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Learn. Do. Impact.

Using our Learn - Do - Impact methodology, we have not just enabled 4000+ students learn and apply AI skills, but also connected them to industry opportunities.


Project-based learning with real-world challenges + datasets. Guided mentorship from AI Experts.


Students build digital apps that produce tangible real-world outcomes within 2-3 weeks.


Students pitch solutions to industries for project, recruiment, and mentorship opportunities.


900 Non-IT Students Build Forecast Models for Industry & Government

Industry Projects:

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Predictive Maintenance for Solar Panels

Flood Forecasting

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Machine Vision for Document Processing


Dengue Outbreak Forecasting

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Predictive Maintenance for Industry Plants


Energy Optimization for Chiller Plants

NUS Faculty of Science wanted to develop industry-ready AI talents. There were 2 challenges; enabling their non-IT students with practical AI skills and building bridges between the Faculty and industry.

Terra AI planned and initiated IoT Datathon, where students learn practical AI skills and develop AI solutions to solve industry problem statements. At the end of the datathon, the participants were invited by the companies to further develop their solutions as interns.

Since 2017, Terra AI has conducted 3 Datathons with NUS Faculty of Science, with over 900 participants trained to solve various industry challenges using predictive AI. A number of Datathon alumni managed to secure data science career opportunities at global companies, while a few established their own AI startups, because of this program.

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“IoT Datathon is a catalyser for innovation and a breeding ground for the talent of tomorrow. Seeing finalists from different disciplines come together proved once again that diversity wins."
Tommy Leong, Zone President, Schneider Electric


“IoT Datathon is very helpful in helping me understand deep learning concepts. It provides thorough elaboration on building deep learning models. Solving the problem set given provided us realistic perspectives on applying deep learning techniques in real-world scenarios.”
Chandana, Business Analytics Student, working as Data Scientist at San Swee Hock School of Public Health


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“Datathon has provided me with space and resources to learn important technical skills from industry experts, that are crucial for anyone who wishes to excel in Data Science or AI.”
Clarence, Science Student, Scholarship recipient of DSO National Laboratories, Singapore’s Defense Research Agency

NUS Science

​Bridging Global Talents to
Singapore's Deep Tech Ecosystem

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Simulated Trading Profits from Deployed Energy Forecasting Models 

Keith, AI4IMPACT Apprentice, sharing his experience building AI forecasting models during Deep Learning Datathon 2020

SGINNOVATE (, one of the largest deep tech venture capital firms backed by the Singapore Government, is looking to locate and groom talent for their 75+ deep tech startups. 

In 2020, Terra AI launched a series of virtual programs focused on AI talent development. One of them is Deep Learning for Finance, where 450 students and professionals, 85% from non-IT backgrounds, learned deep learning from scratch and developed AI forecasting applications for wind energy trading in real-time, using real data from European wind farms. Within 4 weeks, 50 deep learning applications were developed and deployed, 40 of them generating simulated profits. The entire process (from learning to AI deployment) is powered by Autocaffe.

In the end, the top finalists (40 participants) were shortlisted to participate in SGInnovate's Deep Tech Summation Program, where students work directly with startup founders on deep tech projects. 

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“The experience, skills and knowledge I have learnt from talking these real-world problems will stay with me for a long time, and definitely help me in my final project on applying machine learning at MIT!"
Min Htoo, Year 4 NTU Chemistry undergraduate, a visiting student researcher at Massachusetts Institute of Technology (MIT)


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“We do not have many expectations when entering the datathon since we had little to no experience with deep learning. With teamwork and guidance from the mentors, we manage to emerge as champions.”
John Vijay, Year 2 NUS Business Analytics undergraduate, interning as Machine Learning and Data Analyst at Human Managed


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“We are forced to think deeper when solving a real-world problem. This is normally difficult to pick up on your own, especially for time series. Being exposed to real-world datasets and problem statement gives you the experience you need for solving real-world challenges”
Kaitlyn, NUS Year 2 Physics undergraduate, worked as Summation Intern at Polybee



School Children Build Chatbots for Social Impact

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Created by Cyra, Hidayati, and Saffarian
Labschool Kebayoran Junior High School (Indonesia)
Sichuan University (China)

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Created by Tolganai Kydyrmollaeva and Nurdaulet Balken
High School Student (Kazakhstan)

In June 2020, AI4IMPACT launched Build-A-Bot Bootcamp in Singapore, where students learn how to build their own chatbots. There were 260 participants, some as young as primary school age. Within 2 weeks, the participants successfully created 50 fun chatbots ( through our Learn-Do-Impact methodology.

Inspired by this initial success and many more subsequent chatbot programs held throughout 2020, AI4IMPACT launched CHATBOT UNI ( in 2021. School children worldwide including Singapore, Indonesia and Kazakhstan have created fun and interesting chatbots. Some examples are chatbots to learn sign language, eco-education, or to promote Bali tourism.

We are now working with educational institutions in Singapore and Indonesia to deliver chatbot curricula and train-the-trainer programs to public and private schools.

Cyra Alesha, a Junior High School student from Indonesia, sharing her chatbot learning journey and motivation for building SignLearn

School Children
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