In this program, you will learn the knowledge and skills required to apply AI to real-world engineering systems.
Part-Time/ 1 Year
Ngee Ann Polytechnic reserves the right to reschedule/ cancel any programme, modify the fees and amend information without prior notice.
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.
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).
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.
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.
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.
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.
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.
Recognition of Prior Learning (RPL)
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.
For more information about Recognition of Prior Learning, please click here.