Business
Operations, Supply Chain & Procurement Challenges
Operations, Supply Chain & Procurement challenges put you inside the work of running processes that deliver on time and at cost. You'll build skills in process mapping, flowcharting and BPMN, sharpen capacity planning and scheduling, and use ERP navigation and benchmarking to find where work breaks down.
From there you'll tackle the harder edges — supply chain optimization, Lean Six Sigma DMAIC, 5-Whys & Fishbone root-cause analysis, and Kraljic matrix supplier segmentation — running RFP/RFI orchestration and vendor evaluation the way operations teams actually do. Each challenge you solve earns a verified credential you can share with recruiters.
- ResearchSeniorNew
Benchmark Reward-from-Feedback Methods on a Tabletop Pick-Place
You will use a Franka Panda arm in PyBullet on a 4-object pick-and-place task. For each of the three feedback methods, train a reward model and a downstream policy until converg…
- Reinforcement Learning
- Reward Learning
- Preference Comparison
Human-Robot Interaction - CodeIntermediateNew
Implement Federated Learning for a Government Statistics Office
Use Flower as the FL framework. Simulate 8 municipalities each with a partition of a synthetic wage dataset (provided, 1M rows, EU-Labour-Force-Survey schema). Train a gradient-…
- Federated Learning
- Differential Privacy
- Python Or Javascript
Privacy-Enhancing Technologies - CodeSeniorNew
Diagnose Memory Corruption in a Trading-Firm Order Gateway
Read the 8k-line allocator + order-pool code (provided), plus 3 production crash dumps and 14 hours of pre-crash telemetry. Hypothesize root cause (likely candidates: use-after-…
- Cpp Programming
- Manual Memory Management
- Pointers
Imperative and Low-Level Programming - ResearchIntermediateNew
Compiler Fuzzing Campaign on a Production C Backend
Stand up a Csmith-based generator producing 200,000+ random valid C programs over the campaign. Differential-test the target backend against a baseline C compiler (matching opti…
- Fuzzing
- Differential Testing
- Test Case Minimization
Advanced Compilers and Program Optimization 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
- CodeIntermediateNew
Profile-Guided Optimization for a Production JavaScript Bundler
Read the bundler's existing release-build pipeline (Rust + Cargo). Design and implement a PGO workflow using Rust's profile-guided LLVM PGO: instrument build, training run on th…
- Profile Guided Optimization
- Llvm
- Benchmarking
Advanced Compilers and Program Optimization - CodeIntermediateNew
GPU-Parallel Graph Coloring for an EDA Tools Vendor
Implement Jones-Plassmann graph coloring in CUDA (or HIP if AMD hardware available). Input: a 12-million-node graph in CSR format (compressed sparse row). Output: a valid colori…
- Parallel Algorithms
- Gpu Programming
- Cuda
Parallel and Distributed Algorithms - CodeIntermediateNew
Build a Variant-Calling Pipeline for a Genomics SaaS
Stand up a Nextflow pipeline covering: read trimming, BWA-MEM alignment, duplicate marking, base-quality-score recalibration, GATK HaplotypeCaller variant calling, and variant f…
- Bioinformatics
- Variant Calling
- Workflow Orchestration
Computational Biology and Health Informatics - AnalysisIntermediateNew
Evaluate OS-Level Containment for a Multi-Tenant Edge Platform
Set up reproducible environments for gVisor, Firecracker, and Wasmtime on identical hardware (4 vCPU, 8 GB RAM). Run the platform's 4 workload archetypes (anonymized): API proxy…
- Containment
- Virtualization
- Wasm
Advanced Operating Systems - Browse challenges
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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
Audit BLEU vs. COMET on a Multilingual Customer-Support Corpus
You receive 600 source-translation-reference triples covering 6 languages (EN as source; ES/FR/DE/JA/PT-BR/HI as targets), each scored on adequacy and fluency (1-6) by 3 profess…
- Mt Evaluation
- Neural Mt
- Statistical Analysis
Machine Translation - AnalysisIntermediateNew
Cost-Optimize a Large-Scale Spark Job for an Ad-Tech Platform
You receive the Spark job source (PySpark), the EMR cluster config, and 5 nights of job-history JSON. Profile the job with the Spark UI + EMR metrics, identify the top 3 cost dr…
- Spark Optimization
- Cloud Services
- Cost Engineering
Cloud Computing for Data and ML - CodeBeginnerNew
Build a Bounded Concurrent Queue for a Microservice Worker Pool
Implement a bounded concurrent queue in Go (no third-party queue libraries; standard library + sync primitives only) that supports: Put(item) blocks when full, TryPut(item, time…
- Concurrent Data Structures
- Mutex And Condvar
- Systems Language Proficiency (Go, Rust, C++)
Concurrent and Parallel Programming - AnalysisBeginnerNew
Choose a Hash Table vs Trie for a URL-Shortener Cache
Implement (1) a hash-table cache with linear probing and (2) a compressed trie cache, both with the same eviction policy (LRU). Measure (a) p50/p99 lookup latency, (b) memory fo…
- Hash Tables
- Trie Data Structure
- Benchmarking
Data Structures Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- CodeFoundationalNew
Optimize a Slow Search Function for a Recipe Marketplace
Receive the current Python function (nested loop over (recipe_title, ingredient_list) pairs), the 400k-row dataset (CSV), and 20 representative queries. Step 1: write up the cur…
- Algorithm Analysis
- Big O
- Functions & Data Structures
Algorithm Design and Analysis - 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) - CodeIntermediateNew
Detect Atrial Fibrillation from Wearable Heart-Rate Data
Build a Python pipeline that ingests raw PPG + accelerometer at 100Hz, applies motion-artifact rejection using the accelerometer channel, detects beats, computes RR-interval irr…
- Health Sensing
- Signal Processing
- Biomedical Signals
Computational Biology and Health Informatics - CodeIntermediateNew
Restore Smartphone Low-Light Photos for a Consumer AI App
You receive 200 paired low-light / well-lit phone photos plus 1,000 unpaired low-light photos. Build a pipeline that combines a learned denoiser (e.g. a small DnCNN-style model …
- Image Restoration
- Denoising
- Tone Mapping
Image Processing and Computational Imaging - 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 - AnalysisIntermediateNew
Amortized-Analysis Investigation of a Production Cache
Read the C++ cache source (around 1,800 lines, custom open-addressing with periodic resize-and-rehash). Perform amortized analysis using all three methods (aggregate, accounting…
- Amortized Analysis
- Functions & Data Structures
- Algorithm Analysis
Advanced Algorithms - 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 - CodeIntermediateNew
Multi-Sensor Late-Fusion Prototype for an Indoor AGV
Use the public KITTI dataset (or a similar paired LiDAR+RGB dataset) restricted to static-obstacle classes. Implement a late-fusion baseline: a LiDAR-only detector (PointPillars…
- Sensor Fusion
- Object Detection
- Perception
AI for Autonomous Vehicles - DesignSeniorNew
OTA Firmware-Update Architecture for a 50,000-Device Smart-Meter Fleet
Design a 4-stage OTA architecture: (1) signed image build + manifest, (2) backend rollout (1 percent canary, 10 percent expand, 50 percent expand, 100 percent), (3) device-side …
- Embedded Systems
- Cyber Physical Systems
- Edge Computing
Internet of Things and Cyber-Physical Systems - DesignIntermediateNew
Real-Time Traffic-Sensor Fusion for a Smart Intersection
Design a fusion architecture: per-modality timestamping (NTP-disciplined within 50ms), per-modality confidence weighting (modality-specific noise model), Kalman-filter or partic…
- Sensor Fusion
- Cyber Physical Systems
- Edge Computing
Internet of Things and Cyber-Physical Systems - CodeSeniorNew
Auto-Vectorize an Inner Loop for AVX-512
Profile the existing kernel on a 12-dataset benchmark (provided). Pick one of two strategies: (a) add an LLVM IR-level vectorization pass plugged into the existing pipeline, or …
- Vectorization
- Llvm
- Loop Optimization
Advanced Compilers and Program Optimization - AnalysisIntermediateNew
Benchmark NPUs for an Autonomous Forklift Vision Stack
You receive ONNX exports of the 3 production models, a labeled validation set of 2,000 forklift-camera frames, and developer-kit access to three NPU candidates (anonymized as NP…
- Edge Inference
- Npu Benchmarking
- Onnx Optimization
Edge ML and On-Device 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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