Science & Technology Course

CZ4042: Neural Networks

Course Type: Certification | Study Mode: Part-Time
Keywords: Undergraduate | IT | Neural Networks

Course Detail

Introduction
This course covers the information processing techniques inspired by the workings of biological neural networks, which provides solution to interrogatives that current linear systems are not able to resolve. With insights into the Biological neuron, knowledge on the diverse artificial neural networks, the student will be able to design and select suitable artificial neural network model for solving real world applications, and perform the required simulations and implementations.
Curriculum Overview
On successful completion of this course, students will have:
a) Understand that current artificial neurons are simple abstractions of the biological neurons, realized as elements in a program or as circuits made of silicon.
b) Recognize that current artificial neural networks, although yet to come close to having a fraction of the power of the human brain, can be trained to perform useful functions.
c) Possess a good idea on diverse forms of artificial neural networks.
d) Understand the underlying principles, structures and operations of different artificial neural networks.
e) Supervised and Unsupervised learning. Design and select a suitable artificial neural network model for an application.
f) Understand what artificial neural network can do for you. Appreciate successful applications in the areas of pattern classification, function approximation and time series prediction.
Entry Requirements
Working professionals with prior knowledge of:
Pre-requisite: CZ1007 Data Structures, CZ1012 Engineering Mathematics II
- At least 21 years of age
- Have 2 years of full-time work experience, or have fully discharged full-time NS liability, or are currently employed on a full-time basis.
- Degree in Engineering/Science or
- Polytechnic Diploma with relevant working experience
Other Information
Funding
- SkillsFuture Series / SSG
- SkillsFuture Credit
- NTUC-UTAP
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