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.
- 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 - CodeFoundationalNew
Optimizing Inventory for a Barcelona D2C Cosmetics Brand
You are given a CSV file with 6 months of daily sales data for 20 SKUs, including product name, date, units sold, and current stock level. Your task is to write a Python program…
- Python
- Data Cleaning
- Data Analysis
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 - AnalysisIntermediateNew
Benchmark Approximate Nearest-Neighbor Indexes for a Code-Search Startup
You receive a 5 M-vector sample (768-dim, float32) and a 1,000-query labeled benchmark with ground-truth top-50 neighbors per query. Index the same sample in Chroma (HNSW), Qdra…
- Ann Indexes
- Hnsw
- Benchmarking
Vector Databases and Embeddings 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
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 - CodeIntermediateNew
Diagnose Equipment Failures with a Bayesian Network
You receive 90 days of sensor logs (vibration, spindle temperature, coolant flow, ambient humidity), the maintenance log of 180 failure events labeled by root cause, and a short…
- Bayesian Networks
- Probabilistic Inference
- Parameter Learning
Probabilistic Graphical Models - CodeIntermediateNew
Solve a Vehicle-Routing Problem with Tabu Search
You receive a week of anonymized daily VRPTW instances (around 800 orders per day, 120 vehicles, hard delivery windows). Implement tabu search with: a route-insertion constructi…
- Tabu Search
- Metaheuristics
- Vehicle Routing
Evolutionary Computation and Metaheuristic Search - 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 - 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.
- DesignIntermediateNew
Design a Continuous Eval Pipeline for an Enterprise RAG Product
Design (and partially build) a continuous-eval pipeline for a RAG system: (1) a structured eval set with at least 50 queries grouped by query class; (2) automated scoring (LLM-a…
- Continuous Evaluation
- LLM Evaluation
- Retrieval Augmented Generation
AI Measurement and Evaluation
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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