Data and AI Process Videos
Data science and artificial intelligence projects, products, and teams are unique. Explore these educational videos to help you understand how to improve the likelihood of success on your next data science or AI initiative.
AI Failures
Learn 6 common reasons why AI projects fail – and tips to avoid these on your next project.
Related post: Why Big Data Science Projects Fail
5 Tips to Manage Data Science
Data science projects are tricky to execute. Learn these five tips to better manage your next data science project.
Related post: 6 Actions to Be a Better Data Science Manager
AI Product Management Manifesto
The AI Product Management Manifesto provides guidelines that help product managers understand how to resolve various competing priorities.
Related post: What is an AI Product Manager?
AI Team Roles
Building a successful AI team requires a diverse team of specialized roles that work together to deliver the end product. Explore nine common roles.
Related post: Data Science Roles – A Definitive Guide
SEMMA Data Science Process
SEMMA is the second most-known life cycle for managing data science projects. Learn what it is and assess whether you should use it.
Related post: What is SEMMA?
CRISP-DM
Crisp-DM is the most well-known life cycle for data science projects. Learn its six phases and how you might use them on your next project.
Related post: What is CRISP DM?
Agile AI
Agility is a mindset to help teams learn and adapt quickly. Learn how to be Agile as an AI team.
Related post: Agile AI
AI Life Cycle
The AI project life cycle describes the various steps that your team takes to deliver an AI product.
Related post: What is the AI Life Cycle?
Kanban
Kanban is a light-weight process that helps team manage their workflow. Learn how to use it for data science and AI teams.
Related post: Kanban for Data Science