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MLOps track

Batch Inference

Scheduled scoring, offline predictions and job management.

6 concepts4 labs1 challenges
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Concepts

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Work through the concepts in order, or jump to what you need.

1

Batch Inference

Concept · Hands-on lab included

2

Batch Pipeline Design

Concept · Hands-on lab included

3

Output Architecture

Concept · Hands-on lab included

4

Mini-Batch and Windowed Processing

Concept · Hands-on lab included

5

Batch Evaluation and Reconciliation

Concept · Hands-on lab included

6

Batch vs Real-Time Decision

Concept · Hands-on lab included

Practice

Hands-on labs

Apply what you've learned in guided, production-style environments.

Browse all labs

Design a Restartable Batch Job

35 min · intermediate · Batch Pipeline Design

Version Prediction Outputs

35 min · intermediate · Output Architecture

Score Windowed Mini-Batches

40 min · advanced · Mini-Batch and Windowed Processing

Write a Batch vs Real-Time Decision Calculator

35 min · intermediate · Batch vs Real-Time Decision

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Next modules

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ML Lifecycle

The full ML lifecycle and the operational discipline MLOps adds.

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Experiment Tracking

MLflow tracking, run metadata, reproducibility and comparing experiments.

0%

Dataset Versioning

DVC, data lineage and immutability for training data.

DevOpsForge - MLOps · Batch Inference
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