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
- AnalysisSeniorNew
Brain-Tumor MRI Segmentation Bake-Off
You receive a curated public multi-modal MRI brain-tumor cohort (~600 patients, T1/T1c/T2/FLAIR with whole-tumor / tumor-core / enhancing-tumor masks). Train all three architect…
- Medical Imaging
- Segmentation
- Convolutional Neural Networks
Open coursework - CodeBeginnerNew
Build a Robust Image Classifier for a Climate-Tech Satellite Startup
You receive a labeled dataset of about 25,000 Sentinel-2 patches (positive = illegal construction visible, negative = not). The dataset is split by region AND by season so you c…
- Data Augmentation
- Deep Learning
- Pytorch
Advanced Deep Learning - 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
- Transformer
- Fine Tuning
Open coursework - CodeIntermediateNew
Multi-Sensor Late-Fusion Prototype for an Indoor AGV
Use the public KITTI dataset (or a similar paired LiDAR+RGB dataset) restricted to static-obstacle classes. Implement a late-fusion baseline: a LiDAR-only detector (PointPillars…
- Sensor Fusion
- 3d Object Detection
- Perception
Open coursework Develop in-demand professional skills.
Each challenge names the skills it strengthens. Over time, your profile fills with the competences a hiring manager would actually look for.
Why Ewance
- AnalysisBeginnerNew
Mine Association Rules for a Grocery Retailer's Promo Strategy
You receive 6 months of basket-level transaction data (around 22 million baskets, around 18,000 SKUs) plus a category taxonomy. Run association-rule mining (Apriori or FP-Growth…
- Association Rules
- Market Basket Analysis
- Apriori
Data Mining and Knowledge Discovery - CodeIntermediateNew
Build a Forgetting-Curve-Aware Spaced-Repetition Engine
You receive 6 months of practice logs from 8,000 learners (item, timestamp, response correctness, response latency). Fit a learner-personalized forgetting model (logistic per-it…
- Spaced Repetition
- Personalization
- Behavioral Data
Open coursework - AnalysisIntermediateNew
Frame an Energy-Storage Dispatch Decision as a Bayesian Decision Problem
You receive 2 years of hourly spot-price data, 2 years of wind generation data, and a manufacturer's battery degradation model. Frame dispatch as a Bayesian decision problem: mo…
- Bayesian Decision Theory
- Price Modeling
- Back Testing
Decision Making Under Uncertainty - CodeSeniorNew
Triage Brain-CT Stroke Detector with Calibrated Uncertainty
You receive a curated public head-CT dataset (about 2,800 scans, slice-level labels for hemorrhagic stroke) and a held-out 600-scan hospital cohort. Train a 3D CNN or 2.5D slice…
- Medical Imaging
- Convolutional Neural Networks
- Uncertainty Quantification
Open coursework - Browse challenges
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Strategy Analyst
Frame the business question, model the options, build the recommendation. From market sizing to competitive analysis, this role is where strategy consulting meets in-house decision-making.
- CodeIntermediateNew
Designing a Dynamic Pricing Engine for a Ride-Hailing Startup
Your team is given a dataset of historical rides (timestamp, pickup location zone, demand level, available drivers). You must design a pricing algorithm that: (1) uses a multipl…
- Python
- Pandas
- Simulation
Programming for Business Applications - ResearchIntermediateNew
Kernel Methods vs. Deep Learning on a Tiny-Data Drug-Discovery Task
You receive (or download) 3 public ADMET datasets from MoleculeNet (e.g., BBBP, Lipophilicity, FreeSolv). For each, train both: (a) a Gaussian process with a Tanimoto kernel ove…
- Kernel Methods
- Gaussian Processes
- Graph Neural Networks
Advanced Machine Learning - AnalysisBeginnerNew
Detect Fraudulent Refund Requests for a Mid-Market Marketplace
You receive a labeled dataset with buyer history, seller history, shipping carrier, refund reason text, and outcome label (legit / fraud). Train and evaluate at least two classi…
- Classification
- Model Calibration
- Imbalanced Classification
Open coursework - CodeIntermediateNew
Ship a Streaming RAG Endpoint with Caching and Fallbacks
You will build a FastAPI service exposing one POST /chat endpoint that (1) streams tokens via Server-Sent Events, (2) caches identical (system_prompt, query, retrieved_context) …
- LLM API Integration
- Streaming
- Response Caching
LLM Application Development Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- DesignSeniorNew
Build an Edge MLOps Pipeline for a Smart-Agriculture Sensor
You receive a fleet simulator (1,000 simulated sensors with bandwidth + battery profiles), a model registry stub, and the current firmware's model-loading interface. Design and …
- Edge Mlops
- Ota Updates
- Model Versioning
Open coursework - ResearchIntermediateNew
Design a Capability Evaluation for an Open-Weights Coding Model
Pick a recent open-weights coding model (e.g., a Qwen, DeepSeek, or Llama variant). Design an evaluation set of around 40 coding tasks across 4 buckets: standard benign coding, …
- Capability Evaluation
- Safety Evaluation
- LLM Evaluation
AI Safety and Alignment - ResearchSeniorNew
Self-Supervised Pretraining for a Pathology Foundation Vendor
You receive a public pathology dataset (about 80,000 unlabeled whole-slide-image patches plus a labeled 8,000-patch subtype-classification subset across 4 classes). Pretrain a R…
- Self Supervised Learning
- Medical Imaging
- Transfer Learning
Machine Learning for Imaging and Medical Image Analysis - CodeIntermediateNew
Reproducible Patient-Cohort Analysis for a Pharma AI Vendor
You receive a written cohort definition (type-2 diabetes patients on metformin for at least 90 days, aged 40-70) and a target output: 12-month HbA1c change distribution plus a K…
- Reproducible Analysis
- Cohort Analysis
- Survival Analysis
Open coursework - ResearchIntermediateNew
Planning Under Uncertainty for a Last-Mile Delivery Fleet
Build a simulator of the 50-block area with stochastic travel times conditioned on weather and time-of-day. Implement value iteration (for a small state space), MCTS (Monte Carl…
- Planning Under Uncertainty
- Markov Decision Processes
- Monte Carlo Tree Search
Open coursework - DesignIntermediateNew
Design a Continuous Eval Pipeline for an Enterprise RAG Product
Design (and partially build) a continuous-eval pipeline for a RAG system: (1) a structured eval set with at least 50 queries grouped by query class; (2) automated scoring (LLM-a…
- Continuous Evaluation
- LLM Evaluation
- Retrieval Augmented Generation
AI Measurement and Evaluation - AnalysisBeginnerNew
Right-Size a Real-Time Recommendation Serving Cluster
You receive 7 days of request-level telemetry (timestamp, latency, error code, pod) plus the existing Horizontal Pod Autoscaler (HPA) and node-group configs. Analyze traffic pat…
- Model Serving
- Kubernetes
- Autoscaling
Machine Learning at Scale - AnalysisBeginnerNew
Run an A/B Test on Two System Prompts for a Sales Email Assistant
You will (1) design the A/B test (random assignment by rep_id, 50/50 split, 2-week duration), (2) instrument three primary metrics: reply rate (event-based), average tokens per …
- Prompt Evaluation
- Ab Testing
- Metric Design
Open coursework - StrategyBeginnerNew
Spec the AI Stack for an Indoor Service Robot Roadmap
You will research and write a 6-page AI-stack strategy spanning navigation (build vs. buy a SLAM stack), manipulation (in-house RL vs. licensed Vertical-AI APIs), voice (cloud A…
- Ai Strategy
- Build Vs Buy Analysis
- Roadmap Design
Open coursework - CodeIntermediateNew
Build a Domain Instruction-Tuning Recipe for a Legal Coach
You will source instruction data from three streams: ~3,000 synthetic paralegal Q&A generated by a frontier model (anonymized prompts), ~1,500 curated examples from public legal…
- Instruction Tuning
- Lora Fine Tuning
- Data Curation
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.
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