LearnAI | National AI Student Challenge 2024

National AI Student
Challenge 2024

The National AI Student Challenge 2024 offers 3 Challenge Tracks, each with its own eligibility criteria and requirements.

Step 1: Please carefully review the eligibility criteria for each of the Challenge Tracks below.
Step 2: Kindly ensure that you meet the eligibility criteria before selecting your preferred Challenge Track.
Step 3: Each Challenge Track has limited space. Secure your spot by applying promptly. Assignments are first-come, first-served. Successful applicants will be notified by 21 February 2024.

Mission:	Predict pets’ adoption rate and understand adopter’s preferences to allow one of the leading pet adoption portals in Malaysia be more self-sustainable and to increase revenue through advertising and sponsorships.
Skills and Tools:	• Data Science and AI / ML knowledge • Python Programming Language • Software Engineering • Open-source Libraries
Deliverables:	• Exploratory Data Analysis (EDA) Interactive Notebook (.ipynb) • End-to-end Machine Learning Pipeline • Details of deliverables will be shared during the briefing
Eligibility:	• You must be a full-time student currently enrolled in a local Secondary School, Integrated Programme (IP) School, International School, Independent School, Junior College, Institute of Technical Education, Polytechnic, University or Full-time National Serviceman (NSF). • Participation is on an individual basis only.
Evaluation:	• Appropriate data processing & feature engineering • Appropriate use and optimization, and explanation of choice algorithms / models • Appropriate use and explanation of evaluation metrics • Good understanding of DS, AI / ML
Prizes:	Internship placements for Top 3 Winners

Mission:	Develop or fine tune a large language model (LLM) (maximum of 13B parameters) with Amazon Sagemaker Jumpstart, that can outperform a reference LLM model and other competing models in a quiz-based evaluation.
Skills and Tools:	Python skills are optional. Your core tool must be Amazon Sagemaker. Access and training of use of Sagemaker will be provided. However, you are allowed to use any other open-source resources to enable the development or fine tuning of the LLM model.
Deliverables:	A fine tuned or trained large language model (max 13B parameters) submitted for competitive evaluation by deadline. Initial dataset will be provided during training workshops. Other datasets will not be provided. You will need to build your own datasets that can best finetune your LLM model to win.
Eligibility:	• Each member of the team must be a full-time student currently enrolled in the Institute of Technical Education, Polytechnic or University based in Singapore. • Each team must consist of one (1) team leader AND between one (1) and four (4) team members.
Evaluation:	• Top 10 teams on an open leaderboard with best performing models will be selected for finals. Details of evaluation criteria will be shared during the briefing. • 10 teams will compete in the finals quiz-based evaluation.
Prizes:	• Internship placements for Top 3 Winning Teams • Amazon vouchers to be won by Top 5 Teams

Mission:	Develop a Large Language Model (LLM)-powered application using prompt engineering that addresses a real-world problem statement.
Skills and Tools:	• Prompt Engineering • Python Programming Language • Any open-source resources to enable the development of the LLM-powered application
Deliverables:	• One slider of the developed LLM-powered application, including description real-world problem statement • Video demonstration of the LLM-powered application
Eligibility:	• Each member of the team must be a full-time student currently enrolled in a local autonomous university and have completed at least their first year. • Participants may sign-up individually or as a team. A team must contain one (1) team leader and not more than three (3) team members.
Evaluation:	• Impact of the solution • Novelty of the solution • Performance and efficiency of the solution • Presentation
Prizes:	AISG AI Internship Programme (AIIP) placements for Top 3 Winning Teams

Date	Time	Remarks
15 Jan	12.00pm	Registration Begins
14 Feb	12.00pm	Registration Deadline
15 Feb – 21 Feb	Offline	Assignment of Challenge Track
24 Feb	10am – 12pm	[Track 1 (AIP) & Track 3 (CSIT)] Welcome Session + Meet-the-Challenge-Partner Session (In-person)
24 Feb	10am – 1pm	[Track 2 (AWS)] Welcome Session + Meet-the-Challenge-Partner Session (In-person)
20 Mar	12.00pm	Submission Deadline
21 Mar – 22 Apr	Offline	Shortlisting the Top 5 Grand Finalists per Challenge Track
23 Apr	12.00pm	Grand Finalists Revelation
11 May	9am – 5pm	Grand Final Presentation @ AI Student Developer Conference 2024 (In-person)

Thank you for your interest in participating in this challenge. Due to overwhelming response, application to the challenge is now closed.

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