DAI graduates will be equipped with technical expertise in AI and design innovation skills that can be applied across a range of disciplines, e.g. engineering, healthcare, media, built environment and more.
DAI focuses on using AI to “better design” with an emphasis on application-based courses and design studios where students will work on real-world data via company-sponsored projects.
Apart from our focus in Design and AI topics, DAI has 4 design studios where students have to work on real-world challenges via company-sponsored projects. Hence, there is a lot of hands-on experiential learning at DAI.
These are similar to the exchange experiences and internship opportunities for the other degree programmes. However, it should be noted that only internships in the second summer are counted for DAI.
Design is a critical part of SUTD’s curriculum and research. In DAI, students will focus on application of AI-driven design across user interface/user experience, products, systems, and built environments to create human-centric solutions.
Some possible AI-driven design innovation projects which students may be involved in include designing smarter medical systems for accurate early detection of diseases, predicting urban growth patterns to optimize city planning and safer and more intuitive services.
Design thinking, design innovation, human-centric design, UI/UX, product, systems, built environment, and data-driven design will be taught in the DAI programme.
DAI has four design studios where students have diverse exposure to industry sectors and hands-on experience working on real-world data via company-sponsored projects. You will have the opportunity to engage directly with industries to look at problems, ask the right questions, collect data to analyse and come up with design solutions using AI. You will be exposed to not just AI tools and methodologies but other complementary tools as well.
In Product Design Studio, students will form teams to respond to a “Product Design Challenge” by developing, testing, and presenting a new product or business idea. Students will be introduced to a stage-based design process and be given opportunities to develop their skills in understanding user needs, ideating solutions and making prototypes through experiential learning.
Example Projects
- Unmanned vehicle with sensors and AI for collision avoidance in a warehouse.
- An urban farming unit that changes farming conditions based on real-time data.
In Service Design Studio, students will form a team to respond to a “Service Design Challenge” by conceptualizing, designing, and implementing a new AI-based application to deliver a service. Students will learn web technologies to deploy cross-platform service solutions to various industry needs. The course is offered as a project-based course and managed in a tripartite collaboration involving SUTD, a Technology Expert company, and industries.
Example Projects
- A chatbot that listens to a patient’s symptoms and health concerns, then guides the patient to the correct care based on its diagnosis.
- An application that analyses unstructured medical data (radiology images, blood tests, EKGs, genomics, patient medical history) to give doctors better insight into a patient’s real-time needs.
In Systems Design Studio, students will form a team to respond to a “Systems Design Challenge” by exploring the application of AI-enabled tools in large scale complex systems. Students will be introduced to planning, optimizing and management of organizational systems through simulation models.
Example Projects
- Simulate a system of elevators – What are the best strategies to operate the elevators and minimize average waiting times.
- Simulate a delivery system – Analyse trade-offs between number of drivers; demand; average waiting time; number of orders cancelled; etc.
- Analyse the number of beds in a hospital, number of doctors and nurses, waiting room capacities, pharmaceutical inventories, etc. required during a pandemic.
Students will be conceptualizing and designing applications for the sustainable well-being and smart augmentation of an existing built environment, ranging from cities to building interiors.
Students will get to learn and apply AI-driven techniques in areas such as geospatial data analytics, building information modelling and ambient intelligent interaction.
Example Projects
- An AI application for designing adaptive spatial segregation and differentiated routing to reduce nosocomial infections in hospitals (e.g. separating infected/symptomatic COVID-19 patients and those without).
- An AI application for real-time capturing, tracking, analysis and verifying of building works in construction sites by coupling digital twins and augmented reality (AR) technologies.
The foundation of the DAI curriculum is AI application and design innovation. Depending on the courses, you are required to understand mathematical principles to design AI-driven solutions with software and programming tools and techniques. So, both mathematics and programming are part of the DAI curriculum and you should be comfortable in these areas if you use to pursue the DAI programme.
The pre-requisites will be addressed in the first-year of Freshmore curriculum. DAI courses do touch on mathematics, programming, and design. Hence, proficiency in these areas is an advantage, but not essential as we will cover them in class.
In DAI, the foundations are in AI application and design innovation, we do have courses that involve coding. Depending on the courses that you are taking, some courses may require you to have a good understanding about the mathematical principles besides the coding skills. On top of just coding the AI part from scratch, there are also online tools that you can use especially in the area of generative designs. There are few tools which we can make use of and we are teaching all that in the DAI programme as well. The focus is actually using a lot of methodologies and tools to solve problems and not just mainly on coding.
Some of the programming languages that you will learn in DAI are Python, Ruby, HTML, CSS, and JavaScript.
Some of the software/tools include (but not limited to):
- Autodesk
- Adobe CS
- Rhino 3D
- Paperspace
- Amazon Machine Learning
- ARcGIS Pro
- MIRO
- Python (Keras, scikit-learn, etc)
- Hadoop
- MapReduce
DAI students will be given the necessary background and experience in applied machine learning technology and concepts. Depending on the electives which you will select in Term 6 onwards, you may pursue other concepts like deep learning, natural language processing and others.
DAI’s curriculum was designed and curated by SUTD and several industry partners. We will continue to work closely with industry partners, to keep the curriculum updated to best realise the learning goals of the DAI programme.
DAI focuses on AI applications and design innovation while CSD is very much like a computer science degree where their AI minor focuses on AI computation.
CSD is a computer science curriculum where you will learn the basics of computer science computing and you will then have a choice essentially to specialize. AI is one of the specialisation where you will look at computing algorithms fundamentals related to AI.
DAI is a different programme that looks at using AI as a tool to drive design innovation whether it’s in products, services, systems or built environments. DAI has a more general curriculum that looks at the application of AI.
If you are more interested on the computing aspects or wanting to understand the algorithm of AI then CSD would be the choice for you.
But if you are more interested to look at essentially using AI as a tool to apply across different industries as a designer then DAI would be the course for you.
Currently DAI does not offer a minor.
Currently, students will be able to pursue a minor on top of their major, potentially without having to overload on the number of modules (this depends on the specialisation chosen, if any). Students will get to indicate their preferred minor after they have made their choice of major at the end of Term 3. Both the major and minor requirements must be completed within the normal candidature of the undergraduate programme, i.e. 8 terms.
DAI students cannot take the AI minor as the AI element in DAI is already a major. They are eligible to pursue all other minor programmes listed on https://www.sutd.edu.sg/Admissions/Undergraduate/Minors-and-Tracks
The DAI programme is designed as an interdisciplinary programme that cuts across the existing majors with a focus on design and AI applications. Hence, elements of other majors have already been woven into the DAI curriculum.
DAI offers two specialisation/tracks:
Healthcare Design
Discover how to design healthcare products and services with artificial intelligence and be equipped with fundamental knowledge in medical technologies to develop the next generation of healthcare solutions.
Enterprise Design
Gain skills and knowledge on design, manufacturing, sustainable engineering, and business subjects which are required to make an enterprise successful in our fast-evolving world.
Ideal for those who wish to lead transformational innovations within organisations.
Grading may be based on a combination of homework, design projects, class participation/activity, online quizzes, mid-term tests and final exams, with the weightages varying for different subjects.
Students are graded on a GPA of 5.0. To help ease your transition to the university, all four subjects taken in the first Freshmore term are not graded. From the 2019 cohort onwards, students can also choose an additional two subjects from Freshmore terms 2 and 3 to be ungraded.
DAI graduates can look forward to job roles such as:
- Design Innovator
- Innovation Strategist
- Product Designer
- Business Intelligence Developer
- Data Visualisation Specialist
- Data Scientist
- Applied Machine Learning Engineer
- Robotics Engineer
- User Experience (UX) Designer
- User Interface (UI) Designer
in various private and public sectors including banking and finance, UI/UX agencies, high-tech firms and more.
- Aviation
- Cities/urban planning
- Engineering
- High-technology industries
- UI/UX solution companies
- Financial and banking
- Logistics and travel
- Product Design
- Consulting
- Telecommunications
- Healthcare
- Defence
- Professional Services
- Banking/Financial services
- Marketing/Media
- Government/Statutory Board
- eCommerce
There is currently an acute shortage of AI talents i.e., engineers and product managers who can combine technical expertise in design innovation with the skills to apply AI to other disciplines (such as engineering, healthcare, media, built environment, etc.). This includes AI for making UI design smarter, automating content creation, curation and management including creating abstracts and graphic objects, personalising UX, etc.
Given this, and the anticipated 10,000 tech-related jobs to be created in the next few years through Digital Industry Singapore (DISG), we believe that there will be a very strong demand for AI talents who are well-trained in user experience design, software programming, hardware design, IoT integration to formulate personalised solutions that meet the needs of that industry sector, and society in general.