AI Today Podcast: AI Glossary Series- methodology, waterfall, Agile, CRISP-DM, Cognitive Project Management for AI (CPMAI)
Nov 10, 2023
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The hosts discuss the importance of methodology in AI projects, comparing Waterfall and agile methodologies. They explore the differences between CRISP DM and CPMI methodologies and highlight the benefits of getting certified in Cognitive Project Management for AI (CPMAI).
Follow best practice methodologies to avoid common reasons why AI projects fail.
Waterfall and agile are two different approaches in AI project management, each suitable for specific project requirements.
Deep dives
Methodologies for Successful AI Projects
The podcast discusses the importance of methodologies in AI projects. It emphasizes that making AI successful goes beyond just machine learning models and algorithms, and requires a full understanding of big data, ethical concepts, and data management. The podcast introduces the concept of methodology as a set of steps and processes followed in a particular order to achieve desired and repeatable outcomes. It highlights CPM AI methodology as a project management approach specifically designed for running and managing AI projects. The podcast emphasizes the significance of following best practice methodologies to avoid common reasons why AI projects fail.
Waterfall and Agile Methodologies
The podcast explores two specific methodologies: waterfall and agile. Waterfall is described as a sequential development process that flows like a waterfall, where each phase is completed before moving on to the next. It is suitable for projects with well-defined requirements and minimal need for change. Agile, on the other hand, is presented as an iterative approach that focuses on short sprints and rapid deliverables. It emphasizes responding to change and collaboration with customers. Agile is highlighted as more suitable for software development projects that require flexibility and adaptability.
Data-centric Methodologies: CRISP DM and CPM AI
The podcast introduces two data-centric methodologies: CRISP DM and CPM AI. CRISP DM, an established methodology for data mining, consists of six phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment. While it is effective for data projects, it may need enhancement to adapt to AI projects. CPM AI, or Cognitive Project Management for AI, is presented as an enhanced data-centric methodology that incorporates agile principles and AI-specific details. The podcast highlights the benefits of CPM AI, such as its focus on iterative processes and its ability to address common reasons for AI project failures. It encourages listeners to explore the free introduction course and consider becoming CPM AI certified to enhance their AI project management abilities.
In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the terms Methodology, Waterfall, Agile, CRISP-DM, Cognitive Project Management for AI (CPMAI).
In this episde we explain how these terms relate to AI and why it’s important to know about them. Just about every single industry is using AI in some shape or form to help streamline and improve processes, increase productivity, gain a competitive edge, and stand out from others.