Code Challenges
Build a working backend, frontend, integration, or data pipeline against a real-shaped spec.
- CodeSeniorNew
Implement a Pipelined RISC-V (RV32I) Core for Automotive Telemetry
Implement a classic 5-stage RV32I pipeline in SystemVerilog. Include data-forwarding from EX/MEM and MEM/WB back to EX, a load-use stall, and branch resolution in EX with a 1-cy…
- Systemverilog
- Risc V
- Pipelining
Digital Systems Design - CodeSeniorNew
Real-Time Sentiment Analysis for a Sustainable Fashion Brand
You are to develop a real-time sentiment analysis system for EcoWear. Ingest data from Twitter API (hashtag #EcoWear) and a mock review API, process using Spark Streaming with M…
- Spark Streaming
- Mapreduce
- Nosql
Big Data and Cloud Technologies - CodeIntermediateNew
Fine-Tune a Sequence-to-Sequence Model for Code-Doc Generation
Take a small base model (CodeT5+ or a distilled CodeLlama-Instruct). Build the dataset by mining around 8,000 high-quality function-docstring pairs from permissively-licensed Py…
- Seq2seq
- Transformers
- Lora Fine Tuning
Neural Networks for NLP - 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 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
- CodeIntermediateNew
Build a Speaker-Diarization Pipeline for a Legal-Tech Startup
You receive 20 hours of de-identified hearing audio with ground-truth speaker labels (4 speaker classes per hearing). Build a speaker-diarization pipeline (pyannote-audio or sim…
- Speaker Diarization
- Speech Recognition
- Pyannote
Speech Recognition and Spoken Language Processing - 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 - CodeSeniorNew
Reverse-Engineer and Patch an N-Day Vulnerability in a Vendor Binary
Receive the vulnerable binary (Linux ELF, x86-64), the public CVE-2025-XXXX advisory + PoC, and the bank's deployment context (RHEL 9, the binary runs as a non-root service). Lo…
- Reverse Engineering
- Binary Exploitation
- Ghidra
Open coursework - CodeIntermediateNew
Port a Monte Carlo Engine to CUDA for an Asset Manager
Profile the CPU MC engine to identify the kernel candidates: path generation (Brownian motion + correlated factors), payoff evaluation, aggregation. Port to CUDA: use cuRAND for…
- Cuda
- Monte Carlo
- Gpu Programming
Open coursework - 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.
- CodeIntermediateNew
Roll Out mTLS Across 80 Microservices with Istio
Install Istio (current LTS) in ambient mode where possible, sidecar mode where ambient is not yet supported by the service. Phase 1: enable PERMISSIVE mTLS namespace by namespac…
- Istio
- Mtls
- Kubernetes
Service Mesh and Microservices Networking - CodeBeginnerNew
Build a Robust Image Classifier for a Climate-Tech Satellite Startup
You receive a labeled dataset of about 25,000 Sentinel-2 patches (positive = illegal construction visible, negative = not). The dataset is split by region AND by season so you c…
- Data Augmentation
- Deep Learning
- Pytorch
Advanced Deep Learning - 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 - CodeBeginnerNew
Image-Classification Model for a Quality-Control Line at a Bottling Plant
Train an image classifier on 8,000 labeled bottle images (3 defect classes + 'ok'). Use transfer learning from a pre-trained backbone (EfficientNet-B0 or MobileNetV3) — the line…
- Deep Learning
- Supervised Learning
- 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
Design an Anti-Corruption Layer for a Legacy Hospital EHR
Map the legacy EHR's HL7 v2 message schema (ADT, ORM, ORU segments) to the new platform's domain (Patient, Encounter, Order, Result). Identify the 6-10 anti-patterns in the lega…
- Anti Corruption Layer
- Hl7 Integration
- Domain Modeling
Domain-Driven Design - CodeIntermediateNew
Simulating Queueing for a 40-Person SaaS Support Team
Build a discrete-event simulation of the ticket handling process: tickets arrive randomly (Poisson), are triaged, then assigned to specialists (tier 1 and tier 2). Calibrate usi…
- Simulation
- Queueing Theory
- Python
Operations Analytics and Optimization - CodeSeniorNew
Train a 3D Object Detector for Highway Trucking
Use the nuScenes or Waymo Open Dataset (open access) as your training and evaluation source. Fine-tune a strong baseline (e.g., CenterPoint or BEVFusion) and define an evaluatio…
- 3d Object Detection
- Perception
- Pytorch
AI for Autonomous Vehicles - CodeIntermediateNew
Train a Multimodal Classifier for Medical Triage
Pick a fusion architecture (early fusion via cross-attention, late fusion via score combination, or a unified multimodal encoder like FLAVA/CoCa). Train on the 14,000 pairs with…
- Multimodal Fusion
- Cross Attention
- Pytorch
Open coursework - CodeSeniorNew
Triage Brain-CT Stroke Detector with Calibrated Uncertainty
You receive a curated public head-CT dataset (about 2,800 scans, slice-level labels for hemorrhagic stroke) and a held-out 600-scan hospital cohort. Train a 3D CNN or 2.5D slice…
- Medical Imaging
- Convolutional Neural Networks
- Uncertainty Quantification
Open coursework - CodeSeniorNew
Profile and Cut Inference Cost on a Recommender at Scale
You receive (1) a frozen ONNX export of the production model, (2) a sample request trace of 24 hours at 1% sampling, and (3) a single A100-class GPU sandbox. Profile with NVIDIA…
- Gpu Profiling
- Model Quantization
- Inference Optimization
Open coursework - CodeIntermediateNew
Secure a LoRaWAN Sensor Network for Cold-Chain Logistics
Read the LoRaWAN 1.0.x vs 1.1 spec (the network runs 1.0.3). Design the new key management: device-unique AppKey + NwkSKey, rotation every 90 days for the warehouse devices (the…
- Lorawan
- Wireless Security
- Key Management
Wireless and Mobile Networks - CodeFoundationalNew
Classify Retail Product Photos for an E-Commerce Marketplace
Use a publicly-available product-image dataset (e.g., Fashion-MNIST extended, or a Kaggle e-commerce subset of around 10k images across 12 categories). Fine-tune a small pretrai…
- Image Classification
- Transfer Learning
- Pytorch
Open coursework - CodeSeniorNew
Build and Evaluate an LSM-Tree Storage Engine in Rust
Your analysis task is to complete the engine and produce an evidence-backed comparison of the two compaction strategies. Start from the 'starter-engine' Rust module and finish t…
- Lsm Tree
- Storage Engine
- Rust
Open coursework - CodeBeginnerNew
Implement a Distance-Vector Routing Algorithm
Implement distance-vector routing in Python: each simulated router maintains a distance vector, exchanges vectors with neighbors every 1 second of simulated time, and updates it…
- Routing
- Distance Vector
- Network Simulation
Open coursework - CodeIntermediateNew
Train a Differentially Private Classifier on Medical Records
Use Opacus (PyTorch DP-SGD library). Train a tabular classifier (small MLP + gradient-boosted features) with DP-SGD at the agreed epsilon/delta. Run an accuracy-vs-privacy front…
- Differential Privacy
- Dp Sgd
- Opacus
Open coursework - CodeIntermediateNew
Generate Synthetic Tabular Data with Privacy Guarantees
Implement DP synthetic data generation: either DP-CTGAN, PATE-GAN, or a marginal-based DP method like PrivBayes / MWEM. Train on the real dataset (around 200,000 transactions, 1…
- Synthetic Data
- Differential Privacy
- Generative Models
Privacy-Preserving Machine Learning
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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