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This course is intended to introduce to you the concepts of Natural Language Processing (NLP) from the fundamentals till the latest technologies and enable you to apply NLP techniques in real-world projects. It will introduce several major popular state-of-the-art NLP techniques with a focus on attention-based deep learning models. You would need to have exposure to programming skills (Python). An important takeaway would be the translation of theoretical concepts learnt into practical hands-on applications by running simulations on real-life datasets such as machine translation or text summarization. With the emergence of AI-based generative tools such as ChatGPT, NLP is becoming a highly valued topic in several research and development laboratories/sectors, hence this course will equip you with useful industry-relevant skills. In addition, this course will be relevant across 5 MSc programmes (CME, CCA, ET, PE and SP) since students taking this course will be equipped with the fundamental skillsets for machine learning and deep learning algorithms that can be applied in various contexts beyond NLP.
| AUs | 3.0 AUs |
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EE1102
Physics Foundation For Electrical & Electronic Engineering
EE2005
Electrical Devices & Machines
EE2073
Introduction To Eee Design & Project
EE2101
Circuit Analysis
EE2102
Analog Electronics
EE2103
Semiconductor Fundamentals
EE3011
Modelling & Control
EE3013
Semiconductor Devices & Processing
EE3015
Power Systems & Conversion
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| 1900 | COMMON LEC (A) 1900-2150 Fri EMB | COMMON LEC (A) 1900-2050 Fri "EMB" | ||||
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| 2130 | ||||||