Those are important points: we need to put time limits on our goals and come up with a series of smaller objectives leading to the main objective. Time bounds can serve as the motivation needed to get started. Also, at the smaller milestones, we can evaluate our progress, get feedback and course-correct. That’s a much better approach than only getting feedback at the end!

Multiple milestones also can build our confidence through small wins. Making continual progress is a lot more enjoyable than waiting until the entire project is complete to see a working model. Also, the iterative approach to writing software is part of the agile development method which emphasizes “evolutionary development”, continual improvement, and rapid response to requested changes.

Thanks for the kind words, and keep up the good work with your data science projects!