Deep Learning Fundamentals
Date: 26 Jun, 27 Jun 2023 | 9am-5.30pm | Online
Duration: 2 Days
Course Overview
Deep learning is the most important breakthrough in the history of Artificial Intelligence (AI). We easily can divide the history of AI into before and after deep learning eras. Apart from its technical value, Deep Learning (DL) has facilitated many new applications for AI and machine learning. Thanks to deep learning, we can implement high-performance and robust intelligent systems in daily life, the health sector, prediction, surveillance, decision making, and business analytics. DL also allows us to handle semi-structured and unstructured data efficiently. Therefore, it can effectively be used in customers opinion mining, chatbot design, and social media analytics. In this course we are going to introduce deep learning and its applications, then focus on the design and development of deep convolutional neural network models mostly for natural language processing, sentiment analysis, and opinion mining based on a few hands-on that will be carried out by learners.
This module is part of Professional Certificate in Text Processing.
Course Objectives
At the completion of the course, the participants will be able to:
- acquire basic knowledge of deep neural networks and how they work
- understand the applications of deep learning
- use popular software tools and applications for deep learning implementation
- acquire basic skills on how to design and implement text classification and opinion mining systems using deep learning
- acquire basic skills on how to implement convolutional neural networks in Python using Tensorflow and Keras packages
Who Should Attend
ICT Executives, Managers, Engineers, Analysts
Prerequisites
- Basic AI and Machine Learning knowledge
- Basic Python programming skills (Click to view the course detail of Python Programming.)
Course Convener
(Click their photos to view their short biographies)
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 on teaching Artificial Intelligence and Data Science courses, e.g. machine learning, deep learning, data mining and etc.
She graduated from NUS with a PhD degree on Electrical and Computer Engineering. Her research focused on Game Theoretical Modelling, Optimization Methods, Algorithm Design and Wireless Networks.
She worked in BHP Billiton Marketing Asia for eight years and gained a lot of industry experience through different functions, e.g. risk management, supply chain management, sales and marketing planning and etc.
Course Fees
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes
Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.
To enquire, email soc-ace@nus.edu.sg
To register, click Register
Course Code:
TGS-2022012786 (Classroom Learning)
TGS-2022012789 (Synchronous e-learning)
For members of public and NUS Alumnus (without R&G Voucher), please follow the steps below:
Select Short Course / Modular Course -> Apply for Myself -> Browse Academic Modules / Short Courses-> Module/Course Category -> Short Courses -> Browse Courses-> Strategic Tech Mgt Institute (Faculty/Department / Unit)
Please download the user guide for NUS Online Application Portal after you click ‘Apply for Myself’ if you need assistance.
Course Fee Breakdown
Singapore Citizens
39 years old or youngerSingapore Citizen
40 years old or older
