دانلود کتاب پایتون آسان شد – راهنمای عملی کدنویسی، ساختار داره و اپلیکیشن‌های عملی

Is there a reason to write a book about programming in times of artificial intelligence (AI)? I think, yes, there is. You still have to learn the fundamentals of programming, and that’s what this book is about. AI can do many things by now, but it cannot replace yet every part of software engineering. And this is where this book comes into place. I try to give you an idea of what programming is about, about the pitfalls of Python, and what Python has to offer. I didn’t write exercises in this book because I think the best way of learning a programming language is by doing a project. I never really solved the exercises anyway; learning by doing is, in my opinion, the much more effective way of learning. This book is not going to teach you everything there is to know about Python. It’s simply impossible to learn too many things. Though there are books on Python that tried, these are 1000 pages long and feel more like encyclopedias. I didn’t want to write such a book because who reads 1000 pages about Python? I think it’s much more efficient to write a concise book that you can read back to back and later on you will anyway use Google or an AI assistant to find the information you need. I think a book on a programming language should give you an idea of how the programming language works and what it can do. It should only kick start your journey into this new language. The times of printed encyclopedias are over. I wrote this book with scientists and engineers in mind. Of course, you can also do web development, IT security, and many other things with Python. But I didn’t write about these things. Explaining the Django web framework or some IT security is too specific for this book and out of scope. Science and engineering, on the other hand, need very little knowledge in order to get started. Furthermore, scientists and engineers have the potential to become good programmers. But first, they have to learn it properly, which, unfortunately, is something many experienced programmers didn’t do. And for this reason, there is a lot of bad code out there. When programming, you often have to find out why something doesn’t work as it should, so you have to follow the traces of the code to find the error. You also have to structure the knowledge you have about the code as well as possible and thus make it available to your coworkers. Knowing how to work scientifically is a great advantage in programming. This book is only the beginning. It takes some intrinsic motivation to become a good programmer. For this reason, there are no exercises in this book, nor is it hundreds of pages long explaining all kinds of things you won’t remember. Instead, I tried to write a concise book that you can really read back to back. Though I have to admit that I also added some examples of mathematical problems for scientists and engineers toward the end of the book for the interested reader. But you don’t have to read them if you’re not interested in them. Usually by far the best way of learning programming is having a personal project to work on. This gives you a goal and practical experience. You also learn to work independently. This book won’t teach you everything that you need to know for your project; it is only able to give you a jump start. You can take some of the things that you learned and combine them into something new. But you also have to find out a lot of things yourself. Here, your best friend is good old Google, or also some of the many AI tools that can answer your questions as well. Once you get started, it is important to keep learning. Ask some friends for advice to improve your code, do an internship, watch YouTube videos, or read books that help you write better code. For example, my other book, Software Engineering Made Easy, further explains many of the gray boxes you will find in this book. Learn from different sources and compare their advice. Programming is not an exact science, and you will have to find out what works best for you. There’s an infinite number of ways to solve a problem, and you have to find the one that works best for you.