Computer Science
Backend & API Development Challenges
Backend & API Development challenges put you behind the systems that power every product, where you design the contracts other teams build on. You'll work through REST API Design and HTTP Fundamentals, build services with FastAPI, model data with GraphQL schema design, and harden access with OAuth 2.0 / JWT.
From there you'll handle the harder edges — API security (OWASP API Top 10), rate limiting, API versioning, multi-tenancy architecture, and API gateway patterns (Kong, Envoy) — the way platform teams actually run them in production. Each challenge you solve earns a verified credential you can share with recruiters.
- CodeBeginnerNew
Build a Protein Structure Search and Visualization Tool
Build a FastAPI backend wrapping Foldseek's easy-search command, returning top-20 hits with alignment metadata. Build a React frontend with a structure upload widget and a 3D vi…
- Biomolecular Structure
- Bioinformatics
- Full Stack Development
Computational Biology and Health Informatics - CodeIntermediateNew
Ship a Streaming RAG Endpoint with Caching and Fallbacks
You will build a FastAPI service exposing one POST /chat endpoint that (1) streams tokens via Server-Sent Events, (2) caches identical (system_prompt, query, retrieved_context) …
- LLM API Integration
- Streaming
- Response Caching
LLM Application Development - DesignIntermediateNew
Counterfactual Explanations for an Insurance Pricing Model
You receive a trained LightGBM regression model (premium in GBP), the feature schema (28 features, 14 mutable from the customer's side), and 500 sample quotes. Use DiCE (Diverse…
- Counterfactual Explanations
- Dice Ml
- Interpretability
Explainable and Interpretable AI - CodeIntermediateNew
Design Prompt Versioning and Observability for a Coding Assistant
You will (1) design a prompt-registry data model (versions, owners, environments, change log) and implement it in Postgres + a small Python SDK, (2) instrument the assistant to …
- Prompt Versioning
- Observability
- Pii Scrubbing
LLM Application Development Practice your coursework on real scenarios.
Every challenge is shaped from real industry context — not generic exercises. The work mirrors what your degree prepares you for.
Why Ewance
- CodeBeginnerNew
Build a Crop-Disease Classifier for a Smallholder Agritech Startup
You receive a curated 22,000-image cassava-disease dataset across 5 classes (4 diseases + healthy) plus a labeled 1,200-image held-out test set. Train a CNN classifier (start wi…
- Cnn Classification
- Cnn Architectures
- Transfer Learning
Deep Learning for Computer Vision
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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