Langauge Processing, fall 2022

Undergraduate course, Tel-Aviv University, School of CS
Start date: 2023-05-01

Advanced undergraduate course in Natural Language Processing, covering topics from classic unigram methods to most advanced large pretrained language models.

Syllabus

Natural Language Processing (NLP) aims to develop methods for processing, analyzing and understanding natural language. The goal of this class is to provide a thorough overview of modern methods in the field of Natural Language Processing. The class will not assume prior knowledge in NLP. Among others, we will cover word representations, language modeling, sequence models, and self-supervision, focusing on the interface between structured prediction and deep learning. Course website