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Introduction
This course is designed for Scientists, Engineers, and Technical Managers interested in leveraging cloud computing for their professional pursuits. It caters to those in technical roles and 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 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.
This course is a direct route to attaining the AWS CLOUD PRACTITIONER CERTIFICATION. Upon successful completion of the lesson, learners will be issued with a coupon to attempt the AWS certification examination and will also receive an "NTU Certificate of Completion".
Learners will also be invited to exclusive networking opportunities with AWS professionals during the course.
Course Availability
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Date(s): 13 to 15 May 2024
Time: 9:00AM to 5:00PM
Venue: NTU@one-north campus, Executive Centre (Buona Vista)
Registration is closed.
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.
- Course objectives and overview
- AWS Certification exam information
- AWS documentation
- Introduction to cloud computing
- Advantages of the cloud
- Introduction to AWS
- Moving to the AWS Cloud
- Activity: Sample Exam Question
- Knowledge check
- 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
- AWS global infrastructure
- Demo: AWS global infrastructure
- AWS services and service categories
- Activity: AWS Management Console Clickthrough
- Activity: Sample Exam Question
- Knowledge check
- AWS shared responsibility model
- Activity: AWS Shared Responsibility Model
- AWS IAM
- 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
- 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
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Knowledge check
- 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
- AWS EBS
- Demo: Amazon Elastic Block Store Console
- Lab: Working with EBS
- AWS S3
- Demo: AWS S3 Console
- AWS EFS
- Demo: AWS EFS Console
- AWS S3 Glacier
- Demo: AWS S3 Glacier Console
- Activity: Storage Technology Selection
- Activity: Sample Exam Question
- Knowledge check
- 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
- 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
- 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 course is targeted at individuals considering careers switches, looking to enhance their tech skillsets, are looking for accelerated paths to AWS certification, looking to pursue more advanced AWS Certification and 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$3,270.00
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SSG Funding Support |
Course fee |
Course fee payable after SSG funding, if eligible under various schemes |
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BEFORE funding & GST |
AFTER funding & 9% GST |
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Singapore Citizens (SCs) and Permanent Residents (PRs) (Up to 70% funding) |
S$3,000.00 |
S$981.00 |
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Enhanced Training Support for SMEs (ETSS) |
S$381.00 |
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SCs aged ≥ 40 years old |
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- Standard course fee is inclusive of GST.
- NTU/NIE alumni may utilise their $1,600 Alumni Course Credits. Click here for more information.
Mr Andre Low
Andre Low is a graduate student at the Nanyang Technological University, Singapore. He obtained his Bachelors in Materials Science and Engineering from Nanyang Technological University in 2021. Andre is currently researching on multi-objective optimization strategies towards accelerating materials discovery in high-throughput platforms and self-driving labs across different materials systems such as nanoparticles, polymers, and perovskites. As an instructor for the AWS Cloud Practitioner course, his meticulous approach and innovative thinking in materials science ensure participants gain an insight-driven and modern perspective on cloud computing applications.
Dr Maung Thway
Dr Maung Thway is a research fellow at School of Materials Science and Engineering of Nanyang Technological University. Thway is currently researching on methodologies that will accelerate materials discovery. He received the PhD degree in electrical engineering from National University of Singapore, Singapore, in 2020. His research during PhD candidature included perovskite/Si and III-V/Si tandem solar cell: fabrication, characterization, and integration. Bringing his keen understanding of both electrical engineering and material science, Thway offers a robust and analytical perspective, ensuring AWS Cloud Practitioner course participants benefit from a meticulous and research-driven approach to cloud computing.
Dr. Jose Recatalà Gómez
Dr. Jose Recatalà Gómez is currently a research fellow at the Nanyang Technological University, Singapore. He obtained his PhD degree from the University of Southampton in 2021, where he focused on rapid synthetic routes and descriptor-based design of thermoelectric chalcogenides. He combines materials informatics and machine learning with high-throughput experiments to discover new solid-state inorganic materials for energy and environment-related applications. As an AWS Cloud Practitioner course instructor, he brings a rigorous scientific methodology and a profound understanding of the latest technological innovations in both cloud computing and materials science.
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.
