Present/Upcoming Courses

Term 1, Year 2021 - '22
Natural Language Processing -- CZ4045/CE4045 Course Materials in NTU Learn
Term 2, Year 2021 - '22
Deep Learning for NLP -- CE7455

Past Courses

Term 1, Year 2020 - '21
Natural Language Processing -- CZ4045/CE4045 Course Materials in NTU Learn
Term 2, Year 2020 - '21
Deep Learning for NLP -- CE7455
Term 2, Year 2019 - '20
Deep Learning for NLP -- CE7455
Term 2, Year 2019 - '20
Artificial Intelligence -- CZ3005/CSC304 Course Materials in NTU Learn
Term 2, Year 2018 - '19
Artificial Intelligence -- CZ3005/CSC304 Course Materials in NTU Learn
Term 1, Year 2017 - '18
Data Structures -- CZ1007 (Tutorials) Course Materials in NTU Learn
Term 2, Year 2017 - '18
Artificial Intelligence -- CZ3005/CSC304 Course Materials in NTU Learn
    Sample Feedback from Students on CE7455 (Grad NLP; Year 2020-21 - Term 2)
First, Prof Joty is very knowledgeable and very connected to front tier research. For ex- ample, his group has published a significant number of top tier NLP papers each year and he is connected to strong researchers worldwide. In this way, he can teach us firsthand knowledge and very recent research trends in NLP communities Secondly, though being very knowledgable researcher, Prof Joty is catering to beginners in NLP and does not re- quire much prior knowledge for his course. He can explain difficult concepts and theorems in layman terms and help beginners to understand. Meanwhile he also extends the knowl- edge to connect with front research trends, which benefit experienced student like me too. Thirdly, Prof Joty has made this course clear to follow, by hosting a course website where we can clearly see syllables to cover in each week and also invited speakers from different subdomains.
Prof Joty is very insightful and vivid in explaining difficult concepts. Overall I feel his explanation and teaching is no worse than those in top tier universities like Prof Graham Neubig at CMU or Prof David Silver at UCL.
    Sample Feedback from Students on CE/CZ4045 (UGrad NLP; Year 2020-21 - Term 2)
great job in teaching the fundamentals of how deep learning is applied in NLP. It’s so much better than learning the traditional way of NLP which is not commonly used in 2020 already. Great job in introducing pytorch, another framework that spur student to learn and use it which may be useful in the future.
Given that this is the first time Deep learning is being incorporated into NLP, Prof Joty has taken the effort to include several tutorials for Python, Pytorch and others on Google Colab. That definitely would have cost him additional time but he understands that those are important concepts which we students should all know. He could have taken the easier approach of asking us to google and self-learn, but he provided the resources for us. :D
    Sample Feedback from Students on CE7455 (Grad NLP; Year 2019-20 - Term 2)
I like this course very much. It is well organised with good reference to recent papers and progress. It also includes a lot of practical sessions which can help student to build their own NLP models step by step. I hope there can be more courses like this in SCSE department with new contents such as Reinforcement Learning, Computer Vision, etc.
Professor Joty has planned and structured a course of NLP very well. From fundamen- tal ideas to concept deepening assignments/project. Many useful resources and links are provided for further learning. Teaching materials are up-to-date. Teaching assistants are engaging and helpful to provide python tutorial to the class. As a newbie in Python and Machine Learning, I fell very welcome to the course.
    Sample Feedback from Students on CZ/CS3005 (Ugrad AI; Year 2017-2018 - Term 2)
He is a very good lecturer, he explain it in a very clear and easy to understand way. I can easily tell that he is making a lot of effort to get students to get better.
He always provides relevant examples and goes through the content step by step. Very clear and easy to understand. Thoroughly enjoyed his lectures.
This course, I feel, has been very difficult due to the information and concept of we (student) needed to understand. However, the lecturer has been very clear in explaining the course contents and information, and even giving examples, so that we can better understand the course.

-- Tutorial at Qatar Computing Research Institute

Summer 2015
Machine Learning (8 Lectures)