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
- ResearchSeniorNew
Design a Distributed-Training Strategy for a Mid-Sized LLM
You will write a 5-page design memo that picks a parallelism strategy for fine-tuning a 13B model on 32 H100 GPUs, with a tokens-per-second estimate, a memory-per-GPU calculatio…
- Distributed Training
- Parallelism Strategies
- LLM Training
Machine Learning at Scale - 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 - StrategyIntermediateNew
Design a Post-Editing Workflow for a Cross-Border Fintech
You will design a 4-stage MTPE workflow: (1) source-content readiness check, (2) MT generation with the existing vendor, (3) post-editing with tier-based effort (light vs. full)…
- Mt Evaluation
- Workflow Design
- Neural Mt
Machine Translation - 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 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
- CodeBeginnerNew
Predict Subscription Churn for an EdTech Platform
You receive a CSV with about 18,000 student-month rows: features include login frequency, session length, quiz scores, parent app opens, and plan tier. The target is whether the…
- Supervised Learning
- Logistic Regression
- Gradient Boosting
Machine Learning (Undergraduate) - CodeSeniorNew
Offline RL for Robot-Arm Skill Reuse
You receive 5,000 logged trajectories (state, action, reward, next-state) across 12 tasks, with 9 tasks for training and 3 held out. Train an offline RL algorithm (CQL or IQL re…
- Offline Rl
- Conservative Q Learning
- Skill Reuse
Robot Learning - CodeBeginnerNew
Simulated Annealing for Shift Scheduling at a Hospital
You receive 6 months of anonymized shift demand data, the nurse roster (skills, certifications, contracted hours), and the labor-law hard constraints. Encode the schedule as a 7…
- Simulated Annealing
- Metaheuristics
- Constraint Handling
Evolutionary Computation and Metaheuristic Search - CodeBeginnerNew
Image Search for a DTC Furniture Retailer's App
Use a pretrained vision-embedding model (CLIP ViT-B/32 or DINOv2-small). Index a catalog of around 1,500 furniture images. Curate a small evaluation set of around 50 user-style …
- Image Embeddings
- Vision Transformers
- Image Search
Computer Vision (Undergraduate) - 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.
- 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
Big Data and Cloud Technologies - CodeIntermediateNew
Natural Language Inference for an HR-AI Compliance Tool
Use SNLI/MNLI/ANLI as starting data and curate 200 domain-specific HR examples (synthetic or anonymized) for fine-tuning. Fine-tune a small encoder (DeBERTa-v3-base or similar),…
- Natural Language Inference
- Transformer Models
- Fine Tuning
Computational Semantics - CodeBeginnerNew
Compare MDP Solvers for a Smart-Grid Battery Dispatch Pilot
Model home-battery dispatch as a finite MDP: state is (state-of-charge, hour-of-day, current price tier), actions are charge/hold/discharge with realistic efficiency losses, tra…
- Markov Decision Processes
- Value Iteration
- Policy Iteration
Artificial Intelligence: Principles and Techniques - ResearchSeniorNew
Concept-Activation Vectors for an Autonomous-Vehicle Perception Audit
You receive a trained semantic-segmentation model (8 classes including pedestrian, vehicle, road, sky), an internal validation set of 2,500 driving frames, and a small concept-i…
- Tcav
- Concept Explanations
- Interpretability
Explainable and Interpretable AI 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
- ResearchSeniorNew
SAT-Based Planner for Smart-Grid Demand Response
Encode the dispatch problem (which customers to curtail by how much, respecting per-customer contractual caps and grid-cell totals) as a SAT or MaxSAT instance. Solve 50 histori…
- Sat Based Planning
- Constraint Encoding
- Benchmarking
Automated Planning - DesignBeginnerNew
Build an Attention-Visualization Tool for Translation Quality Audit
You will load a small open-source EN-FR transformer (e.g., Helsinki-NLP Opus-MT-en-fr), build a Streamlit or Gradio demo that lets the user paste English source, see the French …
- Attention Mechanisms
- Neural Mt
- Tool Design
Machine Translation - ResearchIntermediateNew
Fine-Tune a Vision-Language Model for Image Captioning
Take BLIP-2 or LLaVA-1.6 as the base. Fine-tune (LoRA is fine) on a 4,000-image accessibility-curated dataset where each image has a useful caption written by a low-vision-exper…
- Vision Language Models
- Fine Tuning
- Pytorch Or Tensorflow
Multimodal Machine Learning - DesignIntermediateNew
Instrument a Model Monitoring Stack from Scratch
Pick the priority product (recommend the customer-service RAG assistant, around 40k queries/day). Define monitoring signals: input drift (Evidently/NannyML), output quality (LLM…
- Model Monitoring
- Data Drift Detection
- LLM Evaluation
ML Engineering and Production ML - 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
- Neural Networks
- Uncertainty Quantification
Machine Learning for Imaging and Medical Image Analysis - 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 - ResearchIntermediateNew
Prototype a Normalizing Flow for Anomaly Scoring in Climate Sensor Data
You receive 12 months of multivariate sensor traces (8 channels per sensor, hourly). Train a Normalizing Flow (Real NVP or a small Neural Spline Flow) on a clean training window…
- Normalizing Flows
- Density Estimation
- Anomaly Detection
Deep Generative Models - CodeBeginnerNew
Build a Hybrid Search for an Enterprise RAG Knowledge Base
You receive 50,000 internal documents (anonymized policy memos, regulation excerpts, internal FAQs) plus a 300-query benchmark with binary relevance labels for the top-10 return…
- Hybrid Search
- Bm25
- Dense Retrieval
Information Retrieval and Search - 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 - DesignIntermediateNew
Spec Trust-and-Safety Eval Harness for an LLM-Powered Customer-Support Bot
You will spec a 6-page evaluation harness covering: (1) jailbreak test set (about 200 prompts across 6 attack families), (2) PII-leakage probes (about 100 synthetic-customer pro…
- LLM Evaluation
- Red Team Operations
- Pii Detection
Trustworthy AI, Robustness, and Safety - CodeIntermediateNew
Fine-Tune a Transformer for Customer-Support Triage at an Enterprise AI Vendor
You receive 240,000 labeled support tickets across 14 queues, with English, Bahasa Indonesia, and Tagalog. Fine-tune a multilingual transformer encoder (XLM-RoBERTa-base is a st…
- Hugging Face Transformers
- Fine Tuning
- Multilingual NLP
Deep Learning - CodeIntermediateNew
Use Actor-Critic to Auto-Tune a HVAC Control Policy
You receive a Sinergym wrapper around the EnergyPlus model of one floor with 8 thermal zones, weather data for one year, and occupancy schedules. Train a Soft Actor-Critic (SAC,…
- Actor Critic
- Soft Actor Critic
- Continuous Control
Deep Reinforcement Learning
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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