Lifecycle of a Data Science Project
summary
An overview of how a data science project progresses from initial idea to deployment, detailing how much time is spent on each phase and how the team organizes work. Describes team roles and delivery structure that keep data scientists focused on research rather than on implementing models in production, with concrete practices for handoff and deployment.
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chapters (11)
- 0:00Start
- 1:14Data Science Skills
- 3:51Example of data scientist projects
- 5:10What is the structure of a project?
- 6:12Understanding the problem
- 8:44Data collection, cleaning, and understanding
- 10:43Exploratory analysis
- 12:53Feature engineering
- 14:12Data modeling
- 18:58Time spent on a DS project
- 23:51Example project: property value
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