Machine Learning Systems for Engineers - Part of Modular Certificate in Machine Learning and Data Visualization (Elective) (DEM1)
About This Course
This module will help students 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 lke: 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)
What You'll Learn
Entry Requirements
Min. 3 relevant GCE ‘O’ levels and with at least 1 year of relevant working experience:
• English Language (Grade 1-7)
• Mathematics (Grade 1-6)
• Science (Grade 1-6)
OR NITEC with GPA >= 3.5
OR NITEC with GPA >= 3.0 and with at least 1 year of relevant work experience
OR Higher NITEC with GPA >= 2.0
OR Higher NITEC with GPA >= 1.5 and with at least 1 year of relevant work experience
OR NITEC in Technology or Services with GPA >= 3.5 and with at least 1 year of relevant working experience
OR Higher NITEC in Technology or Services with GPA >=2.0 and with at least 1 year of relevant working experience
OR relevant Advanced WSQ Certificate (or higher) and Level 6 WSQ Workplace Literacy SOA and Workplace Numeracy SOA and with at least 1 year of relevant working experience
OR applicants with at least 2 years of relevant working experience may apply for the course
Recognition of Prior Learning (RPL)