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.
- CodeIntermediateNew
Out-of-Order Execution Microbenchmark Suite
Design and implement 6 microbenchmarks: ROB capacity probe (varying chain length), load-store queue probe, branch mispredict cost probe, ILP saturation probe, store-to-load forw…
- Out Of Order Execution
- Performance Counters
- Benchmarking
Advanced Computer Architecture - DesignIntermediateNew
Wireless Sensor-Network Design for a Vineyard Microclimate Study
Spec the network: 60 LoRaWAN sensor nodes + 2 gateways (TheThingsStack indoor + outdoor gateway choice), star topology with possible relays. Node hardware: ESP32 + LoRa + sensor…
- Sensor Networks
- Embedded Systems
- Lorawan
Internet of Things and Cyber-Physical Systems - AnalysisIntermediateNew
Cache Coherence Protocol Comparison on a Multicore Simulator
Stand up gem5's Ruby coherence framework with both MESI and MOESI protocols on a 16-core configuration. Run the 6-benchmark suite (provided): producer-consumer queue, false-shar…
- Cache Coherence
- Multicore Architecture
- Simulation
Advanced Computer Architecture - 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 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
- CodeBeginnerNew
Quantize a Vision Model for a Smart-Doorbell SoC
You receive a trained FP32 PyTorch person-detector (mAP 0.74 on a 5k validation set) plus a calibration dataset of 500 unlabeled doorbell frames. Convert to ONNX, then apply pos…
- Quantization
- Model Optimization
- Onnx
Open coursework - 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 - CodeFoundationalNew
Parallelize an Image-Processing Pipeline with Data Parallelism
Your analysis task is to take the serial pipeline module and its configuration (provided as 'serial-pipeline-module'), run it against the representative image batch described in…
- Data Parallelism
- Python
- Multiprocessing
Open coursework - CodeSeniorNew
Port a Numerical Kernel from CPU to GPU for a CFD Simulator
Receive the existing CFD solver (C++17 + OpenMP, around 8,000 lines, the hot kernel is a 7-point stencil sweep over a 512^3 grid), the validation harness, and access to an A100 …
- Gpu Programming
- Cuda
- Parallelism
Open coursework - 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.
- ResearchIntermediateNew
Evaluate a Knowledge-Graph-Augmented Recommender
You receive permission to use the public MovieLens 1M dataset plus a derived item-KG (movie -> genre, director, decade) built from Wikidata. Train two recommenders: a matrix-fac…
- Knowledge Graph Embeddings
- Recommender Systems
- Benchmarking
Open coursework - CodeIntermediateNew
Parallelize a Monte Carlo Risk Engine for a Quant Fund
Starting from the provided single-threaded C++ engine module (engine_scalar.cpp) and the provided benchmarking and equivalence specification (parallelization-spec), profile the …
- Parallel Algorithms
- Shared Memory
- Work Stealing
Open coursework - DesignSeniorNew
Design a Lock-Free Concurrent Skip List for a Time-Series Database
Using the baseline implementation and benchmark harness in the provided code module (baseline-skiplist-rs), design and build a lock-free skip list that replaces the mutex-guarde…
- Lock Free
- Concurrent Data Structures
- Rust Programming
Open coursework - 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 Get recognized by recruiters and employers.
Credentials are blockchain-anchored via LearnCoin — tamper-evident, portable, link-shareable on LinkedIn and beyond.
Why Ewance
- ResearchIntermediateNew
Benchmark Graph-Embedding Methods on a Climate-Network Dataset
You receive a 200M-edge sample of the knowledge graph and a labeled entity-similarity test set (5,000 pairs with relevance labels). Benchmark three methods: a shallow embedding …
- Graph Embeddings
- Graph Neural Networks
- Scalable Ml
Open coursework - CodeSeniorNew
Build a Unikernel for a Privacy-Focused VPN Provider
Choose either MirageOS or Unikraft as the unikernel framework. Build an image running a minimal WireGuard data plane (existing OCaml or Rust WireGuard reference implementation i…
- Unikernels
- Virtualization
- Wireguard
Advanced Operating Systems - ResearchBeginnerNew
Hyperparameter Search via CMA-ES for a Pharma QSAR Model
You receive a labeled QSAR dataset (around 25,000 compounds, regression on a binding-affinity target), a fixed feature pipeline (Morgan fingerprints + descriptors), and the team…
- Cma Es
- Metaheuristics
- Hyperparameter Optimization
Evolutionary Computation and Metaheuristic Search - AnalysisIntermediateNew
Cost-Optimize a Misshapen Kubernetes Cluster
Receive 30 days of cluster metrics (Prometheus + AWS Cost Explorer exports), Helm releases, and PodDisruptionBudgets per namespace. Profile: identify the top 3 cost drivers (lik…
- Kubernetes
- Cost Optimization
- AWS
Cloud Computing - CodeIntermediateNew
Design Error Recovery for a Friendly Compiler
Read the existing parser (recursive-descent, in Rust). Design and implement a panic-mode error recovery strategy with synchronization tokens (statement boundary, end of block, s…
- Error Recovery
- Recursive Descent Parsing
- Diagnostic Design
Compiler Construction - 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 Programming
Privacy-Enhancing Technologies - CodeSeniorNew
Design a Polyhedral Loop-Tiling Strategy for a Tensor DSL
Study the DSL's IR (provided, MLIR-based with linalg-style ops). Choose a tiling strategy (rectangular tiling with cost-modeled tile sizes is the safe baseline; full polyhedral …
- Polyhedral Analysis
- Loop Tiling
- Mlir
Advanced Compilers and Program Optimization - AnalysisIntermediateNew
Benchmark Visual SLAM Stacks for an Indoor Delivery Robot
You receive 8 indoor rosbag recordings (about 90 minutes total) captured by the robot's stereo camera + Inertial Measurement Unit (IMU) plus ground-truth trajectories from an ex…
- Visual Slam
- Sensor Fusion
- Trajectory Evaluation
Open coursework - 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 - AnalysisSeniorNew
Brain-Tumor MRI Segmentation Bake-Off
You receive a curated public multi-modal MRI brain-tumor cohort (~600 patients, T1/T1c/T2/FLAIR with whole-tumor / tumor-core / enhancing-tumor masks). Train all three architect…
- Medical Imaging
- Segmentation
- Convolutional Neural Networks
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) - CodeSeniorNew
Port a Microkernel's Fast Message Path from x86-64 to RISC-V
Starting from the representative fast-path module and its behavioral specification in the provided materials, re-implement the synchronous fast message path for RISC-V 64-bit (t…
- Microkernels
- Ipc
- Risc V
Open coursework
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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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