The phases of the life cycle of a data science project are:
1. Discovery involves learning the business domain, framing the problem, identifying key stakeholders, etc
2. Data preparation includes conditioning the data
3. Model planning includes assessing the structure of the data and determining the applicable techniques
4. Model building includes developing datasets for training, testing.
5. Communicating results
6. Operationalizing includes setting up a pilot project to deploy