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Updated in [June 30th, 2023]

This four-week course, Natural Language Processing: Foundations, provides students with a solid understanding of how to work with text. Instructors Min and Chris, both with over 30 years of experience in natural language processing, will guide students through traditional, time-tested approaches as well as the exciting, modern advanced approaches using deep learning. At the end of the course, students will have the foundation to create their own text classification application and a generative, text suggestion system, like autocomplete. Both instructors have won awards for teaching at NUS and have received strong student feedback in their teaching of the NLP course at NUS.

[Applications]
Upon completion of this course, students will be able to apply their knowledge of Natural Language Processing to create their own text classification application and a generative, text suggestion system. They will also have the foundation to explore both traditional and modern advanced approaches using deep learning. With the guidance of instructors who have over 30 years of experience in the field, students will be well-equipped to apply their knowledge of NLP to real-world applications.

[Career Path]
A recommended career path for learners of this course is a Natural Language Processing (NLP) Engineer. NLP Engineers are responsible for developing and deploying natural language processing models and algorithms to solve real-world problems. They must have a strong understanding of NLP fundamentals, such as text pre-processing, tokenization, and sentiment analysis, as well as a deep knowledge of machine learning algorithms and techniques. NLP Engineers must also be able to work with large datasets and have experience with programming languages such as Python and R.

The development trend of NLP Engineers is rapidly growing due to the increasing demand for natural language processing applications in various industries. Companies are increasingly relying on NLP Engineers to develop and deploy models that can process large amounts of data quickly and accurately. As a result, NLP Engineers are in high demand and the job market is expected to continue to grow in the coming years.

[Education Path]
The recommended educational path for learners of this course is to pursue a degree in Natural Language Processing (NLP). This degree typically involves courses in linguistics, computer science, and artificial intelligence. Students will learn the fundamentals of NLP, including text analysis, text mining, and machine learning. They will also gain an understanding of the various algorithms and techniques used in NLP, such as deep learning, natural language understanding, and natural language generation. Additionally, students will learn how to apply NLP to real-world problems, such as text classification, sentiment analysis, and text summarization.

The development trend of NLP is rapidly evolving, with new technologies and applications being developed every day. As such, students pursuing a degree in NLP should be prepared to stay up-to-date with the latest advancements in the field. Additionally, they should be prepared to develop their own projects and applications, as this is an important part of the degree. Finally, students should be prepared to work with a variety of different languages and technologies, as NLP is a highly interdisciplinary field.