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
- CodeBeginnerNew
Forecast Hourly Energy Demand for a Microgrid Operator
You receive 24 months of hourly demand, weather (temperature, irradiance), and calendar data for the community. Build a probabilistic forecaster (e.g., quantile regression with …
- Probabilistic Forecasting
- Quantile Regression
- Deep Forecasting
Open coursework - CodeIntermediateNew
Agentic RAG with Context-Window Budgeting
You receive a synthetic dataset of 60 founder-style queries paired with 'workspaces' (each up to 500 documents across 3 source types), plus gold-standard answers and citation li…
- Agentic RAG
- Context Window Management
- Iterative Retrieval
Retrieval-Augmented Generation - StrategyBeginnerNew
Frame an AI Opportunity for a Mid-Cap Insurance Carrier
You receive: line-of-business P&Ls, customer-journey maps, and a list of 18 candidate AI initiatives the operating teams have proposed over the last year. Score each candidate o…
- Ai Strategy
- Opportunity Scanning
- RICE Prioritization
AI for Business and AI Product Management - CodeIntermediateNew
LoRA Fine-Tune a 7B LLM for Legal-Clause Extraction
You receive a curated extraction dataset (2,000 train, 500 val, 500 test contracts with span-level labels across 12 clause types) and a fine-tunable 7B base model (e.g., Llama-3…
- Lora
- Fine Tuning
- Parameter Efficient Tuning
Open coursework 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
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 - AnalysisBeginnerNew
Chunking Strategy Bake-Off for Financial Filings
You receive 40 anonymized 10-K filings and 100 labeled questions split into 50 narrative (e.g., 'what is the company's main risk factor?') and 50 numerical (e.g., 'what was oper…
- Document Chunking
- Semantic Chunking
- Layout Aware Chunking
Retrieval-Augmented Generation - 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 - CodeBeginnerNew
Building a Customer Segmentation Tool for a SaaS Scale-up
You are provided with a JSON file containing user data: user_id, total_logins, days_since_last_login, features_used (count), subscription_tier (free/basic/premium). Your task is…
- Python
- Pandas
- Scikit Learn
Open coursework - Browse challenges
Explore role
Marketing Analyst
Plan and measure campaigns that grow the business. Funnel analytics, attribution, segmentation, and the rigorous measurement that lets marketing defend its budget at the leadership table.
- 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
Open coursework - StrategyIntermediateNew
Design a Compliance Strategy for an AI Robo-Advisor in the EU
Anchor the work on the published EU AI Regulation risk classification (limited vs. high-risk systems) and the European Securities and Markets Authority guidelines on robo-advice…
- Ai Governance
- Regulatory Analysis
- Product Strategy
AI and Quantitative Finance - CodeIntermediateNew
Plan Inventory Replenishment as an MDP for an E-Commerce AI Startup
You receive 18 months of daily demand for 50 representative SKUs at one warehouse plus lead-time and unit-cost data. For one SKU at a time, formulate an MDP with state = (on-han…
- Mdp Modeling
- Value Iteration
- Dynamic Programming
Open coursework - 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…
- Experiment Design
- Statistical Evaluation
- Human Evaluation
AI Measurement and Evaluation 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
Defect Detection on PCBs for a Hardware-AI Manufacturer
Use the publicly-available PCB defect dataset (e.g., DeepPCB or HRIPCB). Fine-tune a small object detector (YOLOv8n or RT-DETR-small) on the 6 defect classes. Evaluate mean Aver…
- Object Detection
- Transfer Learning
- Model Evaluation
Computer Vision - ResearchBeginnerNew
Curate a Domain Lexicon for a Climate-Tech NLP Stack
You receive 5,000 policy documents and a benchmark of 200 documents with manually tagged domain terms. Curate a lexicon of ~1,500 terms with (1) canonical English form, (2) Swah…
- Lexical Resources
- Named Entity Recognition
- Spacy
Open coursework - StrategyIntermediateNew
Designing a BI Strategy for a Regional Retail Chain
Your challenge is to design a BI architecture including a data warehouse (conceptual and logical models), an ETL strategy to integrate data from multiple sources (POS, inventory…
- Data Warehousing
- Etl
- Olap
Business Intelligence - CodeSeniorNew
Video Action Recognition for a Retail Loss-Prevention Startup
Use a public action-recognition dataset (UCF101 + a small curated retail-action subset; the latter is provided synthetic or you can label 50 short clips). Fine-tune a small back…
- Video Understanding
- Action Recognition
- Transfer Learning
Computer Vision - ResearchIntermediateNew
QLoRA Fine-Tune for a Customer-Support Domain Assistant
You receive 8,000 anonymized support ticket pairs (question -> agent response), the company's product documentation (around 600 pages), and a strong RAG baseline already running…
- Qlora
- Fine Tuning
- RAG
Open coursework - CodeBeginnerNew
Implement a Constraint Solver for a Lisbon Tourism Scheduler
Model the next-week schedule as a CSP: variables are (guide, day, slot) assignments; domains are available routes; constraints encode language requirements, max consecutive tour…
- Constraint Satisfaction
- Backtracking Search
- Python
Introduction to Artificial Intelligence - DesignBeginnerNew
Scaling a Sydney D2C Cosmetics Startup's Data Pipeline
You are tasked with designing a cloud-based data pipeline for GlowUp. The pipeline must ingest real-time user events (page views, purchases, returns) from web and mobile apps, p…
- Cloud Computing
- Apache Spark
- Nosql
Open coursework - ResearchSeniorNew
Inductive Logic Programming for a Fraud-Rule Discovery Pilot
You receive a labeled fraud dataset (around 25,000 transactions, around 4% positive class), a feature schema (28 features including device, geo, behavioral history), and a basel…
- Inductive Logic Programming
- Symbolic Ai
- Rule Learning
Open coursework - DesignSeniorNew
Design a Multi-Objective Dynamic Pricing Engine for CityRide
Acting as a data scientist on CityRide's pricing team, design and prototype a dynamic pricing engine that, given the live time, pickup zone, and supply-demand conditions, quotes…
- Reinforcement Learning
- Optimization
- Simulation
Open coursework - AnalysisBeginnerNew
Lower TikTok Acquisition Costs for a Direct-to-Consumer Cosmetics Brand
Working only from the materials provided, diagnose what makes some of the brand's TikTok ads far cheaper to convert than others and recommend how to reshape future creative. Sta…
- Web Scraping
- Content Analysis
- Data Visualization
Open coursework - CodeBeginnerNew
Structured-Output Prompts for Invoice Extraction
You receive 300 real invoice transcripts (already OCR-ed) labeled with 14 target fields, plus the current production prompt and its 12 percent failure log. Design a new prompt u…
- Structured Output
- Json Schema
- Few Shot Prompting
Prompt Engineering - CodeBeginnerNew
Build a Product Knowledge Graph for a Fast-Fashion Retailer
You receive 200 sample SKUs across 4 markets (Spain, Germany, Japan, Brazil) as CSVs with country-specific attribute names. Design an OWL ontology with shared classes for Produc…
- Knowledge Graphs
- Owl Ontology
- Rdf
Open coursework
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.