What is AI Hack

The largest student-organised data science hackathon in the UK. Our flagship AI Hack this year will be a virtual 24h frenzy of hacking and data science. It aims to bring the most forward-thinking and creative student data scientist to solve some of the world's most pressing challenges. Joining us for the hackathon will be a superb experience to

Test your data science skills and to apply them to real projects
Chance to level up your CV for the career goals you aspire towards!
A chance to win part of our £2000 worth of prizes
The experience of obtaining professional mentorship during our event

Form teams, Solve REAL projects and win prizes.

Key Dates

Applications Open
Applications Close
Participants Announced

Applications Open
Applications Reviewed
Participants Announced

Schedule

Opening Address
Hack Begins
Mentor Session 1
Kahoot Data Science Quiz 1

Mentor Session 2
Kahoot Data Science Quiz 2
Submission Deadline on DevPost

Final Round on Teams

Challenges

Kaiko Cryptocurrency Challenge
From Kaiko
Start Challenge
Boston Housing Market Challenge
From Open Source
Start Challenge
Crops Yield Prediction Challenge
From Open Source
Start Challenge

Prizes

Challenge Prizes
Top 3 teams for each challenge will win a prize.
Data Science Quizzes
We will have a few live Data Science Quizzes throughout the Hackathon. Top 3 for each quiz will stand a chance to win a prize.
Social Media Challenge
Top 3 individuals judged based on creativity and number of likes and comments.

Frequently Asked Questions

AI Hack is Imperial College Data Science Society's annual datathon where students get to showcase their analytics skills and meet like-minded aspiring data scientists.

AI Hack will be virtual this year and will take place from 20th of February — 21st of February.

To be able to produce a good submission, we would recommend some familiarity with some of the following things:

Data and software engineering: pandas, dplyr, ggplot, matplotlib, seaborn, PyTorch, TensorFlow, Tableau, parallelisation, docker, GCP or AWS, ipython…
Machine learning: Nonparametric smoothing, random forests, finite and infinite mixture models, XGboost, kernel methods, Gaussian processes, neural networks, autoencoders…
Statistical modelling: frequentist and Bayesian linear models, frequentist and Bayesian hypothesis testing, Monte Carlo methods, bootstrap simulations, PCA…

We recommend Python, but you could also use R, Julia or any language that can be used for scientific computing.

Teams consist of 3-4 people

There will be channel set up before the Hackathon itself for all individual sign ups to meet new people and teammates.

Sadly we won't be able to accommodate people who miss the sign-up date.