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AI Project Management & Execution

CODE: AI13 

DURATION: 3 Days/5 Days/10 Days

CERTIFICATIONS: CPD

  • Modern facilities
  • Course materials and certificate
  • Accredited international trainers

3 Days

£3,450

5 Days

£4,450

5 Days

£7,300

Course Overview

While many organizations can design an AI strategy, the greatest challenge lies in execution. AI projects have high failure rates due to their experimental nature, unique technical risks, and cross-disciplinary demands. This course covers AI Project Management & Execution, focusing on best practices for successfully planning, executing, and monitoring AI initiatives. Participants will learn to integrate governance structures and align AI projects with strategic objectives while managing unique risks such as data quality, bias, and model performance.

Course Delivery

This course is available in the following formats:

Virtual

Classroom

Request this course in a different delivery format.

Course Outcomes

Delegates will gain the knowledge and skills to:

Scope and plan AI initiatives by defining success criteria and managing the uncertainty of experimental work.

Master end-to-end AI project lifecycles, from data acquisition and modelling to deployment and monitoring.

Lead and facilitate collaboration within cross-functional teams of data scientists, engineers, and business stakeholders.

Proactively identify and mitigate technical risks like data quality issues, model drift, and integration challenges.

Apply MLOps principles to reliably deploy, scale, and maintain models in a production environment.

Measure and communicate ROI by tracking business metrics to demonstrate value and secure sponsorship.

Key Course Highlights

At the end of this course, you’ll understand:

  • How to scope AI projects and define success criteria for iterative, experimental work.
  • The end-to-end AI project lifecycle, from data acquisition to deployment and monitoring.
  • The principles of leading and facilitating cross-functional AI teams effectively.
  • Key technical risks like data quality and model drift, and how to mitigate them.
  • The core principles of MLOps for deploying and maintaining models reliably.
  • How to measure an AI project’s value and communicate its ROI to secure sponsorship.
Who Should Attend

This course is designed for project managers, team leaders, IT professionals, business analysts, risk managers, and innovation managers who want to leverage AI to enhance project planning, execution, risk management, and decision-making. It is also suited for those seeking to integrate AI tools into project workflows or improve their understanding of AI’s role in managing complex projects effectively. No prior AI experience is required, but a basic knowledge of project management is beneficial.

Upcoming Course Dates

Delivery Format: Classroom & Virtual

Date: 16/02/2026

Location: London

Delivery Format: Classroom & Virtual

Date: 27/04/2026

Location: London

Delivery Format: Classroom & Virtual

Date: 28/09/2026

Location: Doha

AI Project Management & Execution

✓ Modern facilities

✓ Course materials and certificate

✓ Accredited international trainers

✓ Training materials and workbook

✓ Access to online resources

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