MLOps for Enterprise AI Products

Objectives

• Analyze ml product lifecycle and governance, including use-case ownership, model risk tiering, and approval gates.
• Configure or structure data and feature pipelines, including training-serving consistency and feature-store patterns.
• Evaluate packaging and deployment, including model registries, containers, endpoints, and batch scoring.
• Manage monitoring and model operations, including prediction quality, drift, latency, errors, and cost metrics.
• Apply production readiness workshop, including design an mlops control flow for a selected model.

Target audience

• Professionals responsible for this subject area
• Managers, supervisors, and team leaders
• Analysts, specialists, engineers, or coordinators working with the relevant processes
• Project, implementation, assurance, or improvement team members
• Professionals preparing for broader responsibilities in this field

Materials provided

• ○ Course-specific presentation slides
• ○ Guided exercises, scenarios, or configured-environment activities appropriate to the subject
• ○ Course-specific worksheets, checklists, or calculation templates
• ○ Applied workplace case materials
• ○ 4D Certificate of Completion issued by 4D Training & Consultancy
• ○ Post-course support for implementation questions

Training Options

Programs can be delivered in-house, online, or in a blended format depending on your team's schedule, location, and learning objectives. When an external certificate or exam is included, certification rules and fees remain under the relevant awarding body's policies, while 4D provides the training and preparation support.

Why choose 4D

4D Training & Consultancy adapts the program to the client’s operating environment. Delivery combines structured explanation with subject-specific analysis, exercises, and implementation decisions so participants can transfer the learning to real responsibilities without implying vendor authorization.