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
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.
Upon completion of the course, students will be able to:
- Practice problem solving skills.
- Read UML sequence and class diagrams.
- Apply basic concepts of Object Orientation to a given scenario/context.
- Apply good programming practices and design concepts to develop software.
- Appreciate the role of algorithms and in problem solving.
Upon completion of the course, students will be able to:
- Practice problem solving skills.
- Read UML sequence and class diagrams.
- Apply basic concepts of Object Orientation to a given scenario/context.
- Apply good programming practices and design concepts to develop software.
- Appreciate the role of algorithms and in problem solving.
Upon completion of the course, students will be able to:
- Practice problem solving skills.
- Read UML sequence and class diagrams.
- Apply basic concepts of Object Orientation to a given scenario/context.
- Apply good programming practices and design concepts to develop software.
- Appreciate the role of algorithms and in problem solving.
Upon completion of the course, students will be able to:
- Practice problem solving skills.
- Read UML sequence and class diagrams.
- Apply basic concepts of Object Orientation to a given scenario/context.
- Apply good programming practices and design concepts to develop software.
- Appreciate the role of algorithms and in problem solving.
Upon completion of the course, students will be able to:
- Apply the key object-oriented programming and design techniques of abstraction, encapsulation, inheritance and polymorphism to a given scenario.
-Sketch UML class diagrams and sequence diagrams.
-Create and debug programs using the Java programming language.
- Apply good programming practices and design concepts to develop software.
- Integrate object-oriented thinking into application of problem-solving skills.
- Appreciate the role of algorithms and data structures in problem solving.
Students proposed a digital platform for users to source the most cost-efficient rental of construction logistics, that is meant to digitise the entire procurement process of construction logistic reservation, save time, and help users to discover the best price from all suppliers in the market.
This course aims to provide students with a broad coverage and examples of social analytics techniques and trends underlying the current and future development. Upon completion of the course, students will be able to:
- Extract social media data via social APIs and custom scripts.
- Extract social networks from non-network data such as transactional/operation data as well as textual conversations.
- Computationally identify and quantify social influencers.
- Computationally extract and identify trending topics.
- Visualize social networks and text analysis results.
- Deploy custom scripts in Amazon Web Services.
Students proposed ways to find out the most ideal means to engage the target audience by leverage on existing trends and behavioural patterns online, and suggested a digital media approach whereby they can increase awareness using their website and social media platforms to drive traffice to encourage business.
Students analysed the organisation's environment and suggest insights to upcoming product trends, general customer sentiments and strategies to counter competitors.
Students proposed strategies on how to help the company minimise marketing costs as well as increase their probability of successful customer acquisitions for their renting/leasing services through idenfying prospective customers who are likely to be interested in their service from social media data, and improve their current offerings that are aligned to current market trends.
Students analysed on the competitors' advertising strategies, online reviews and customer insights, including doing a sentiment analysis on their products vis-a-vis their competitors. The students also provided an influencer analysis based on social blade data on the proportion of followers, the engagement rate of influencers and who the influencers are (and their effectiveness).
Students analysed the factors that affect the experiences of tourists at hawker centres and attractions, including providing recommendations to tackle problems areas and promote positive experiences.
This course aims to provide students with a broad coverage and examples of social analytics techniques and trends underlying the current and future development. Upon completion of the course, students will be able to:
- Extract social media data via social APIs and custom scripts.
- Extract social networks from non-network data such as transactional/operation data as well as textual conversations.
- Computationally identify and quantify social influencers.
- Computationally extract and identify trending topics.
- Visualize social networks and text analysis results.
- Deploy custom scripts in Amazon Web Services.
This course aims to provide students with a broad coverage and examples of enterprise analytics techniques with special focus on supervised machine learning techniques and applications. Upon completion of the course, students will be able to:
- Work with data from exploration to pattern discover to deployment
- Prepare the data and create new powerful features
- Build powerful machine learning models efficiently
- Assess each supervised model using the appropriate criterion
- Apply robust supervised algorithms such as decision trees, gradient boosting models, forests, neural networks and support vector machines.
- Develop expertise in using SAS machine learning tool called Model Studio in SAS Viya
- Build Machine Learning pipelines in SAS Model Studio
- Deploy and manage machine learning models in production