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
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
- 3d Object Detection
- Perception
AI for Autonomous Vehicles - ResearchSeniorNew
Trajectory Prediction Model for Urban Robotaxis
Use the Argoverse 2 motion-forecasting dataset (open access). Train an LSTM baseline + a transformer challenger (e.g., a small Wayformer or HiVT). Evaluate on minADE/minFDE (min…
- Trajectory Prediction
- Transformer Models
- Evaluation
AI for Autonomous Vehicles - CodeIntermediateNew
Plan Warehouse Pick Routes with a Classical Planner
You receive a stylized warehouse map (aisle graph), 30 sample shifts of pick tasks, and the current heuristic's outputs. Write a PDDL domain + problem generator, solve with at l…
- Pddl Modeling
- State Space Search
- Classical Planning
Automated Planning - CodeSeniorNew
Bulk Synchronous Parallel PageRank for a Web-Graph Lab
Working from the lab situation record (`lab-case-file`), implement 25 iterations of PageRank under a Bulk Synchronous Parallel (BSP) model using either Apache Spark with GraphX …
- Parallel Algorithms
- Bsp
- Graph Algorithms
Open coursework 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
- AnalysisIntermediateNew
Compare ML Compiler Stacks on a Vision Backbone
Take a frozen ResNet-50 (or similar) in ONNX. Compile and benchmark it via TensorRT on Jetson + GPU, ONNX Runtime on all three, OpenVINO on x86 CPU, and IREE on ARM if time allo…
- Ml Compilers
- Tensorrt
- Onnx
Machine Learning Systems - 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 - DesignIntermediateNew
Add Profile-Guided Optimization to a Production JavaScript Bundler
Design and implement a profile-guided optimization workflow for the bundler using Rust's LLVM-based PGO: an instrumented build, a training run over the eight-project benchmark c…
- Profile Guided Optimization
- Llvm
- Benchmarking
Open coursework - CodeIntermediateNew
Apply Software Transactional Memory to a Real-Time Auction Book
Implement two variants of the same auction-book API (best-bid/best-ask lookup, place-order, cancel-order, match-orders): (1) baseline with java.util.concurrent locks + a SkipLis…
- Transactional Memory
- Concurrent Data Structures
- Haskell
Advanced Concurrency and Parallel Computing - Browse challenges
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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.
- CodeSeniorNew
Scale an HPC MPI Workload Across a Multi-Node Cluster
Receive the MPI weather model (Fortran 2018 + C, ~22,000 lines), 4 weeks of strong-scaling logs (1 to 256 ranks), and access to AWS ParallelCluster with EFA-enabled c7gn instanc…
- Hpc Programming
- Mpi
- Parallel Performance
Advanced Concurrency and Parallel Computing - CodeSeniorNew
Port a CPU Monte-Carlo Simulator to GPU for an Energy Trader
Receive the existing simulator (C++17 + OpenMP, around 5,000 lines), the test book (around 8,000 spread options), and access to an H100 80GB. Port to CUDA: random-number generat…
- Gpu Programming
- Cuda
- Monte Carlo
Advanced Concurrency and Parallel Computing - AnalysisIntermediateNew
Catastrophic-Forgetting Audit on a Domain Fine-Tune
You receive the fine-tuned 7B chemistry model and its base, plus a benchmark basket (MMLU subset, GSM8K, IFEval, a small instruction-following set). Run all 4 benchmarks on both…
- Catastrophic Forgetting
- LLM Evaluation
- Fine Tuning
Fine-Tuning Large Language Models - 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 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
- AnalysisBeginnerNew
Instruction Set Analysis for an Embedded Workload
Compile all 12 workload programs to both ISAs using the appropriate cross-compiler (GCC with -march=rv32e for RISC-V; provided proprietary toolchain for the in-house ISA). Repor…
- Instruction Sets
- Code Density
- Embedded Systems
Computer Architecture - 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
Edge ML and On-Device Machine Learning - AnalysisIntermediateNew
Halve a Daily Spark Bill Without Breaking the SLA
Work only from the materials in this file. Read the representative PySpark module (PULSE-JOB) and the cluster configuration (PULSE-CLUSTER) to understand how the nightly job is …
- Spark
- Cost Optimization
- Etl Pipelines
Open coursework
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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