Machine Learning Solution Design

Short Course

Machine Learning Solution Design

Programme Schedule	Duration (days)	Mode of Delivery	Programme Code
To be advised	3	Classroom Learning	TGS-2022014568

Course Overview

Machine Learning Operations (MLOps) is a set of practices that aims to deploy and maintain Machine Learning (ML) models in production reliably and efficiently. Machine Learning models are tested and developed in isolated experimental systems. MLOps is about orchestrating the steps in the ML pipeline, then automating the execution of the pipeline for continuous training (CT) of the models. This course provides a high-level understanding of the processes required in the creation of Machine Learning solutions and design. Practical hands-on interactions with the tools forms a part of the learning process.

Course Objectives

This course will enable learners to:

Understand and execute the processes of MLOps from ML solution design of new model pipelines
Understand ML lifecycle management
Learn the tools and techniques in MLOps

Job Role Readiness

Data Engineers
Data Analysts
Software Engineers
Any professionals involved in Machine Learning lifecycle management.

Prerequisites

At least a polytechnic diploma
Basic Python programming knowledge

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This programme is part of

Professional Certificate in Machine Learning Operations

Types of Available Fundings

Enhanced Training Support

SFEC

UTAP

PSEA

Testimonials

The course is well-structured to understand how machine learning models work in details. The professor explained the concepts clearly.

Ho Gui Ying

This course is quite in-depth in the logic behind machine learning algorithms, where the professor is quite detailed and clear in her explanations, making it easy for people to understand. It would be advisable for those who have some knowledge as it can be tough for those with zero knowledge in coding and data science.

Lim Jiahui

Instructors

Dr Ai Xin

Dr Ganesh Neelakanta Iyer

Dr Ganesh Neelakanta Iyer is a Lecturer in in the Department of Computer Science, National University of Singapore. Prior to this, he worked as a lead DevOps engineer at Salesforce.com. He had also served as an Associate Professor in the Department of Computer Science & Engineering, School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore. He has received his Bachelor’s degree in Computer Science and Engineering (University first rank) from Mahatma Gandhi University, Kerala, India in 2004 and Masters and PhD degrees from National University of Singapore in 2008 and 2012 respectively. He brings in a decade of industry experience in various companies including Sasken Communication Technologies, NXP semiconductors and Progress software. He has handled several roles in the software industry including QA Architect, Technical Support Manager, Engineering development and Technology Evangelist. He has strong inclination towards Game Theory. He applies game theory for handling conflicts, enforcing cooperation and for multi-agent systems. His technical knowledge and experience are in various areas including Cloud/Edge/Fog Computing Paradigms (including cloud platforms, containers and Kubernetes), Computer Networks, Software Engineering practices (Agile) and Quality Analysis, Economic models (Game Theoretic principles) and current day practices on cloud-based enterprise architectures, Machine Learning and technology for traditional Indian dance (such as Kathakali) popularization. His mathematical interests include game theory, graph theory, optimization principles etc. Over the past several years he has acquired practical knowledge and experience in various cutting-edge software engineering methodologies including Agile framework and has experience formulating and implementing various software engineering principles using Agile for large and small product development teams. Dr Iyer is active in doing practical industry-oriented research on the above topics of his interest. He also aspires to do research on technological innovations to popularize traditional classical arts such as Kathakali and Koodiyattam. He has published two book chapters in the “Encyclopaedia for Cloud Computing” in 2016 in addition to several book chapters, journals and conference publications. Dr. Iyer has delivered several practical workshops and talks on various cutting-edge technology topics in many academic and industry events in several countries including USA, Europe, Australia and Asia. Many of these were on the contributions made by him in his industry engagement for software quality analysis with current day software engineering principles such as Agile for application development involving cloud platforms, mobile platforms and IoT based systems. Dr Iyer is an IEEE Senior Member. He has been a reviewer of many internationals Journals including IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems and several international conferences. He was also the program chair for several international conferences including ICCCI and ICIWE. Dr Iyer has strong teaching skills and boundless passion for teaching. He was a visiting faculty at IIIT-H (International Institute of Information Technology Hyderabad), and has been teaching various subjects including “Game Theory for Computer Science”, “Computer Networks”, “Advanced Computer Networks” and “Scripting and Computer environments” for which, he has framed the syllabus, developed the materials and references, structured the grading scheme and formulated continuous assessment strategies. Further, he was a member of Board of Studies at JNTU-H (a premium university in India) where he participates in framing the syllabus for the university’s upcoming academic year. He is also an expert in performing Kathakali, a traditional Indian dance. He has composed a story in Kathakali and he spends a considerable amount of his personal time to uplift this traditional art by organizing Kathakali performances, workshops and demonstrations and performance by himself. He has also composed a Kathakali story “Sri Mookambika Mahathmyam” which has been staged in multiple venues in India.

A/Prof Danny Poo

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
Full Programme Fee	S$3,150.00	S$3,150.00	S$3,150.00	S$3,150.00	S$3,150.00
Less: SSG Grant Amount	S$2,205.00	S$2,205.00	S$2,205.00	S$2,205.00	-
Nett Programme Fee	S$945.00	S$945.00	S$945.00	S$945.00	S$3,150.00
9% GST on Nett Programme Fee	S$85.05	S$85.05	S$85.05	S$85.05	S$283.50
Total Nett Programme Fee Payable, Including GST	S$1,030.05	S$1,030.05	S$1,030.05	S$1,030.05	S$3,433.50
Less Additional Funding	-	S$630.00	-	S$630.00	-
Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes	S$1,030.05	S$400.05	S$1,030.05	S$400.05	S$3,433.50

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 to be eligible for SSG funding.
The applicable funding is for Singaporeans and Singapore PRs. This is subject to change and in accordance with SSG funding guidelines as of course commencement.

Other Information

This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.

Dr Ai Xin

Dr Ganesh Neelakanta Iyer

A/Prof Danny Poo

Advanced Computing for Executives