Cloud and AI/ML essentials for Scientists, Engineers, and Technical Managers (AWS Cloud Practitioner Certification)

Course Provider

School of Materials Science and Engineering (MSE)


Continuing Education and Training Certificate


This course is designed for Scientists, Engineers, and Technical Managers with an interest in leveraging cloud computing for their professional pursuits. It caters not only to those in technical roles but also to managers seeking a thorough comprehension of cloud computing principles. This comprehensive curriculum offers an insightful examination of cloud concepts, including AWS core services, security measures, architectural design, pricing strategies, and support functions. Upon successful completion, participants will be primed to undertake and achieve the AWS Cloud Practitioner certification. This educational experience equips attendees with the essential skills and expertise needed to proficiently operate applications on the AWS cloud. This extends to the swift deployment of AI/ML solutions in various fields, the seamless running of web applications, and the strategic implementation of team and organisation-wide cloud-based solutions. The course is an ideal fit for those aiming to deepen their knowledge and skillset in the rapidly evolving realm of cloud technology.

Course Availability

  • Date(s): 13 to 15 Dec 2023

    Time: 9:00AM to 5:00PM

    Venue: NTU@one-north campus, Executive Centre (Buona Vista)

    Registration Closing Date: 29 Nov 2023

This course is developed in cooperation with Amazon Web Services (AWS) Academy for scientists, engineers, and technical managers in any technical field. It is in response for demands for a concise, structured and formally taught course that will equip a learner with the skills to be certified with an industry-leading certification. The curriculum is designed as a route to attaining the basic AWS cloud practitioner certification, the first step in developing a cloud career, or incorporating cloud computing into their work.
This course consists of 10 modules. A knowledge check in the form of an MCQ will be conducted at the end of every module and will function as the course evaluation. Learners are expected to pass all knowledge checks to complete the course.
Module sections
This section lists the module sections in this course.
Course Introduction
  • Course objectives and overview
  • AWS Certification exam information
  • AWS documentation
Module 1: Cloud Concepts Overview
  •  Introduction to cloud computing
  • Advantages of the cloud
  • Introduction to AWS
  • Moving to the AWS Cloud
  • Activity: Sample Exam Question
  • Knowledge check
Module 2: Cloud Economics and Billing
  • Fundamentals of pricing
  • Total cost of ownership
  • Activity: Simple Monthly Calculator
  • Delaware North case study
  • AWS Organizations
  • AWS billing and cost management
  • Billing dashboards
  • Technical support models
  • Activity: Support Plan Scavenger Hunt
  • Activity: Sample Exam Question
  • Knowledge check
Module 3: AWS Global Infrastructure Overview
  • AWS global infrastructure
  • Demo: AWS global infrastructure
  • AWS services and service categories
  • Activity: AWS Management Console Clickthrough
  • Activity: Sample Exam Question
  • Knowledge check
Module 4: Cloud Security
  • AWS shared responsibility model
  • Activity: AWS Shared Responsibility Model
  • Demo: AWS IAM Console
  • Securing a new AWS account
  • Lab: Introduction to AWS IAM
  • Securing accounts
  • Securing data
  • Working to ensure compliance
  • Activity: Sample Exam Question
  • Knowledge check
Module 5: Networking and Content Delivery
  • Networking basics
  • Amazon VPC
  • VPC networking
  • Activity: Label This diagram
  • Demo: Amazon VPC Console
  • VPC security
  • Activity: Design a VPC
  • Lab: Build a VPC and Launch a Web Server
  • Route 53
  • CloudFront
  • Activity: Sample Exam Question
  • Knowledge check

Module 6: Compute
  • Compute services overview
  • Amazon EC2 part 1
  • Amazon EC2 part 2
  • Amazon EC2 part 3
  • Demo: Amazon EC2
  • Lab: Introduction to Amazon EC2
  • Activity: Amazon EC2 Versus Managed Services
  • Demo: Amazon EC2 Part Console
  • Amazon EC2 cost optimization
  • Container services
  • Introduction to AWS Lambda
  • Activity: AWS Lambda
  • Introduction to AWS Elastic Beanstalk
  • Activity: AWS Elastic Beanstalk
  • Activity: Sample Exam Question
  • Knowledge check
Module 7: Storage
  • Demo: Amazon Elastic Block Store Console
  • Lab: Working with EBS
  • AWS S3
  • Demo: AWS S3 Console
  • Demo: AWS EFS Console
  • AWS S3 Glacier
  • Demo: AWS S3 Glacier Console
  • Activity: Storage Technology Selection
  • Activity: Sample Exam Question
  • Knowledge check
Module 8: Databases
  • Amazon RDS
  • Demo: Amazon RDS Console
  • Lab: Build a Database Server
  • Amazon DynamoDB
  • Demo: Amazon DynamoDB
  • Amazon Redshift
  • Amazon Aurora
  • Activity: Database case study
  • Activity: Sample Exam Question
  • Knowledge check
Module 9: Cloud Architecture
  • AWS Well-Architected Framework design principles
  • Activity: AWS Well-Architected Framework Design Principles
  • Operational excellence
  • Security
  • Reliability
  • Performance efficiency
  • Cost optimization
  • Reliability & high availability
  • AWS Trusted Advisor
  • Activity: Interpret AWS Trusted Advisor Recommendations
  • Activity: Sample Exam Question
  • Knowledge check
Module 10: Automatic Scaling and Monitoring
  • Elastic Load Balancing
  • Activity: Elastic Load Balancing
  • Amazon CloudWatch
  • Activity: Amazon CloudWatch
  • Amazon EC2 auto scaling
  • Lab: Scale & Load Balance your Architecture
  • Activity: Sample Exam Question
  • Knowledge check
This program is suitable for candidates who work in science, research, engineering, data science, computer science, chemicals, oil and gas or any kind of technical facing discipline. No prior cloud knowledge is necessary other than an interest in utilising cloud computing in present/future work, or to further one’s career.

Standard Course Fee: S$3,240

SSG Funding Support

 Course fee

Course fee payable after SSG funding, if eligible under various schemes


BEFORE funding & GST

AFTER funding & 8% GST

Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding)



Enhanced Training Support for SMEs (ETSS)


SCs aged ≥ 40 years old
SkillsFuture Mid-career Enhanced Subsidy (MCES)
(Up to 90% funding)

  • All fees stated are inclusive of 8% GST.
  • NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click  here for more information. 

    Read more about funding
    Dr Leonard Ng

    Assistant Professor Leonard Ng Wei Tat

    Assistant Professor Leonard Ng Wei Tat is a faculty member with the College of Engineering and an AWS Educator. He is the instructor of multiple undergraduate courses including the year 1 course, Introduction to Data Science and Artificial Intelligence, and deep learning in Introduction to Molecular Simulations. Amongst his research work is the high-throughput, cloud-based data acquisition and inverse design for printed photovoltaics.