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Professional Certificate

Professional Certificate in Text Processing

Programme Structure


Programme NameProgramme ScheduleMode of DeliveryProgramme Code
Natural Language Processing FundamentalsTo be advisedSynchronous e-LearningTGS-2022012353
Sentiment Analysis FundamentalsTo be advisedClassroom LearningTGS-2022012369
Deep Learning FundamentalsTo be advisedClassroom LearningTGS-2022012786
Advanced Deep LearningTo be advisedClassroom LearningTGS-2022012788
Duration 7 days

Programme Overview

Text processing is essential for many applications that involve natural language data. It enables computers to understand and generate human language, extract valuable insights from text data, and automate various tasks that involve text analysis.

Why text processing is beneficial for organisations?

  • Improved efficiency: Text processing automates many tedious and time-consuming tasks such as data cleaning, tokenisation, and normalisation, which can significantly improve efficiency and save time.
  • Increased accuracy: Text processing algorithms can analyse large amounts of data much faster and with greater accuracy than humans, reducing errors and improving the quality of insights.
  • Enhanced understanding: Text processing techniques such as sentiment analysis, topic modelling, and named entity recognition can help identify patterns and insights that might not be immediately apparent from a surface-level reading of the text.
  • Better decision-making: Text processing can help organisations make better decisions by providing insights and identifying opportunities or risks that may have been missed otherwise.
  • Improved customer experience: Text processing can help organisations better understand their customers’ needs, preferences, and sentiment, enabling them to provide better customer service and personalised experiences.

Text processing can help organisations extract valuable insights and automate many time-consuming tasks, leading to better decision-making, increased efficiency, and improved customer experiences.

Programme Objectives

This Professional Certificate will equip learners with the following competencies:

  • Provide theoretical foundations to Natural Language Processing (NLP) and build NLP applications using basic Machine Learning
  • Provide participants with the theoretical foundations to text mining, sentiment analysis and building sentiment classifiers using Machine Learning
  • Equip participants with the skills to mine data from the web and perform sentiment analysis on the data
  • Acquire basic knowledge of deep neural networks and understand the applications of deep learning and its implementation
  • Acquire basic skills on how to design and implement text classification, opinion mining systems and convolutional neural networks in Python using Tensorflow and Keras packages.
  • Articulate advanced deep learning models, their strengths and constraints, and their applications in different businesses
  • Have basic skills in using deep learning algorithms to implement simple Natural Learning Processing (NLP) systems.

Job Role Readiness

It will prepare learners in the following job roles to perform their responsibilities more effectively/ It will prepare learners for the following job roles:

  • Artificial intelligence/Machine Learning Executives and Engineers, Data Analysts

Who Should Attend

IT Professionals who plan to be AI / ML Engineers and Data Analysts

Prerequisites

At least a polytechnic diploma.

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Types of Available Fundings

  • Enhanced Training Support
  • SFEC
  • PSEA

    • Instructors


    A/Prof Xavier Bresson

    A/Prof Xavier Bresson

    A/Prof Xavier Bresson is an international leader in the field of deep learning. Particularly, he co-pioneered a new machine learning technology called graph neural networks (GNN), which combines graph theory and neural network techniques to tackle complex data domains. He has organised several international conferences and tutorials on graph deep learning such as the recent UCLA’21 workshop on “Deep Learning and Combinatorial Optimization”, the MLSys’21 workshop on “Graph Neural Networks and Systems”, the UCLA’19 workshop on “New Deep Learning Techniques”, and the NeurIPS’17, CVPR’17 and SIAM’18 tutorials on “Geometric Deep Learning on Graphs and Manifolds”. He has been a speaker at the top machine learning conferences KDD’21, AAAI’21, ICLR’20 and ICML’20. In 2002, he co-developed with Turing award winner Yoshua Bengio a new class of expressive GNN. He has published more than 70 peer-reviewed articles, which have been cited 13,500+. A/Prof Bresson has been the main lecturer of undergraduate deep learning courses since 2015 at EPFL, NTU and NUS, and has received outstanding evaluations for his teaching material and engaging style. He has also taught graduate courses on advanced deep learning at NUS and was a guest lecturer for Turing award winner Yann LeCun’s course at NYU. He has provided industrial short courses on AI and Deep Learning to Fortune 500 companies s.a. Deloitte, UnitedHealth and university alumni training centres at UCLA, EPFL, and NTU.

    Dr Ai Xin

    Dr Ai Xin

    Dr Ai Xin is currently a Lecturer with the School of Computing at the National University of Singapore (NUS). She has many years’ experience teaching Artificial Intelligence and Data Science courses such as machine learning, deep learning and data mining. She graduated from NUS with a PhD degree in Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks. She worked at BHP Billiton Marketing Asia for eight years, gaining extensive industry experience in various functions such as risk management, supply chain management, and sales and marketing planning.

    Dr Lek Hsiang Hui

    Dr Lek Hsiang Hui

    Dr Lek Hsiang Hui is a Specialist in Data Analytics, System Analysis and Development. He is an IT techie who is passionate about computer systems and technology. He is involved in a few startups and is constantly looking into innovative IT solutions which can be translated to business ideas, with the recent one in the area of Big Data Analytics. He is also a mobile application developer and has produced more than 10 mobile apps. Dr Lek has been teaching various undergraduate courses and executive courses in National University of Singapore (NUS) since 2006. Some of these modules include programming methodology, enterprise system analysis and development, and data mining. During this period, he has won a number of teaching awards such as NUS Annual Teaching Excellence Award (2015/16, 2016/17, 2017/18) and NUS Annual Teaching Excellence Honor Roll (2018/19), Faculty Teaching Excellence Award (2014/15, 2015/16, 2016/17), and Faculty Teaching Excellence Award Honor Roll (2017/18). Dr Lek received his Doctor of Philosophy (Information Systems) from NUS in 2013. His research area is in Natural Language Processing (Sentiment Analysis). He graduated with a Bachelor’s Degree (1st class Honors) in Computer Engineering from NUS. Industry Credentials Shopping Malls (UOL, Marina Square, ION), Healthcare (SingHealth), Government (STB), various SMEs in F&B, Apparels, Cleaning Solutions, Photography, Health Products, Baby Products

    Programme Fees


    Singapore Citizens Singapore PRs Enhanced Training Support for SMEs International Participants
    39 years old or younger 40 years old or older
    S$2,272.65 S$882.65 S$2,272.65 S$882.65 S$7,575.50
    1. Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
    2. Participants must fulfill at least 75% attendance and pass all assessment components for all short courses within a professional certificate in order to be eligible for SSG funding.
    3. Please note that all external funding for courses is limited in duration and subject to eligibility and availability.

    Advanced Computing for Executives

    11 Research Link
    COM 3, #B1-07
    Singapore 119391
    Email: soc-ace@nus.edu.sg

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