One of the beauties of data science is how projects can build on each other. In this book, we built a full-throttle production machine learning application. The good news is that you can re-purpose this code, infrastructure, and architecture for other projects. That is my sincere hope: you take what you have learned and build impactful data science systems.
Data science is gritty. Under the hood, it melds multiple fields into a unified profession. An applied full stack data scientist can competently dabble in DevOps and database administration. They should be skilled in machine learning and data visualization. The ability to write solid Python code cannot be overlooked. At the onset of this book, possessing all of these skills might have sounded intimidating. While not an easy journey, learning all these skills is not insurmountable.
No archetype of a "perfect" data scientist exists. Be unique. Be you. Data science can impact the world for both good and bad. Use your God-given skills for good. The world could use it.