Introduction to PMI CPMAI - Master Class

About this course

Reach out to me on LinkedIn for any queries or if you are looking to buy high-quality practice/mock CPMAI exams. Profile: Sanal Mathew John (smj84). Discount coupons are available for the MASTER CLASS as well.This course covers all the important topics and key areas to focus on for the PMI CPMAI exam. I am putting a small price on this course to avoid unnecessary crowd registration and out-of-pocket comments that do not make any sense. You can connect with me on LinkedIn if you want this course for free.Here are the key aspects defining CPMAI:1.  Methodology and Framework: It is described as a vendor-neutral methodology or a vendor-agnostic framework. It provides a structured approach or guidance for planning, managing, and executing AI initiatives successfully.2. Purpose: CPMAI was developed to address the high rate of failure often seen in AI projects. It aims to close gaps and reduce failure rates by equipping professionals with the tools and structure needed. The goal is to ensure AI and ML projects deliver meaningful, measurable value and transition from proof-of-concept to scalable, production-ready systems.3. Characteristics:◦Vendor-neutral/agnostic: It is not tied to specific AI tools or platforms.◦Iterative: Projects follow iterative loops of development and refinement. The phases are meant to be mutually iterative.◦Data-centric: It inherently focuses on data, recognizing that AI projects are driven by data. It emphasizes early-stage data assessments.◦AI-specific: It extends traditional project management approaches, like agile and data-focused frameworks (such as CRISP-DM), with best practices tailored to the unique needs of AI projects. It provides AI-specific guardrails.4. Structure: CPMAI organizes AI projects into six iterative phases: business u

Course objectives

• to prepare participants for the PMI CPMAI exam
• to reduce failure rates in AI projects
• to promote best practices specific to AI-focused project management