7.3 Training and Adaptation Pipelines¶

Role at Stage 7: Model Infrastructure¶

Automate dataset generation, fine-tuning, evaluation, and artifact export. This part is one capability inside the stage. It should leave behind an artifact, measurements, and a short explanation of failure modes.

Explanation¶

This part has 4 sub-parts because the topic needs that many learning units to feel natural. Some stages have more parts and some have fewer; the structure follows the topic, not a fixed template.

Part Diagram¶

%%{init: {"flowchart": {"htmlLabels": true, "nodeSpacing": 80, "rankSpacing": 110}, "themeVariables": {"fontSize": "18px"}} }%%
flowchart LR
  P["<b>7.3</b><br/>Training and<br/>Adaptation Pipelines"]
  P --> S1["<b>7.3.1</b><br/>Pipeline Orchestration"]
  P --> S2["<b>7.3.2</b><br/>Dataset Generation<br/>Jobs"]
  P --> S3["<b>7.3.3</b><br/>Fine Tuning Jobs"]
  P --> S4["<b>7.3.4</b><br/>Model Registry and<br/>Release Gates"]
  P --> E["<b>Exam</b><br/>Part practice"]

Sub-Parts¶

Sub-part folder	What it explains
7.3.1 Pipeline Orchestration	Pipeline Orchestration is the working skill inside Training and Adaptation Pipelines that helps you build the stage artifact, A deployed model-backed service with data or retrieval pipeline, registry metadata, eval checks, structured logs, and dashboards, while collecting enough evidence to trust the result.
7.3.2 Dataset Generation Jobs	Dataset Generation Jobs is the working skill inside Training and Adaptation Pipelines that helps you build the stage artifact, A deployed model-backed service with data or retrieval pipeline, registry metadata, eval checks, structured logs, and dashboards, while collecting enough evidence to trust the result.
7.3.3 Fine Tuning Jobs	Fine Tuning Jobs is the working skill inside Training and Adaptation Pipelines that helps you build the stage artifact, A deployed model-backed service with data or retrieval pipeline, registry metadata, eval checks, structured logs, and dashboards, while collecting enough evidence to trust the result.
7.3.4 Model Registry and Release Gates	Model Registry and Release Gates is the working skill inside Training and Adaptation Pipelines that helps you build the stage artifact, A deployed model-backed service with data or retrieval pipeline, registry metadata, eval checks, structured logs, and dashboards, while collecting enough evidence to trust the result.

What a Person Who Masters This Part Can Do¶

Explain how Training and Adaptation Pipelines supports a deployed model-backed service with data or retrieval pipeline, registry metadata, eval checks, structured logs, and dashboards..
Build and inspect this artifact: Create a generate-train-evaluate-export pipeline.
Measure progress with: Track dataset version, config, checkpoint, report, and promotion decision.
Debug at least one failure mode before moving to the next part.

Build and Measure¶

Build: Create a generate-train-evaluate-export pipeline.

Measure: Track dataset version, config, checkpoint, report, and promotion decision.

Tests¶

Take one 30-question exam after studying this part. It opens in a new browser tab so the study page stays available.

Open Part Exam

Back to Stage¶

Return to Stage 7: Model Infrastructure.