Computer Science
Programming Fundamentals Challenges
Programming Fundamentals challenges put you inside the work of writing code that is correct, readable and fast. You'll build core skills in functions & data structures, object-oriented design and design patterns, work in Python or JavaScript, and learn to do code reading and refactoring the way teams expect.
From there you'll tackle the harder edges — algorithm analysis, complexity analysis, graph algorithms and generics & type systems — pushing into performance engineering, low-latency programming patterns and systems-language proficiency (Go, Rust, C++). Each challenge you solve earns a verified credential you can share with recruiters.
- CodeIntermediateNew
Forecast Energy Demand for a Nordic Renewable Utility
You receive 5 years of hourly residential-segment demand, hourly weather data (temperature, wind, irradiance), and a calendar of public holidays. Build a probabilistic forecaste…
- Time Series Forecasting
- Probabilistic Modeling
- Feature Engineering
Applied Machine Learning - StrategyBeginnerNew
Toil Audit + Automation Sprint for a Platform Team
Week 1-2: every team member logs every toil instance for 10 working days (timestamp, category, duration). Categorize using the Google SRE toil taxonomy (manual, repetitive, auto…
- Toil Reduction
- Automation
- Reliability Engineering
Open coursework - 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
Open coursework - AnalysisIntermediateNew
Compare Kernel SVMs and Gradient Boosting on Imbalanced Tabular Data
You receive a 220,000-row anonymized loan-default dataset with mixed numeric and categorical features and a ~6% positive class. Train and evaluate (1) an RBF-kernel SVM with pro…
- Kernel Methods
- Gradient Boosting
- Model Selection
Machine Learning 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
- CodeFoundationalNew
Tune a Pick-and-Place Controller for a Cosmetics Co-Packer
You receive 4 hours of logged trajectories from the existing controller (joint positions, target poses, miss/success labels) and read/write access to the controller config (YAML…
- Motion Control
- Trajectory Tuning
- Robot Kinematics
Open coursework - 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
Open coursework - AnalysisIntermediateNew
MCMC for Conversion-Funnel A/B Testing at a Marketplace
You receive 6 weeks of per-visitor funnel data (visit, sign-up, trial start, trial-to-paid conversion) split by variant and by acquisition channel (organic, paid social, paid se…
- Mcmc
- Bayesian Hierarchical Models
- Ab Testing
Open coursework - AnalysisIntermediateNew
Audit BLEU vs. COMET on a Multilingual Customer-Support Corpus
You receive 600 source-translation-reference triples covering 6 languages (EN as source; ES/FR/DE/JA/PT-BR/HI as targets), each scored on adequacy and fluency (1-6) by 3 profess…
- Mt Evaluation
- Neural Mt
- Statistical Analysis
Machine Translation - 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.
- CodeBeginnerNew
Demand Sensing for a 40-Person SaaS Scale-Up
You are a growth analyst at FlowMetrics. Using weekly data on signups, trial conversions, website traffic, and marketing spend, develop a model to forecast monthly subscription …
- Time Series Forecasting
- Regression Analysis
- Python
Forecasting for Decision Making - ResearchBeginnerNew
Drug-Repurposing Candidate Screen with Embedding Similarity
You receive (1) a list of 15 known therapeutic candidates (SMILES + ChEMBL identifiers) for a single rare disease, (2) a database of about 4,500 marketed drugs (SMILES + ATC cod…
- Molecular Embeddings
- Similarity Search
- Transfer Learning
Machine Learning for Healthcare and Biomedicine - AnalysisSeniorNew
Field Study: Dynamic Pricing for GreenGrid's Renewable Power Sales
Your task is to investigate price and renewable-supply behavior in a public electricity market and use that evidence to build a dynamic pricing model for GreenGrid. Work only fr…
- Dynamic Pricing
- Optimization
- Risk Management
Open coursework - AnalysisIntermediateNew
Vehicle-to-Everything (V2X) Communication Trial Analysis
Load the anonymised dataset (logged packet RX/TX, PC5 sidelink RSSI, RSRP, SINR, vehicle trajectory, application latency for safety messages). Compute the canonical 3GPP Release…
- C V2x
- Pc5 Sidelink
- Wireless Performance Analysis
Open coursework 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
- AnalysisIntermediateNew
Capacity Planning Model for a Black-Friday Traffic Surge
Pull 18 months of per-service request rate + utilization from Prometheus. Forecast BFCM traffic per service using a baseline + multiplicative seasonal model (Prophet or statsmod…
- Capacity Planning
- Forecasting
- Autoscaling
Site Reliability Engineering - ResearchBeginnerNew
Hyperparameter Search via CMA-ES for a Pharma QSAR Model
You receive a labeled QSAR dataset (around 25,000 compounds, regression on a binding-affinity target), a fixed feature pipeline (Morgan fingerprints + descriptors), and the team…
- Cma Es
- Metaheuristics
- Hyperparameter Optimization
Evolutionary Computation and Metaheuristic Search - CodeBeginnerNew
Diagnose and Fix a Deadlock in a Multi-Threaded Payments Service
Receive the service source (Java 21 + Spring Boot, around 30,000 lines), 4 thread dumps from production deadlocks, and a load harness that reproduces the bug roughly 1 in 50 run…
- Deadlock Analysis
- Locks And Monitors
- Java
Concurrent and Parallel Programming - CodeBeginnerNew
Optimize Wind-Turbine Layout with a Genetic Algorithm
You receive a wind-speed-and-direction time series for the lease area, the polygon boundary, a minimum inter-turbine spacing constraint, and a Jensen wake model. Implement a rea…
- Genetic Algorithms
- Metaheuristics
- Constraint Handling
Open coursework - 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 - ResearchSeniorNew
Probabilistic Numerics for an ODE-Constrained Battery Model
You receive 12 months of charge/discharge cycle data for 50 battery packs from a delivery-van fleet, plus the existing single-particle ODE degradation model (Python). Use a prob…
- Probabilistic Numerics
- Bayesian Inference
- Ode Modeling
Open coursework - CodeBeginnerNew
Build an Embedding-Based Semantic Search for a Legal-Document Corpus
Embed the 380k-document corpus using a multilingual sentence-transformer (e.g. multilingual MPNet or LaBSE). Store embeddings in FAISS or pgvector. Build a search service that r…
- Deep Learning
- Ml Applications
- Python Programming
Machine Learning (CS Elective) - DesignIntermediateNew
Build a Feature Store for a Fintech Fraud Team
You will design a feature-store layer covering 12 representative fraud features (account-level, merchant-level, transaction-level), with both batch (Spark) and online (low-laten…
- Feature Stores
- Data Pipelines
- Spark
Machine Learning at Scale - CodeSeniorNew
Grounded Language for a Robotics Pick-and-Place Demo
Use a tabletop simulator (PyBullet or Isaac Sim, both open) with 5 object types and 5 spatial relations (left of, right of, behind, in front of, on top of). Curate or generate a…
- Grounded Language Understanding
- Semantic Parsing
- Perception
Open coursework - CodeIntermediateNew
Ship an MVP RAG Knowledge Assistant for a Climate-Tech Startup
As a 4-person team across a 6-week sprint, ship: (1) an ingestion pipeline for around 4,000 mixed PDFs and markdown files; (2) a vector store with documented chunking strategy; …
- Retrieval Augmented Generation
- Software Engineering For Ai
- Vector Databases
AI Software Engineering Group Project - CodeFoundationalNew
Build a Simple Neural Network to Read Handwritten Postal Codes
You receive a labeled dataset of about 60,000 handwritten digit images (28x28 grayscale) drawn from Indian postal forms. Build two models from scratch in PyTorch: (1) a 2-layer …
- Neural Networks
- Convolutional Neural Networks
- Pytorch
Open coursework - AnalysisBeginnerNew
Customer-Segmentation Study for a DTC Subscription Box
Use 18 months of anonymized data: order history, churn events, NPS responses, box-rating data, referral activity, marketing-channel attribution. Engineer features (RFM-style + b…
- Unsupervised Learning
- Python Programming
- Ml Applications
Machine Learning (CS Elective)
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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