Professional Certificate in Deep Learning for IoT

Professional Certificate

Professional Certificate in Deep Learning for IoT

Programme Structure

Programme Name	Programme Schedule	Mode of Delivery	Programme Code
Statistical Models for the Internet of Things	To be advised	Classroom Learning	TGS-2022011563
	To be advised	Synchronous e-Learning	TGS-2022013108
Neural Networks for the Internet of Things	To be advised	Classroom Learning	TGS-2022011564
Deep Learning for the Internet of Things	To be advised	Classroom Learning	TGS-2022013118

Duration 6 days

Programme Overview

In the rapidly evolving landscape of the Internet of Things (IoT), harnessing the power of data is paramount. Our Professional Certificate in Deep Learning for IoT is designed to equip learners with indispensable skills, ensuring they are at the forefront of this technological revolution. Learners will delve into the application of statistical methods, enabling them to decipher and predict intricate patterns within IoT data. The programme goes beyond the basics, empowering learners to design deep learning networks that not only learn and predict but also make informed decisions within the complex IoT ecosystem.

Programme Objectives

This Professional Certificate will equip learners with the following competencies:

Apply simple statistical methods to analyzing and understanding IoT data to make predictions and diagnoses
Design neural networks to learn and make predictions and decisions about IoT data
Design and build sophisticated deep learning neural networks to analyse, understand and react to IoT data

Job Role Readiness

It will prepare learners in the following job roles to perform their responsibilities more effectively/ It will prepare learners for the following job roles:

IoT engineers
Specialists in machine learning

Who Should Attend

IoT engineers and specialists in machine learning.

Prerequisites

Bachelor’s Degree in Computing or Mathematics, with programming knowledge
Other Bachelor’s Degree holders with programming knowledge may be considered.
Learners should have completed the Professional Certification in Cloud Technologies for the Internet of Things before embarking on the short course, ’Statistical Models for the Internet of Things’.

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This programme is part of

Advanced Professional Certificate in Internet of Things

Types of Available Fundings

Enhanced Training Support

SFEC

PSEA

Instructors

A/Prof Colin Tan Keng Yan

A/Prof Colin Tan Keng Yan is a senior lecturer at the Department of Computer Science, NUS School of Computing. He specializes in embedded systems and operating systems related courses. Colin has taught courses on real-time system design, operating systems, programming methodology, and had taught a course on software product development for digital markets. In this course students are given a semester to build three production quality software systems, with the first two being on Facebook and on HTML5, and in the third project students are given free rein on the technologies that they would like to use. The third project is particularly beneficial to students, as they get real first-hand experience in building a software product, from conceptualizing, validating their concept with users, to User Interface (UI) design, UI validation with users, building the system, and finally to marketing their systems to recruit thousands of users before their project submission deadline. Projects completed in this module have spawned startups like Pearcomms, HunQRy and PaperBaton, while alumni in this course have gone on to careers in tech giants like Facebook, Google and Microsoft. Colin, together with two other CS colleagues and three ECE colleagues, is currently teaching a course that gives first-year Computer Engineering students first-hand experience in building non-trivial computer systems like tele-operated robots. Students learn key issues of high-efficiency hardware programming, dealing with electro-mechanical issues like variations in motor and gearbox quality, secure network communications, and real-time mapping of the environment using algorithms like SLAM. They also pick up key skills like performing independent research, and learning how to improvise to solve problems with limited resources. Colin also runs courses in drone design, construction and programming. Colin has written a lightweight operating system for the Arduino called ArdOS that fits into less than a kilobyte of memory, available at https://bitbucket.org/ctank/ardos-ide/wiki/Home. He has also written several other libraries for the Arduino including smartTimer, a library for writing timer-based embedded systems, which also includes a software-based real-time clock for the Arduino, and smartSerial, a bare-metal bare-bones serial communications library for the Arduino. His Bitbucket repository is available at https://www.bitbucket.org/ctank. Colin is Lab Coordinator for Makers@SoC, a maker space that was recently set up to give students a chance to immerse themselves in maker culture, which is a blend of DIY and technology. Makers@SoC addresses two key concerns of the industry: that we are producing technology professionals who can only code and cannot build anything physical – a key concern in fields like IoT – and that CS majors may not have a good appreciation of the hardware on which they build their systems. Makers@SoC runs courses in 3D modeling, basic electronics, microcontroller interfacing and programming, circuit design and fabrication, and through-hole and surface-mount soldering. Colin is Chairperson for the IT Software Solutions for Business trade for Worldskills Singapore 2016 and Worldskills Singapore 2018, and has been a long-time General Secretary for the National Olympiad for Informatics (NOI) competition. Outside of academia Colin reads widely into Catholic theology, is a sponsor and a speaker at the Rite of Christian Initiation of Adults (RCIA) Programme, and is a council member and a formation instructor at the Secular Order of Discalced Carmelites (OCDS) in the Roman Catholic Church of Singapore. He is also an avid foodie, a cigar collector, an enthusiast of retro technology, and a somewhat decent and fairly eclectic cook.

Programme Fees

Singapore Citizens		Singapore PRs	Enhanced Training Support for SMEs	International Participants
39 years old or younger	40 years old or older	Singapore PRs	Enhanced Training Support for SMEs	International Participants
S$1,863.90	S$723.90	S$1,863.90	S$723.90	S$6,213.00

Total Nett Programme Fee Payable, including GST, after additional funding from various funding schemes.
Participants must fulfill at least 75% attendance and pass all assessment components for all short courses within a professional certificate in order to be eligible for SSG funding.
Please note that all external funding for courses is limited in duration and subject to eligibility and availability.

A/Prof Colin Tan Keng Yan

Advanced Computing for Executives