Data ScienceMachine LearningArtificial Intelligence
Student only
This hackathons is only open to students. Double check the event page for more information as this may mean only those from a particular university/country are eligible.
Event Type
in person
262
Participants
23
Est. Projects
Organizers
Alex Johnson
alex@example.org
Jamie Rivera
jamie@example.org
DATA SPRINT — Ultimate Data Science Challenge
by ANVESHAN – Applied Research & AIML Club, NIE Mysuru
Gear up for DATA SPRINT — the most intense, creative, and high-energy data science showdown at NIE!Solve real-world ML problems, craft insights from raw data, build powerful models, and present your story like a pro — all in one thrilling challenge.
This isn’t just another hackathon.It’s your chance to compete, learn, and sprint your way to the top. “Crack. Model. Present. Win.”
What’s the Challenge?
We have curated 5 real-world problem statements, each packaged with:
A dedicated dataset
A clear README
Expectations & output format
All datasets will be released on 1st December, 5 PM via Google Drive.Participants can choose ANY dataset, explore the problem, and build their solution in a Jupyter Notebook (.ipynb).
What You Need to Submit
Every team must submit:A complete Jupyter NotebookCode + EDA + feature engineering + model + evaluationA brief explanation/story behind your approachFinal predictions, plots, metrics inside the notebook
Notebook quality matters — clarity > complexity.
Who Can Participate?
Open to all college students
Any department, any year
Team size: 1 to 3 members
Mode: Hybrid (work online present offline)
Top 3 teams will receive exclusive Machine Learning merch & goodies!
Evaluation Rubric
Your submission will be judged on:
1. Problem Statement understanding
How well you understood the dataset, context & objectives.
2. Data Cleaning & Preprocessing
Quality of handling missing values, outliers, inconsistencies, etc.
3. Feature Engineering
Creativity + relevance of new features and transformations.
4. Modeling & Performance
Approach to model selection, tuning and final metrics.
5. Presentation & Storytelling
Clarity, structure, and ability to communicate insights in the notebook + final presentation.
Rules & Regulations
Only college students may participate.
Teams of 1–3 members only.
Plagiarism = Immediate disqualification.
Use of open-source libraries is allowed.
Each team can present only one problem statement.
All submissions must be made before the deadline (Unstop submissions page).
Notebook must run end-to-end without errors.
Final presentation is mandatory for top shortlisted teams.
FAQs
1. Will all teams get the same datasets?
Yes, 5 datasets will be released, and teams can present their solutions to any one.
2. Can we change problem statements after starting?
Yes, but ensure only maximum 2 final submissions to be made.
3. Is this more of a hackathon or a modelling competition?
A mix. You’ll code, analyze, build models, and present like a DS professional, only .ipynb notebook.
4. Do we need prior ML experience?
No. Beginners can attempt it, and there is a support round on 2nd December.
5. Can we work from home/hostel?
Yes hybrid mode.
6. Will GPUs be provided?
No, bring your own compute (Colab allowed).
About ANVESHAN — Applied Research & AIML Club, NIE
ANVESHAN is NIE’s official research-driven club dedicated to AI/ML, data science, LLMs, and applied research.We conduct workshops, research collaborations, hands-on projects, and events that turn students into innovators.
If you love breaking things, analysing data, and building intelligent systems — you belong here.
Ready to Sprint?
DATA SPRINT is your chance to turn ideas into impact.Dive into the data. Craft your story. Show the judges what you can build.
See you at the starting line.