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
- AnalysisIntermediateNew
Catastrophic-Forgetting Audit on a Domain Fine-Tune
You receive the fine-tuned 7B chemistry model and its base, plus a benchmark basket (MMLU subset, GSM8K, IFEval, a small instruction-following set). Run all 4 benchmarks on both…
- Catastrophic Forgetting
- LLM Evaluation
- Fine Tuning
Fine-Tuning Large Language Models - CodeIntermediateNew
Triage Medical-Imaging Annotations with a Small Vision Model
Train a binary normal/abnormal classifier on the public CheXpert or NIH ChestX-ray14 dataset. Use temperature scaling to calibrate the output, then define abstention thresholds …
- Image Classification
- Transfer Learning
- Calibration
Applied Machine Learning - ResearchSeniorNew
Curriculum RL for a Simulated Drone Inspection Task
You receive a PyBullet-based wind-turbine inspection simulator with parameterizable wind, blade orientation, and sensor noise. Design a 3-stage curriculum: (1) hover near a stat…
- Ppo
- Curriculum Learning
- Deep Rl
Reinforcement Learning - ResearchSeniorNew
Implement an Autoregressive Model for Anonymized Voice-Synthesis at a Defense Vendor
You receive a public-domain speech dataset (LibriTTS subset, around 50 speakers) and a fixed evaluation protocol (speaker-identifiability AUC, emotion-preservation MOS proxy, in…
- Autoregressive Models
- Voice Conversion
- Speech Synthesis
Deep Generative Models Practice your coursework on real scenarios.
Every challenge is shaped from real-world context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- CodeIntermediateNew
Instruction-Tune a Small Model for an Edtech Tutor
You receive a 1.5B base model (e.g., SmolLM-1.7B or Qwen-1.8B), permission to use 2 hours of a rented A100, and a curated seed of around 5,000 math-tutoring dialogues. Augment w…
- Instruction Tuning
- Supervised Fine Tuning
- Dataset Curation
Fine-Tuning Large Language Models - CodeBeginnerNew
GPU Cost Dashboard for an AI Consulting Practice
Pull AWS Cost and Usage Report, GCP billing export, and Lambda Labs invoices into a single Parquet table. Implement a tagging convention (project + client + experiment_id) and a…
- Cloud Cost Attribution
- Etl Pipelines
- Data Modeling
Cloud Computing for Data and ML - CodeIntermediateNew
Train a Sequence Model for Wearable-Telemetry Sleep Staging at a Healthtech
You receive 220 nights of wearable telemetry from 60 subjects with PSG ground-truth labels. Train three sequence models: an LSTM baseline, a 1D-CNN+GRU hybrid, and a small trans…
- Sequence Models
- Lstm
- Transformers
Deep Learning - CodeBeginnerNew
Stack Five Models for a Kaggle-Style Forecasting Bake-Off
You receive a pseudonymized dataset of 24 months of daily shipment volumes across about 200 origin-destination lanes plus weather and holiday features. Train 5 base models, use …
- Ensemble Methods
- Time Series Forecasting
- Feature Engineering
Advanced Machine Learning - 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
Distributional Embeddings for a Multilingual Legal Search
Use a public multilingual corpus (e.g., MultiEURLEX or a subset of EUR-Lex) plus a small hand-built test set of around 100 cross-lingual query-passage pairs. Fine-tune (or evalu…
- Distributional Semantics
- Multilingual NLP
- Sentence Embeddings
Computational Semantics - AnalysisIntermediateNew
Model Patient Pathways with a Hidden Markov Model
You receive de-identified monthly summaries for 8,000 diabetic patients, each row coding the count of primary-care visits, specialist visits, ER visits, new medications, and HbA…
- Hidden Markov Models
- Em Algorithm
- Time Series Modeling
Probabilistic Graphical Models - ResearchIntermediateNew
Evaluate VAEs vs. Diffusion for Synthetic Tabular-Data Generation
You receive a real labeled dataset (around 18,000 anonymized patient records, 32 features, binary outcome) and the team's existing VAE baseline. Train a tabular diffusion model …
- Tabular Diffusion
- Vae
- Synthetic Data
Generative AI - CodeIntermediateNew
Train a Domain-Specific Reranker for a Legal-Tech Search Box
You receive 20,000 (query, document, relevance-label) triples from the firm's contract corpus. Fine-tune a small cross-encoder (e.g., ms-marco-MiniLM-L-6-v2 or BAAI/bge-reranker…
- Cross Encoder Reranker
- Fine Tuning
- Ir Evaluation
Information Retrieval and Search 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
- CodeBeginnerNew
Markov Random Field for Image Segmentation in Crop Monitoring
You receive 60 Sentinel-2 image tiles (10-meter resolution) over 12 vineyards, each tile with per-pixel disease labels from agronomist field walks. Take the consultancy's existi…
- Markov Random Fields
- Graph Cuts
- Image Segmentation
Probabilistic Graphical Models - CodeIntermediateNew
Train a VAE for Synthetic Tabular Data at a Healthtech Startup
You receive a synthetic-but-realistic clinical-trial table (around 50,000 patients, 35 columns, mixed continuous and categorical). Train a tabular VAE (or TVAE/CTGAN as alternat…
- Vae
- Tabular Generation
- Synthetic Data
Deep Generative Models - CodeIntermediateNew
Prescriptive Route Optimization for a Sustainable Fashion Logistics Firm
Your team must develop a decision-support tool that recommends optimal delivery routes for EcoThreads' fleet. You'll need to model the logistics network, incorporate constraints…
- Optimization
- Simulation
- Route Planning
Business Analytics - ResearchIntermediateNew
Visual Question Answering for a Pediatric Radiology Workflow
You receive ~8,000 publicly available pediatric chest X-rays with structured findings labels (anonymized; no PHI access required). Build a VQA pipeline that maps a (image, quest…
- Vision Language Models
- Visual Question Answering
- Lora Finetuning
Visual Intelligence and Visual Reasoning - CodeIntermediateNew
Build a Serverless ETL Pipeline for a Climate-Tech Sensor Fleet
Build the pipeline using managed services only (e.g., S3 + Lambda + EventBridge + Glue, or GCS + Cloud Functions + Cloud Scheduler + BigQuery external tables). Source the data f…
- Serverless Architecture
- Etl Pipelines
- Infrastructure As Code
Cloud Computing for Data and ML - AnalysisBeginnerNew
Model Diffusion of a Hashtag Across a Music-Discovery Platform
You receive 30 days of hashtag-usage data (about 2.4 million events) with account metadata and the follow graph between active hashtag users. Fit an information-diffusion model …
- Diffusion Models
- Network Analysis
- Causal Attribution
Social Network Analysis and Web Science - DesignBeginnerNew
Redesign an AI Chat Sidebar for an Edtech Tutor
You receive a short Loom walkthrough of the live product, a CSV of 5,000 anonymized teacher-flagged sessions, and three teacher interview transcripts. Audit the existing sidebar…
- User Centred Design
- Heuristic Evaluation
- Interaction Design
Human-Computer Interaction for AI Systems - DesignBeginnerNew
Build a Participatory Budgeting Decision Tool for a City Government
You will design and prototype a participatory budgeting tool for one neighborhood pilot with around 30 candidate projects and a fixed EUR 2 million budget. Residents vote on wei…
- Participatory Decision Making
- Decision Support Systems
- Portfolio Optimization
Decision Support Systems and Decision Analysis - 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
AI for Autonomous Vehicles - ResearchSeniorNew
Benchmark Long-Context Architectures on a Legal-Doc Retrieval Task
You receive a public legal-QA dataset (e.g., LongBench's legal split or similar) filtered to documents over 50,000 tokens. Implement or wrap 3 architectures: a sliding-window Tr…
- Long Context Architectures
- State Space Models
- Transformers
Advanced Deep Learning - CodeBeginnerNew
Image-Quality Triage Tool for a Tele-Radiology Network
You receive 10,000 chest-X-ray images with multi-label quality flags (rotation, clipping, motion). Train a small multi-label CNN that outputs a per-flag probability and a single…
- Medical Imaging
- Classification
- Convolutional Neural Networks
Machine Learning for Imaging and Medical Image Analysis - AnalysisFoundationalNew
Pricing Strategy for a Sustainable Fashion Brand
You are a pricing analyst at EcoWear. Using the survey data (simulated with 500 responses) and competitor prices, perform a conjoint analysis or price elasticity analysis. Deter…
- Data Analysis
- Statistics
- Data Visualization
Data Analytics for Business
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
Hiring from this pool?
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.