Learning System

Data Science

Machine Learning in Production

This advanced track focuses on deployment and operations, not notebooks only. You will build model pipelines, evaluate performance tradeoffs, and respond to incidents with confidence.

Level: Advanced

Duration: 26 hours

Rating: 4.9

Reviews: 198

Enrollment

$149

Curriculum

  • Lesson 1

    Problem Framing and Baselines

    Define measurable objectives, baseline models, and acceptable tradeoffs.

    34 min

  • Lesson 2

    Training Pipelines and Reproducibility

    Automate training runs, artifact tracking, and environment parity.

    45 min

  • Lesson 3

    Evaluation, Monitoring, and Drift

    Track quality in production and detect shifts before user impact grows.

    40 min

  • Lesson 4

    Serving Architecture and Observability

    Design model serving layers with latency budgets and clear traces.

    39 min

  • Lesson 5

    Incident Response and Rollback Playbooks

    Handle model incidents with alert thresholds, rollback paths, and postmortems.

    32 min