Computer & Information Sciences
Data Science Challenges
Real data-science projects and challenges on Ewance — clean messy datasets, build and evaluate models, and turn raw data into decisions the way a working data scientist does. Solve them to build a portfolio of verified, recruiter-checkable proof you can do the work — not just describe it.
Recommended challenges
- CodeIntermediateNew
Train a Differentially Private Classifier on Medical Records
Use Opacus (PyTorch DP-SGD library). Train a tabular classifier (small MLP + gradient-boosted features) with DP-SGD at the agreed epsilon/delta. Run an accuracy-vs-privacy front…
- Differential Privacy
- Dp Sgd
- Opacus
Privacy-Preserving Machine Learning - DesignSeniorNew
Designing a Data Warehouse for a Renewable Energy Firm
You are given sample data from three sources: energy production logs, weather data, and equipment maintenance records. Your task is to: (1) design a star schema with fact and di…
- Data Warehousing
- Star Schema
- Etl Fundamentals
Database Systems - CodeIntermediateNew
Multi-Turn Dialogue Manager for a Banking Assistant
You receive a transcript dataset of 200 conversations (human-tagged with intent, slot values, and required outcome), a list of 8 supported intents, and tool stubs for 3 backend …
- Dialogue Management
- Intent Classification
- Slot Filling
Question Answering and Conversational Systems - CodeSeniorNew
Real-Time Sentiment Analysis for a Sustainable Fashion Brand
You are to develop a real-time sentiment analysis system for EcoWear. Ingest data from Twitter API (hashtag #EcoWear) and a mock review API, process using Spark Streaming with M…
- Spark Streaming
- Mapreduce
- Nosql
Big Data and Cloud Technologies Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- CodeIntermediateNew
Gaussian Process Regression for Wind Farm Power Curves
You receive 12 months of 10-minute SCADA data (wind speed, air temperature, power output) for 30 representative turbines, plus the manufacturer's published curve. Fit a GP with …
- Gaussian Processes
- Kernel Methods
- Uncertainty Quantification
Probabilistic Machine Learning - CodeIntermediateNew
DPO Fine-Tune for a Domain-Specific Writing Assistant
You receive a base instruction-tuned model checkpoint plus 2,500 preference pairs from editorial reviews (each pair: two grant-application paragraphs, the editor-preferred winne…
- Dpo
- Preference Learning
- Model Finetuning
Machine Learning from Human Preferences (RLHF and Alignment) - CodeIntermediateNew
Build a Vision-Language Search for an E-commerce Catalog
Pick a vision-language encoder (OpenCLIP, SigLIP, or BLIP-2 image-text variant). Index all 600k product images into a vector database (Qdrant/FAISS). Build a query-time pipeline…
- Vision Language Models
- Clip
- Vector Database Basics
Multimodal Machine Learning - ResearchIntermediateNew
Disease-Progression Modelling for a Neurodegeneration Biotech
You receive a curated longitudinal Parkinson's cohort (about 1,200 patients, 4-12 visits each, MDS-UPDRS sub-scores, cognitive assessments, demographics). Fit (1) a linear mixed…
- Disease Progression Modeling
- Mixed Effects Models
- State Space Models
Machine Learning for Healthcare and Biomedicine - Browse challenges
Explore role
Product Manager
Ship product that solves real user problems. Combine user research, prototyping, and stakeholder alignment to turn ambiguous briefs into measurable wins — the role at the centre of modern software teams.
- CodeIntermediateNew
Build a Multimodal Generation Pipeline for a Tourism Operator
You receive 40 sample 30-second videos shot by tour guides, the operator's brand voice doc, and SEO keyword lists for EN/PT/ES. Build a pipeline that (1) extracts a representati…
- Multimodal Generation
- Vision Language Models
- LLM Inference
Generative AI - ResearchBeginnerNew
Run a Human-Preference Study Comparing Two Coding Assistants
Design a blinded paired-comparison study: 12 developer participants, each gets the same 8 realistic coding tasks (refactor, write a function, debug, test), each task is solved b…
- Experimental Design
- Statistical Evaluation
- Human Evaluation
AI Measurement and Evaluation - CodeBeginnerNew
End-to-End Lane Following on a Donkeycar Platform
Use the public Donkeycar Tub dataset (or collect about 30 minutes of driving on the simulator). Train a CNN-policy baseline (the Donkeycar default architecture is fine) that pre…
- End To End Learning
- Imitation Learning
- Pytorch Or Tensorflow
AI for Autonomous Vehicles - CodeIntermediateNew
Fine-Tune a 3B Open-Weight Model for Customer Support Triage
You receive 40,000 anonymized labelled support tickets across 18 categories. Fine-tune a 3B open-weight model using parameter-efficient fine-tuning (LoRA) for the classification…
- Fine Tuning
- Open Weight Llms
- Classification
Large Language Models Build a verifiable portfolio.
Submissions become evidence. Reviewers with shipping experience score against a rubric; the result becomes a credential anyone can verify.
Why Ewance
- CodeIntermediateNew
Plan Warehouse Pick Routes with a Classical Planner
You receive a stylized warehouse map (aisle graph), 30 sample shifts of pick tasks, and the current heuristic's outputs. Write a PDDL domain + problem generator, solve with at l…
- Pddl Modeling
- State Space Search
- Classical Planning
Automated Planning - CodeIntermediateNew
Extract Structured Lease Terms for a Commercial Real-Estate Platform
You receive 500 anonymized lease PDFs and a labelled gold set of 150 leases with the 14 fields filled in. Build a pipeline that does (1) layout-aware PDF parsing (Unstructured, …
- Information Extraction
- Pdf Parsing
- Named Entity Recognition
Linguistic Engineering and Language Technologies - AnalysisBeginnerNew
Spectral Clustering for an Urban-Mobility Operator's Network
You receive 6 months of anonymized O-D trip data (around 4 million trips, around 8,000 virtual stations), the current 9 hand-drawn zones, and the operations team's KPIs (rebalan…
- Spectral Methods
- Spectral Clustering
- Graph Laplacian
Machine Learning on Graphs - ResearchIntermediateNew
Explore the Bias-Variance Trade-off on a Tabular Healthcare Cohort
You receive a 90,000-patient anonymized de-identified tabular dataset (demographics, labs, claims-derived features) and a binary 12-month-readmission outcome. Pick three model f…
- Bias Variance Tradeoff
- Regularization
- Model Selection
Machine Learning - AnalysisIntermediateNew
Network Analysis for Influencer Marketing Campaign
You are a social media analyst at TaskFlow. Using the Twitter API, collect data on at least 200 accounts related to project management and tech leadership (e.g., tweets, followe…
- Network Analysis
- Twitter API
- Influencer Identification
Social Media and Web Analytics - DesignBeginnerNew
Privacy-Preserving Crowd-Density Estimator for Transit Stations
Use a public crowd-counting dataset (e.g., ShanghaiTech or JHU-CROWD) to train a small crowd-density estimator (CSRNet or similar). Wrap it in an on-device pipeline (Python is f…
- Crowd Counting
- Scene Understanding
- Privacy By Design
Visual Intelligence and Visual Reasoning - CodeBeginnerNew
Predict Catalyst Properties for a Green-Hydrogen Pharma Spinout
Use an open catalyst dataset (e.g., Open Catalyst Project subset, or a Materials Project pull) where each candidate has descriptors and a target activity property. Train a tabul…
- Tabular Modeling
- Uncertainty Quantification
- Feature Engineering
AI for Science and Engineering - DesignBeginnerNew
A/B-Test a Recommender Improvement Without Breaking Trust
You receive offline-evaluation results for both the production and candidate models plus aggregate metrics from the last 12 weeks (recipe views, save rate, weekly active users, …
- Experimental Design
- A/B Testing
- Metric Design
Machine Learning in Practice - ResearchIntermediateNew
Hardware-Aware NAS for a Wearable ECG Classifier
You receive a labeled subset of an arrhythmia ECG dataset (about 80,000 10-second windows, 4 classes), a microcontroller latency lookup table (op-level milliseconds) for a Corte…
- Neural Architecture Search
- Hardware Aware Design
- Edge Inference
Edge ML and On-Device Machine Learning - CodeBeginnerNew
Reason about Drone Mission Plans with Probabilistic Logic
Build a small Bayesian network (around 12 nodes) capturing weather, no-fly-zone proximity, battery state, operator certification, and mission risk. Implement exact inference (va…
- Bayesian Networks
- Probabilistic Inference
- Knowledge Representation
Introduction to Artificial Intelligence - CodeIntermediateNew
Build a Feature Store Backbone for a Healthtech ML Team
You receive synthetic wearable telemetry (heart rate, accelerometer, sleep stages) for around 5,000 patients across 90 days, plus the existing scattered feature scripts from the…
- Feature Engineering
- Data Modeling
- Python Or Javascript
Data Engineering and Big Data Systems - CodeIntermediateNew
Fine-Tune a Small Transformer for Legal-Domain EN-DE Translation
You receive a 120,000-segment parallel EN-DE legal corpus and a held-out 1,000-segment test set with reference translations. Fine-tune a small pretrained Transformer (e.g., NLLB…
- Neural Mt
- Hugging Face Transformers
- Fine Tuning
Machine Translation
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
Industry teams behind a decade of practitioner briefs
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Sponsor a challenge and meet candidates through actual work.
Industry teams can shape briefs around the skills they hire for, then evaluate students on rubric-scored deliverables — not resumes.