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
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.
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 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
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.