Upon completion of the course, students will be able to:
- Gain broad awareness of care landscape and ecosystem in Singapore.
- Understand the importance of, and factors leading to smart healthcare.
- Conceptualise and design an end-to-end technological solution to solve a relevant healthcare problem.
- Gain good understanding of constraints and limitations of operationalising smart healthcare.
Students suggested digital ideas on how nurses can avoid administrative lapses when split team measures were enforced during the COVID-19 situation.
Students recommended a platform to assist data integration and planning of duty rosters for healthcare professionals in a hospital, whereby the application could optimise the schedule of healthcare professionals using algorithms in meaningful ways such as maximising rest hours and sending out notifications.
Students looked into the effectiveness of using digital solutions to develop personalised medication lists with illustration to improve patient's medication understanding and adherence.
Upon completion of the course, student will be able to:
- Showcase expertise in executing a project using knowledge acquired from the courses taken from the IS curriculum.
- Experience developing of some technology deliverable for an IT system or proof of concept.
- Experience working in a team environment with a sponsored project (internal, external or self-proposed) using project management skills experience throughout the courses taken in IS.
- Learn about an industry or technology that is related to his selected track not otherwise available in the course curriculum.
- Work on complex and real project used by the project sponsor.
Students developed a new marketplace platform for Zhongguo Remittance to link up their current corporate clients and retail customers, with the aim to improve the user experience and better information access.
By the end of this course, students will learn to:
- Cleanse and prepare data to be in a form adequate for machine learning.
- Outline the steps involved in developing and consuming a machine learning model.
- Develop adequate machine learning models to meet different business objectives.
- Tune the performance of machine learning models.
- Create visualizations to consume the output from machine learning models.
By the end of this course, students will learn to:
- Cleanse and prepare data to be in a form adequate for machine learning.
- Outline the steps involved in developing and consuming a machine learning model.
- Develop adequate machine learning models to meet different business objectives.
- Tune the performance of machine learning models.
- Create visualizations to consume the output from machine learning models.
Upon completion of the course, students will learn:
System development infrastructure
✓ Source code management with Git and GitHub
✓ Task Management with ClickUp
✓ Free document system, Confluence
Data crawling and extraction framework
✓ Extract information from web pages with Scrapy
Data storage system
✓ Choose the right storage architecture based on data characteristics
✓ Use data store and document store for various types of data
Massive data processing frameworks
✓ Install and deploy Hadoop and Spark
✓ Program big data processing logics with Hadoop and Spark
Data interface between modules
✓ Process JSon files
✓ Adopts GraphQL as the data interface
Other open source big data tools
✓ Visualise data results with D3.js
✓ Monitors online data with Prometheus
Upon completion of the course, students will learn:
System development infrastructure
✓ Source code management with Git and GitHub
✓ Task Management with ClickUp
✓ Free document system, Confluence
Data crawling and extraction framework
✓ Extract information from web pages with Scrapy
Data storage system
✓ Choose the right storage architecture based on data characteristics
✓ Use data store and document store for various types of data
Massive data processing frameworks
✓ Install and deploy Hadoop and Spark
✓ Program big data processing logics with Hadoop and Spark
Data interface between modules
✓ Process JSon files
✓ Adopts GraphQL as the data interface
Other open source big data tools
✓ Visualise data results with D3.js
✓ Monitors online data with Prometheus
Upon completion of the course, students will learn:
System development infrastructure
✓ Source code management with Git and GitHub
✓ Task Management with ClickUp
✓ Free document system, Confluence
Data crawling and extraction framework
✓ Extract information from web pages with Scrapy
Data storage system
✓ Choose the right storage architecture based on data characteristics
✓ Use data store and document store for various types of data
Massive data processing frameworks
✓ Install and deploy Hadoop and Spark
✓ Program big data processing logics with Hadoop and Spark
Data interface between modules
✓ Process JSon files
✓ Adopts GraphQL as the data interface
Other open source big data tools
✓ Visualise data results with D3.js
✓ Monitors online data with Prometheus
Upon completion of the course, students will:
- Individually, or in pairs, be able to put together key components of IoT towards building a prototype solution to solve a specific problem A. These hands-on exercises will also help the students in building the IoT prototype for their team project, and train them to be effective IoT solutions architects.
- As a team, given a case scenario B, be able to apply concepts learnt in class to clearly specify the problem statement, describe the IoT solution, and present the actionable wisdom to various key stakeholders. Through short quizzes, this will help the students prepare for the in-class written assignment, and will train them to be effective IoT solutions consultants.
Students developed an IoT prototype, with various occupancy sensors to track, manage and optimize our meeting rooms', shared desks' and discussion corners' utilization; as well as office experience such as noise level.
Objectives:
- Understand concepts related to Cyber-Physical Systems and their essential elements
- Appreciate the unique challenges and complexities faced in computing for the natural world
- Apply the necessary skills to design and develop a Cyber-Physical System
- Create a Cyber-Physical Systems prototype to conquer a real-world societal challenge
- Think deeply and broadly about the various ways in which Cyber-Physical Systems can make immense impact in society, especially to those in need
Students developed digital solutions for elderly residents, especially for those living alone in rental flats, on how they can get access to help with ad-hoc tasks such as fixing electrical appliances, moving furniture, buying groceries etc.
Students developed a chatbot prototype for the SMU-X department, to reduce the number of queries they received from students and the community. They also developed a digital prototype for the makerspace that help track item removals, and facilitate the borrowing (and returning) of makerspace equipment.
Students developed solutions and prototyped for a digital payment system that can be made accessible to groups which do not have access to smartphones and/or internet connection.
TBC