2023 NUS Summer Camp
Discover the journey of ChatGPT
Commence Time
24-30 July 2023
Summer School Feature
Certificate of Completion from NUS
The top students will be awarded recommendation letter from NUS professor
Top students will receive a S$500 scholarship
Upon joining this summer camp, students will receive a special gift
7 days 8 nights luxury hotel accommodation
Take advantage of the opportunity to learn and experience the local culture abroad
Parents can capture their children's school trips in real time
Gala graduation dinner on the closing day
Itinerary
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Course Schedule
Programme Objectives
Natural language processing (NLP) is one of the dominant applications of AI and machine learning, commonly used for tasks that include text classification, translation, summarizing, answering questions, amongst others. NLP has gained special prominence recently with OpenAI’s ChatGPT, a chatbot capable.
Programme Highlights
This course is taught by our seasoned NUS faculty – Dr Edmund Low from NUS College, who has conducted more than 10 youth programmes since 2020. In the recent Winter programme, he received a teaching effectiveness rating of 4.71 out 5, one of the highest rated instructors.
The programme does not only focus on the technical side – how to build and train an AI model, but also touches on the impact of AI on our society.
Through this programme, we hope to inspire our youth to take up STEM related subjects, especially Computing and AI in higher education, and rethink how AI could potentially benefit their future career choices and personal development.
Pre-requisites
Participants are expected to be able to read, write and communicate in English, as the programme will be conducted in English. There are no subject-matter-specific pre-requisites to attend this programme.
Participants are required to bring their own laptop, charger and universal travel adaptor (for international participants) throughout the duration of the programme.
Who should attend
Pre-University and high school students in Grade 10 - 12, with an interest in Artificial intelligence and its real-world application.
Certificate of Completion
Successful participants who complete all requirements of the programme including passing the assessment will receive a certificate of completion issued by NUS SCALE.
A sample of the certificate of participation can be found here:
Participants from the project team with the highest score for the group project will also receive a commendation letter. A sample is shown below:
Dr Edmund Low, Senior Lecturer, NUS College
Dr Edmund Low is a senior lecturer with the NUS College (NUSC) at the National University of Singapore. He has more than 14 years of academic and professional experience in the use of data-driven tools to answer questions in public health and the environment.
His past projects include the use of programming and visual libraries to develop simulation models for automating workflow processes, and the setting up of remote environmental sensing systems to automate real-time continuous monitoring, for early incident warning.
He currently heads the quantitative reasoning domain, and is also director of the Quantitative Reasoning Centre, at University Scholars Programme (NUS USP). As an educator, Edmund has received both the USP Teaching Excellence Award, as well as the NUS Annual Teaching Excellence Award. Edmund holds a PhD in Environmental Engineering from Yale University.
Q & A
Q: Does student need to learn programming on their own before the programme?
A: No need, we will go through an intro on the specific code syntax used during the course on the first day.
Q: What’s the tool/platform used during programme? Is there any requirement on laptop specs
A: The platform we are going to use is Kaggle notebooks (hosted on the cloud), so there’s no requirement for laptop specs, as long as it can run basic applications such as MS Office, launch a web browser.
Participants are encouraged to install Chrome on their laptop for both Canvas (NUS’s Learning Management Platform) and Kaggle.
Q: What’s the estimated amount of self-study/preparation time outside the classroom?
A: Around 1 – 2 hours each day, which includes reviewing the material covered in class, and preparing for the presentation.
