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
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 - CodeBeginnerNew
Calibrate a Demand Forecast with Bayesian Confidence Intervals
You receive 24 months of weekly demand for 600 SKUs plus the existing XGBoost point predictions. Fit a Bayesian conformal-prediction layer (or, alternatively, a Gaussian-Process…
- Bayesian Inference
- Uncertainty Quantification
- Conformal Prediction
Probabilistic Machine Learning - CodeIntermediateNew
Automated Planner for a Field-Service Maintenance Schedule
Model the scheduling problem as either PDDL (Planning Domain Definition Language) or a constraint-satisfaction problem using a solver like OR-Tools. Define: actions (visit_site,…
- Planning
- Constraint Satisfaction
- Python Programming
Introduction to Artificial Intelligence (CS Elective) - CodeIntermediateNew
Property-Based Testing to Harden a SEPA Payments Parser
Work only from the four supplied items: the de-identified incident log of the last four quarterly parser failures (incident-log), the representative parser module (parser-module…
- Property Based Testing
- Fuzz Testing
- Go
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
- CodeBeginnerNew
Build a Face-Anonymization Tool for a Civic-Tech Newsroom
Use a pretrained face detector (RetinaFace or YOLOv8-face is fine). Build a Python tool with a Gradio or Streamlit UI that: (1) detects faces in an uploaded photo, (2) shows det…
- Object Detection
- Image Processing
- Opencv
Open coursework - CodeBeginnerNew
Tabular Q-Learning for Warehouse Slotting
You receive a Python discrete-event simulator with state encoded as a 12-dimensional categorical vector (around 8,000 reachable states) and 6 possible slotting actions, plus 2 y…
- Tabular Rl
- Q Learning
- Epsilon Greedy
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 - CodeBeginnerNew
Train a Word-Alignment Model for Low-Resource Catalan-Aranese
You receive a 35,000-sentence Catalan-Aranese parallel corpus plus a 1,200-pair manually annotated word-alignment test set. Train (1) a classic statistical alignment baseline (e…
- Alignment
- Neural Mt
- Low Resource Mt
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.
- AnalysisBeginnerNew
Explain a Credit-Risk Model with SHAP for a Fintech
You receive a trained XGBoost credit-risk model (binary default prediction), the training feature schema (38 features), and a held-out 10,000-sample test set with labels. Comput…
- Shap
- Interpretability
- Fairness Analysis
Explainable and Interpretable AI - CodeBeginnerNew
Build Semantic Search for an Internal Engineering Wiki
You receive a Confluence XML export (~12k pages, ~80 MB of text) and a hand-labeled benchmark of 50 internal queries with ground-truth doc IDs. Chunk and embed the corpus with a…
- Embedding Models
- Vector Search
- Pgvector
Vector Databases and Embeddings - CodeIntermediateNew
Build a Real-Time Streaming Pipeline for Card-Fraud Scoring
Using the provided transaction-event sample, the cardholder feature snapshot, the reference scoring service, and the risk team's experiment specification, build a stream-process…
- Stream Processing
- Kafka
- Flink
Open coursework - AnalysisBeginnerNew
Audit a Hiring-Screening Model for Demographic Bias
You receive: (a) inference API access to the production model (black-box), (b) a 12,000-resume audit benchmark with self-declared gender and age-band labels (consented, GDPR-com…
- Fairness Metrics
- Bias Auditing
- Model Evaluation
AI Ethics, Fairness, and Responsible 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
- AnalysisBeginnerNew
Stress-Test a Hiring-Funnel Model for Bias
You receive a synthetic-but-realistic dataset of 25,000 past applicants with features (years of experience, education tier, prior role tags) and outcome labels (advanced past th…
- Model Evaluation
- Fairness Metrics
- Logistic Regression
Machine Learning (Undergraduate) - CodeIntermediateNew
Build a Feature Store Backbone for a Healthtech ML Team
You receive synthetic wearable telemetry (heart rate, accelerometer, sleep stages) for around 5,000 patients across 90 days, plus the existing scattered feature scripts from the…
- Feature Engineering
- Data Modeling
- Python
Data Engineering and Big Data Systems - AnalysisIntermediateNew
Choose the Right Tenant Containment Strategy for an Edge Platform
Working only from the provided materials, reach and defend a containment recommendation. Read the documented incident record (case-file) to understand what triggered the review …
- Containment
- Virtualization
- Wasm
Open coursework - AnalysisIntermediateNew
Macroeconomic Forecast for a Renewable Energy Investment Firm
You are a junior strategist at GreenCap. Using historical data (10+ years) from Eurostat and the Bank of Spain, develop a VAR or similar model to forecast GDP growth, electricit…
- Multivariate Time Series
- Var Modeling
- Scenario Analysis
Forecasting for Decision Making - AnalysisBeginnerNew
Is the Optimal Vet-Scheduling Feature Computationally Tractable?
Working only from the materials provided — the product feature specification, the de-identified internal record of the customer request, a representative one-day appointment dat…
- Np Completeness
- Complexity Theory
- Algorithm Analysis
Open coursework - ResearchIntermediateNew
Compare Kernel Methods to Trees on a Genomics Classification Task
You receive a curated benchmark of about 12,000 labeled variants with ~120 numerical + ~40 string features. Fit kernel SVMs (RBF, polynomial, string), random forest, and XGBoost…
- Kernel Methods
- Svm
- Tree Ensembles
Open coursework - CodeIntermediateNew
Build a Shareable Immutable List for a Real-Time Document Editor
Using the provided API specification (persistent-list-spec) and the starter module (immutable-list-starter), implement a persistent immutable list supporting get, set, append, p…
- Data Abstraction
- Recursion
- Persistent Data Structures
Open coursework - CodeBeginnerNew
Build a Multi-Level Feedback Queue Scheduler in xv6
Fork the xv6-riscv repository and implement MLFQ in proc.c with 3 priority queues, per-queue time slices (10ms / 20ms / 40ms), priority demotion on slice exhaustion, and a 100ms…
- Operating Systems
- Scheduling
- C Programming
Operating Systems - CodeSeniorNew
Assess Secure Cross-Bank Fraud Computation for a Four-Bank Consortium
Using the de-identified situation in the consortium case file and the two synthetic per-bank datasets (the bank suspicious-account lists and the merchant fraud-marker tallies), …
- Secure Computation
- Mpc
- Cryptography
Open coursework - CodeIntermediateNew
MinHash Similarity Sketch for a Job-Board Deduplication Pipeline
Implement a MinHash signature generator (128 permutations) over shingled job-posting text (5-gram word shingles). Build an LSH banding index (16 bands of 8 hashes each) tuned fo…
- Minhash
- Locality Sensitive Hashing
- Probabilistic Data Structures
Randomized Algorithms - 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 - AnalysisBeginnerNew
Interpretable-by-Design GAM for an Insurer's Claims Triage
You receive an anonymized claims dataset (around 60,000 claims, target: log reserve), a feature schema (22 features), and an existing LightGBM baseline (held-out R^2 of 0.78). T…
- Generalized Additive Models
- Ebm
- Interpretability
Explainable and Interpretable AI
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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