Complete eight Data Science projects that lock in important real world skills-along with a practical process you can use to learn any new technique quickly and efficiently. Solve Any Data Analysis Problem guides you through eight common scenarios you’ll encounter as a data scientist or analyst. As you explore each project, you’ll also master a proven process for quickly learning new skills developed by author and Half Stack Data Science podcast host David Asboth. In Solve Any Data Analysis Problem you’ll learn how to shift the way you think about data from the structured clean problems you get in a classroom, book, or bootcamp to the messy open-ended challenges of the workplace. As you work through eight problems you’ll see over and over on the job, you’ll discover a solutions-driven methodology that’s focused on getting results. You’ll learn how to determine a minimum viable answer for your stakeholders, identify and obtain the data you need to deliver, and reliably present and iterate on your findings. Which tool you are comfortable doing the above in does not matter. I will provide example solutions to the projects in the book using Python, but the focus will be on problem-solving, not the specifics of the Python programming language. Appendix A gives you a quick overview of the skills and tools in the basic data science toolkit. If you need to brush up on anything, we’ve linked to some useful resources you can use to get up to speed. As for most solutions I provide, the code itself will be written in Python, primarily using the Pandas library. While code snippets will be used to explain the example solution, I will focus discussions on the conceptual solution and less on the specifics of the code. The solution will be in three parts: setting up the problem statement and the data, creating the first iteration of a solution, and a third part to review the work and decide on further steps.

Solve Any Data Analysis Problem (MEAP v8) PDF

The list of books you might like