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.
- CodeBeginnerNew
Refactor a Tangled Java Pricing Engine With Design Patterns
Start from a provided Java 21 codebase with the legacy PricingEngine class, 38 example fixtures (input cart, expected price), and one failing test demonstrating a bug from last …
- Java
- Design Patterns
- Refactoring
Object-Oriented Programming and Design - 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
Site Reliability Engineering - CodeIntermediateNew
Build a CodeQL Query Pack to Catch Logging of Personal Data
Using the provided personal-data source and logging-sink specification, write CodeQL data-flow queries for Java and Python that detect personal data travelling from a source (re…
- Static Analysis
- Codeql
- Data Flow Analysis
Open coursework - DesignSeniorNew
Provably Fair Approximation Algorithm for a Neobank On-Call Roster
Using the roster problem specification (roster-problem-spec), formalize the weekly on-call assignment as a constrained multi-week optimization problem, prove it is NP-hard by re…
- Approximation Algorithms
- Linear Programming
- Np Completeness
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
- 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
Automated Planning - AnalysisBeginnerNew
Build a Public Open-Data Dashboard for Urban Mobility
Pull the city's open-data cyclist-collision dataset (10 years of incidents, geocoded). Define a clear before/after window around the protected-lane rollout, control for traffic-…
- Exploratory Data Analysis
- Data Wrangling
- Geospatial Analysis
Applied Data Analysis and Practical Data Science - CodeIntermediateNew
Prototype a Computer-Vision QA Tool for a Robotics Manufacturer
As a 4-person team, build: (1) a labeling pipeline on around 2,000 component images (Label Studio is fine); (2) a transfer-learned classifier or a small segmentation model that …
- Computer Vision
- Transfer Learning
- Model Deployment
AI Software Engineering Group Project - ResearchSeniorNew
Solve a POMDP for a Healthtech Diagnostic Pathway
You receive a simplified pathway: 5 possible underlying conditions, 8 possible diagnostic tests each with documented sensitivity and specificity, and an outcome payoff matrix fr…
- Pomdp Modeling
- Belief States
- Approximate Solvers
Decision Making Under Uncertainty - 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.
- AnalysisBeginnerNew
Predict 30-Day Churn for a Direct-to-Consumer Cosmetics Brand
Working only from the two materials you are given (a subscriber behavior sample dataset and a one-page stakeholder brief from the head of retention), build a binary classificati…
- Python
- Scikit Learn
- Logistic Regression
Open coursework - CodeFoundationalNew
Build a Best-First Search Solver for a Delivery Startup's Test Lab
Build a Python module exposing uniform-cost search and A-star search on a 2D grid with weighted cells (open road, traffic, no-go). Implement two admissible heuristics for A-star…
- Search Algorithms
- Heuristic Design
- Python
Introduction to Artificial Intelligence - CodeBeginnerNew
GPU Cost Dashboard for an AI Consulting Practice
Pull AWS Cost and Usage Report, GCP billing export, and Lambda Labs invoices into a single Parquet table. Implement a tagging convention (project + client + experiment_id) and a…
- Cloud Cost Attribution
- Etl Pipelines
- Data Modeling
Cloud Computing for Data and ML - 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) 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
Build an End-to-End ML Pipeline for Loan-Default Prediction
You receive 24 months of historical application + outcome data (about 380,000 rows). Build a pipeline using a workflow orchestrator (Prefect, Kedro, or a simple Makefile chain) …
- Ml Pipelines
- Feature Engineering
- Pipeline Testing
Machine Learning in Practice - ResearchIntermediateNew
Build a Generalization-Bound Tutorial for an MLE Onboarding Track
You will produce a Jupyter-notebook tutorial covering (1) sample-complexity intuition, (2) VC-dimension with worked examples for halfspaces and decision stumps, (3) Rademacher c…
- Statistical Learning Theory
- VC Dimension
- Rademacher Complexity
Statistical Machine Learning - CodeIntermediateNew
Detect Atrial Fibrillation from Wearable Heart-Rate Data
Build a Python pipeline that ingests raw PPG + accelerometer at 100Hz, applies motion-artifact rejection using the accelerometer channel, detects beats, computes RR-interval irr…
- Health Sensing
- Signal Processing
- Biomedical Signals
Computational Biology and Health Informatics - CodeIntermediateNew
Build a Vector-Search Backend for an Enterprise AI Knowledge Assistant
You receive a corpus of around 20,000 PDFs (mixed scanned and digital) totalling around 30 GB and a labeled retrieval set of 200 queries with human-judged ground-truth passages.…
- RAG
- Vector Search
- Embeddings
Data Engineering and Big Data Systems - AnalysisBeginnerNew
Community Detection on a Pharma Clinical-Trial Investigator Graph
You receive a pre-fetched dump of around 15,000 trials from a public registry covering oncology over the last 10 years and a mapping of trials to investigator names + institutio…
- Community Detection
- Louvain
- Leiden
Machine Learning on Graphs - CodeBeginnerNew
Ship a Lightweight ML Microservice for an EdTech Reading App
You receive 3 months of session telemetry (around 50M reading events, child-anonymized). Engineer features per session window, train a small classifier (logistic regression base…
- Feature Engineering
- Model Serving
- Containerization
Applied Machine Learning - AnalysisBeginnerNew
Evaluate Speech-to-Text Quality for a Contact-Center Analytics Vendor
You receive 200 anonymized call-recording snippets (2-4 minutes each, ~67 per language) with reference transcripts plus a domain glossary of about 600 product terms. Run all thr…
- Speech Recognition
- Sequence Models
- Model Evaluation
Machine Perception - 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
Design a Negotiation Support Tool for Climate-Tech Supplier Contracts
You will design and prototype a negotiation support tool for a single supplier contract with six issues (price per kg, delivery lead time, minimum order quantity, payment terms,…
- Negotiation Modeling
- Decision Support Systems
- Multi Issue Bargaining
Decision Support Systems and Decision Analysis - 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
Machine Learning (Undergraduate) - CodeSeniorNew
Plan Under Uncertainty for a Warehouse Restocking Robot
You receive a discrete-event simulator of a 1,200-shelf warehouse with calibrated optical-scanning error rates and stock-out cost per shelf. Formulate the restocking decision as…
- Planning Under Uncertainty
- Pomdp
- Monte Carlo Planning
Advanced Robotics - 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
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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