Datathon is a machine learning and data-focused hackathon organized by SLIIT parallel to CodeFest 2020. The key objective is to provide an opportunity for undergraduates to improve their technical capabilities in areas such as data engineering, predictive modelling, recommender systems while providing solutions to the real-world challenging business problems.
Undergraduates will have the chance to team up with like data science enthusiast to use their creativity, analytical thinking, data science skills to analyze the provided dataset, build a predictive model, test and visualize solutions.

 Team Size: Maximum 4 Members

Eligibility:
Those who have already registered in a degree program in a state university or higher education institute in Sri Lanka.

Technologies
Participants are encouraged to use Python / R in Windows platform, but they can come up with any other modelling languages after obtaining prior approval from the organizing committee.

Rules and Regulations:

• A team should consist of maximum 4 members.
• Any number of teams can participate from a university, but a team should only have members from a single university.
• The panels of judges’ decision are the final decision.
• One team can submit only one solution to the given problem.
• Proposed idea should be innovative, and related to Data Science
• All teams must register through the registration link before the closing date
• Students are strongly advised not to use pirated software.
• The winners authorize SLIIT to use their names, photographs, and statements regarding the prizes for advertising or other purposes, without any compensation.

Registration Period: Deadline - 20th Oct 2020 (Registration is now closed!)

Number of Rounds : The competition will be held in two rounds: initial and final.

Technical Sponsor : Zone24x7 (Pvt) Ltd

Cash Prizes :

Winner - 40,000.00 LKR
1^st Runner - 25,000.00 LKR
2^nd Runner - 15,000.00 LKR

Initial Round (On-Line)	Date	02nd of November 2020
	Problem definition	Teams will be given a real-world raw dataset, and they should be able to clean, analyze and build a basic predictive model using Machine Learning and Business Intelligence techniques
	Selection process	Preliminary selection will be based on the outcome of off-campus challenge. Teams will be ordered base on the methodology followed and outcome of the challenge and top 10 teams will be inviting for the final round.
	Evaluation criteria	Based on the Accuracy and the approach used to build the model.
	Special requirements (Optional)	Necessary facilities and equipment should be available to participate in the test conducted through online.
Final Round (On-Line)	Date	Finished
	Problem definition	Based on the problem given by the panel
	Selection process	At the final round, each team should develop a working model within 10 hours for a given challenge. The performance of the model would be assessed by an independent panel of judges.
	Evaluation criteria	Based on the Accuracy and the approach used to build the final model, within ten hours
	Special requirements (Optional)