- DesignExpertNew
Build an Edge MLOps Pipeline for a Smart-Agriculture Sensor
You receive a fleet simulator (1,000 simulated sensors with bandwidth + battery profiles), a model registry stub, and the current firmware's model-loading interface. Design and …
- Edge Mlops
- Ota Updates
- Model Versioning
Edge ML and On-Device Machine Learning - CodeExpertNew
Auto-Tune a Distributed Training Cluster's Throughput
Pick a representative fine-tune job (an open 7B model on a public instruction dataset is fine). Define the search space: NCCL_ALGO, NCCL_PROTO, num_workers, prefetch_factor, gra…
- Distributed Training
- Hyperparameter Tuning
- Nccl
Machine Learning Systems - CodeExpertNew
Cost-Optimize a 24/7 LLM API Cluster
Profile the current usage (24-hour trace, per-team breakdown). Pick a cost-optimization mix from: time-based autoscaling, spot/preemptible instances with graceful drain, smarter…
- Llm Serving
- Autoscaling
- Ray
ML Engineering and Production ML - CodeExpertNew
Build an MLOps Platform Slice for a Fintech Risk Team
Across a 5-person team, ship (1) experiment tracking integrated into a sample model training job; (2) a model registry that promotes-by-tag; (3) a training pipeline orchestrated…
- Mlops Design
- Experiment Tracking
- Model Registry
AI Software Engineering Group Project Practice your coursework on real scenarios.
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Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
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Step 04
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