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.
- AnalysisIntermediateNew
Optimize Stop-Loss Policies with Dynamic Programming at a Quant Fund
You receive five years of daily PnL series for 12 momentum strategies plus a small set of state features (rolling vol, drawdown, regime indicator). Calibrate a discrete Markov m…
- Dynamic Programming
- Backward Induction
- State Modeling
Open coursework - AnalysisIntermediateNew
Build a Bayesian Credit-Scoring Model for an Emerging-Markets Fintech
You receive an anonymized snapshot of about 30,000 historical applications with features (income proxy, tenure on platform, prior loans, region) and the binary default outcome. …
- Bayesian Learning
- Credit Scoring
- Model Evaluation
Advanced Machine Learning - 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 - AnalysisBeginnerNew
Diagnose Churn Drivers for a B2B SaaS Workflow Tool
You receive three CSV exports: 18 months of weekly product-usage events for about 1,800 accounts, the full support-ticket history, and account firmographics (industry, size, pla…
- Exploratory Data Analysis
- Data Wrangling
- Feature Engineering
Applied Data Analysis and Practical Data Science 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
- CodeSeniorNew
Build a Distributed Shared Memory Layer Over RDMA for Risk Engines
Build a Distributed Shared Memory library in C++ that exposes a small region interface — allocate a shared region, read from it, write to it, and free it — starting from the pro…
- Distributed Systems
- Rdma
- Consistency Models
Open coursework - AnalysisBeginnerNew
Spectral-Analyze Wearable Sleep Data for a Healthtech Pilot
You receive 30 nights of wearable data per 25 volunteers, with polysomnography-derived ground-truth stages (Wake / NREM / REM). Engineer spectral features (delta, theta, alpha, …
- Spectral Analysis
- Feature Engineering
- Wavelet Analysis
Open coursework - CodeSeniorNew
Cache-Optimize a Graph-Analytics Kernel for a Social Platform
Receive the existing kernel (C++ + OpenMP, around 1,200 lines), the 1.8B-edge graph (CSR format, around 14GB), and target hardware (dual-socket AMD EPYC 9354, 384GB DDR5, 256MB …
- Cache Optimization
- Graph Algorithms
- Memory Hierarchy
Performance Engineering of Software Systems - DesignIntermediateNew
Rate and Reduce Technical Debt in a Telecom OSS Codebase
Design a SQALE-based technical-debt rating and improvement proposal for Lumera Telekom's OSS. Using only the static-analysis findings export, the module inventory and rating gri…
- Sqale Method
- Technical Debt
- Code Quality
Open coursework - Browse challenges
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Pricing Strategist
Set the price that captures value without leaving sales on the table. Demand modelling, willingness-to-pay research, and the disciplined experimentation that turns pricing into a competitive advantage.
- CodeIntermediateNew
Build an Anomaly-Detection Pipeline for Pharma Cold-Chain Logistics
You receive 18 months of shipment telemetry (around 60,000 shipments, around 12 million sensor readings) plus a hand-labeled set of 1,200 incidents (mix of true excursions, sens…
- Anomaly Detection
- Feature Engineering
- Time Series
Data Mining and Knowledge Discovery - ResearchIntermediateNew
Quantify Distribution Shift for a Climate-Risk Model
You receive the model artifact (a gradient boosted regressor predicting expected annual loss per property), 2010-2020 training data, and a 2021-2024 holdout. Quantify covariate …
- Distribution Shift
- Covariate Shift
- Concept Drift
Open coursework - CodeSeniorNew
Implement a Proof-of-Stake Consensus Mechanism in Rust
Read the Casper FFG paper (Buterin + Griffith, 2017) and design a simplified PoS implementation in Rust: 21 validators, 32-slot epochs, two-phase finality (justify, then finaliz…
- Consensus Algorithms
- Blockchain Protocols
- Rust
Blockchain and Decentralized Systems Engineering - CodeSeniorNew
Multilingual RAG for a European Customer-Support Knowledge Base
You receive 6,000 documents in 4 languages (mix of FAQs, parts catalogs, repair procedures) plus 120 labeled queries (30 per language) with gold source documents. Build a multil…
- Multilingual RAG
- Cross Lingual Retrieval
- Multilingual Embeddings
Open coursework Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- 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 - CodeIntermediateNew
Hierarchical Plans for an Aerospace Maintenance Crew Scheduler
You receive a synthetic week of 80 work orders with hierarchical decompositions, technician certifications, and shared-tool constraints. Implement an HTN planner (PyHOP or HDDL …
- Htn Planning
- Domain Modeling
- Constraint Handling
Automated Planning - 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
Build a Hybrid Recommender for a Niche Consumer-AI Music App
You receive listening events (around 240 million plays) plus a content embedding per track (audio + curator tags). Build a collaborative filtering model (ALS or implicit-feedbac…
- Recommender Systems
- Collaborative Filtering
- Content Based Filtering
Data Mining and Knowledge Discovery - CodeBeginnerNew
Prototype a Multimodal Visual-Question-Answering Demo
You will use a small open-source vision-language model (e.g., LLaVA-1.5-7B or PaliGemma) and prompt-engineer it for the warehouse-VQA task. Build a Gradio web demo. Construct a …
- Vision Language Models
- Multimodal Perception
- Prompt Engineering
Open coursework - CodeSeniorNew
Min-Cost Max-Flow for Cloud Workload Placement
Receive 30 days of anonymized placement requests (workload CPU/memory shape, affinity rules), zone capacity per day, and cross-zone bandwidth costs. Model the placement as a min…
- Network Flows
- Algorithm Analysis
- Graph Algorithms
Advanced Algorithms - CodeIntermediateNew
Agentic RAG with Context-Window Budgeting
You receive a synthetic dataset of 60 founder-style queries paired with 'workspaces' (each up to 500 documents across 3 source types), plus gold-standard answers and citation li…
- Agentic RAG
- Context Window Management
- Iterative Retrieval
Retrieval-Augmented Generation - AnalysisIntermediateNew
Build a Technical Debt Register for a Legacy Banking Monolith
Run 8 structured 45-minute engineer interviews (template provided) capturing one debt item per pain point with reproducible evidence. Run SonarQube against the monolith for a qu…
- Technical Debt
- Debt Quadrant
- Code Quality
Technical Debt Management - 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) - CodeIntermediateNew
Build an Internal-Tools Agent for a Mid-Cap Enterprise
You receive OpenAPI specs for 4 mock internal APIs and 30 reference question-answer pairs spanning easy lookups and multi-tool chains. Build the agent using an LLM tool-use fram…
- LLM Agents
- Tool Use
- Agent Evaluation
AI Agents and LLM-Based Agents - CodeIntermediateNew
Tune a Multicore Pipeline with NUMA-Aware Sharding
Receive the current worker (Rust, around 8,000 lines, uses rayon for its parallelism), the host (2-socket AMD EPYC 9354, 64 cores total, 384GB DDR5), and a benchmark query workl…
- Parallel Performance
- Numa
- Rust
Advanced Concurrency and Parallel Computing - CodeIntermediateNew
Kill Surviving Mutants in a Travel Pricing Service
Work entirely from the provided pricing module (pricing-module) and its existing test suite (existing-tests), using the scenario facts in the briefing document (challenge-brief)…
- Mutation Testing
- Java
- Junit
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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