Specialist Diploma in AI for Engineers

Post-Diploma / 1 Year

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Course Information
Learning Outcomes
Course Schedule
Lesson Plan
Certification
Entry Requirements
Course Fees
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Course Information

Learn all about machine learning, deep learning and AI and understand how they add intelligence to engineering systems and processes.

Learning Outcomes

You will acquire practical coding skills and knowledge to implement AI-enabled engineering systems and processes across different engineering domains. As the economy transforms and becomes highly automated and digitalized, you will be able to boost your chances of employability by adding an AI dimension to your engineering expertise.

Course 
Schedule

Monday, 6:00 pm to 10:00 pm
Wednesday, 6:00 pm to 10:00 pm
Thursday, 6:00 pm to 10:00 pm

Course Start Date: 19 Apr 2021_x000D_
Application Period: 15 Dec 2020 to 31 Jan 2021_x000D_
Application Outcome Date: 1 Mar 2021_x000D_
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Ngee Ann Polytechnic reserves the right to reschedule/cancel any programme, modify the fees and amend information without prior notice.

Lesson Plan

Post-Diploma Certificate in Foundations of AI System
Module
Data Handling and Information Visualization
This module covers data importing, cleaning, interpreting and visualizing. Participants will learn advanced methods with Tableau software. This module deals with methods used to manage and analyze real world large datasets and present the results in visually understandable way. It helps to solve the complex engineering challenges present in the data. In this module, participants will be learning new techniques and tools in Tableau to become more resourceful for the engineering industry.
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Module
Machine Learning Systems for Engineers
This course will help participants to apply AI techniques to their fields in order to get accurate solutions. This module covers the basics of artificial intelligence, machine learning and deep learning. It deals with different types of learning techniques like: supervised, unsupervised and reinforced. The concept of features, data handling, training and testing will be explained. It focuses more on the theory, design and applications of artificial neural networks (ANN).
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Module
Artificial Intelligence Real-World Project 1
In this module, various data mining and data analysis methods will be used to carry out the project. Each participant will do hands-on project by applying what he (or she) has learned related to Data Science and Machine Learning.
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Post-Diploma Certificate in Application of AI Systems
Module
Machine Learning Algorithm Development
The framework for automated detection system is explained. This course deals with the working principle of various classifiers like support vector machine, decision tree, k-nearest neighbor, probabilistic neural network and k-means clustering. The techniques to develop the robust classification models and fine-tuning of classifiers will be discussed.
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Module
Deep Learning Application in Engineering
This module covers fundamentals of deep learning and various DL modelling methods, including convolutional neural network (CNN), long short-term memory (LSTM),autoencoders, Tensorflow framework, Optimization techniques and validation techniques.
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Module
Artificial Intelligence Real-World Project 2
In this module, various data mining algorithms and deep learning solutions will be implemented for an industry problem. Each participant will do hands-on project using Python/Tensorflow by applying what he (or she) has learned related to DL and ML algorithms.
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Certification

1 Specialist Diploma
2 Post-Diploma Certificates
6 Modules

Certification

You are required to complete 2 post-diploma certificates within 2-year validity period to be awarded the Specialist Diploma qualification.


Entry Requirements

Applicants with any of the following qualifications are invited to apply for the course:

A recognised local polytechnic Diploma or a Degree in any engineering/IT discipline._x000D_
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Recognition of Prior Learning (RPL)_x000D_
Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least 5 years of relevant working experience or supporting evidence of competency readiness. Suitable applicants who are shortlisted may have to go through an interview and/or entrance test. The Polytechnic reserves the right to shortlist and admit applicants.

Offered by School of Engineering

Course Fees

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  • The fees below are per semester.

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  • The fees below are inclusive of GST.

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  • The fees below are determined based on prevailing funding policies and subject to review and revision.

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SkillsFuture Credit_x000D_
This course is eligible for SkillsFuture Credit._x000D_
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All Singaporeans aged 25 years and above can use their $500 SkillsFuture Credit from the government to pay f​or a wide range of courses. The credits can be used on top of existing course fee subsidies/funding. This is only applicable for self-sponsored applicants and must be applied via the SkillsFuture Portal. More details on the SkillsFuture Credit Claims will be advised upon admission into the course. Find out more about SkillsFuture Credit at www.skillsfuture.sg/credit._x000D_
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Refer here for full table of course fees throughout the semesters._x000D_
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Skills-Based Modular Courses (SBMCs) are bite-sized part-time courses for individuals to acquire new skills or deepen relevant skills, without the need to pursue a full diploma. Refer here for course fees for SBMCs.

Applicants / Eligibility Fees
Singapore Citizens (SC) below the age of 40 years$371.71
Singapore Citizens (SC) aged 40 and above$255.92
Singapore Permanent Residents (PR)$1982.50
Enhanced Training Support for SME Scheme (for SC & SPR)$255.92
Others (and Repeat Students)$2478.13