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.
- AnalysisBeginnerNew
Cluster a Telco's Subscriber Base for a Pricing Refresh
You receive 12 months of anonymized subscriber-level data: monthly minutes, SMS, mobile data, top-up frequency, top-up amount, churn flag, and tenure. Clean and feature-engineer…
- Clustering
- Feature Engineering
- Exploratory Data Analysis
Data Mining and Knowledge Discovery - 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 - 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 - 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 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
- AnalysisIntermediateNew
Model Patient Pathways with a Hidden Markov Model
You receive de-identified monthly summaries for 8,000 diabetic patients, each row coding the count of primary-care visits, specialist visits, ER visits, new medications, and HbA…
- Hidden Markov Models
- Em Algorithm
- Time Series Modeling
Probabilistic Graphical Models - 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 - CodeBeginnerNew
Implement Async Message-Passing for an IoT Gateway
Receive the current gateway source (Python 3.11, single-threaded paho-mqtt client + a serial HTTP forwarder, ~1,100 lines), a sensor-simulator that fans out 500 mock sensors at …
- Async Programming
- Message Passing
- Asyncio
Concurrent and Parallel Programming - CodeIntermediateNew
Design a Force-Controlled Polishing Skill for a Watchmaker
You receive simulated polishing trajectories from the manufacturer's robot, force-sensor logs from 20 master-craftsman demonstrations, and a quality-rubric (mirror finish 1-5) f…
- Impedance Control
- Force Control
- Manipulation
Robotics - Browse challenges
Explore role
Strategy Analyst
Frame the business question, model the options, build the recommendation. From market sizing to competitive analysis, this role is where strategy consulting meets in-house decision-making.
- AnalysisIntermediateNew
Design an Electronic Health Record Data-Quality Audit
Stand up a Python (pandas + DuckDB) audit notebook ingesting the 14M-record extract. Define and run quality checks across four dimensions: completeness (required-field missingne…
- Health Informatics
- Data Quality
- Snomed Ct
Computational Biology and Health Informatics
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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