Training for data scientists and ML engineers on self-service provisioning, GPU workload submission, MLOps tooling, and model serving on PaletteAI.
Data Science Team Training is designed for data scientists, ML engineers, and MLOps practitioners who need to deploy and manage AI/ML workloads on PaletteAI. All tiers include hands-on lab exercises with GPU access, code examples, and post-training Q&A sessions.
Essentials curriculum
PaletteAI for ML workloads overview, GPU cluster provisioning and resource quotas, deploying Jupyter/notebook environments, model serving basics (KServe, Seldon), intro to Spectro Cloud packs for ML.
Standard (includes Essentials)
MLOps pipeline design (Kubeflow, Argo), multi-GPU scheduling and NUMA-aware placement, model registry integration and versioning, experiment tracking on PaletteAI, data pipeline orchestration (Spark, Ray on K8s).
Premium (includes Standard)
Advanced distributed training patterns, custom operator development for ML workflows, cost optimization for GPU clusters, federated learning and multi-cluster model training, production model monitoring and drift detection, capstone: end-to-end MLOps pipeline build.
| ESSENTIALS | STANDARD | PREMIUM | |
|---|---|---|---|
| Duration | 2 Days | 3 Days | 5 Days |
| Cohort | Up To 12 | Up To 12 | Up To 10 |
| Format | Up to 10 | Virtual or on-site | On-site preferred |
| Labs | 3 guided labs | 6 labs + mini-project | 10 labs + capstone |
| Lab environment | Shared sandbox | Dedicated cluster | Dedicated + 30-day access |
| Instructor | Senior consultant | Senior + office hours | Lead data scientist + mentorship |
| Certification | Completion cert | + Skills assessment | + ISC proficiency badge |
Pre-Training
ISC reviews your team's skill levels and current tooling. GPU-enabled lab environments are provisioned and pre-configured with sample datasets.
Standard (includes Essentials)
MLOps pipeline design (Kubeflow, Argo), multi-GPU scheduling and NUMA-aware placement, model registry integration and versioning, experiment tracking on PaletteAI, data pipeline orchestration (Spark, Ray on K8s).
Post-Training
Q&A sessions with the instructor. Premium tier includes 30-day lab access and ongoing mentorship.
Data Science Team Training is designed for data scientists, ML engineers, MLOps practitioners, and applied research teams who need to deploy and run AI/ML workloads on PaletteAI.
Basic Kubernetes awareness is recommended. No prior PaletteAI experience is required for Essentials.
Get your ML engineers productive on PaletteAI fast.
