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Beginning Programming with Python For Dummies
Create simple, easy programs in the popular Python language Beginning Programming with Python For Dummies is the trusted way to learn the foundations of programming using the Python programming language. Python is one of the top-ranked languages, and there’s no better way to get started in computer programming than this friendly guide. You’ll learn the basics of coding and the process of creating simple, fun programs right away. This updated edition features new chapters, including coverage of Google Colab, plus expanded information on functions and objects, and new examples and graphics that are relevant to today’s beginning coders. Dummies helps you discover the wealth of things you can achieve with Python. Employ an online coding environment to avoid installation woes and code anywhere, any time Learn the basics of programming using the popular Python language Create easy, fun projects to show off your new coding chops Fix errors in your code and use Python with external data sets Beginning Programming with Python For Dummies will get new programmers started—the easy way.
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Python for non-Pythonians
The book uses a very simple and accessible language. All the descriptions of Python functionalities come with intuitive examples to make you learn by doing. This is not a theoretical book and does not cover some of the most internal features of Python. The intention of the authors is to allow business oriented people to start using Python. The main reason for such a choice of style is due to the increasing number of requests by non-technical professionals to solve daily problems and tasks. Whether we want to append multiple spreadsheets or profile the customer base, being able to use a solid infrastructure which enables to collect, check, process, analyze data, and report results has become a basic requirement in most industries. The structure of this book replicates the structure of a grammar book. It first introduces the building blocks of Python - i.e., objects - which can be compared to the different types of words (e.g., verbs, nouns) of a language. It introduces readers to the syntax rules of Python - i.e., statements, functions, and classes. It then provides introduces how to use this new language for managing data. One thing that we found particularly helpful for our students is to provide wrong Python codes with the error message that Python provides, and ask them to fix the code in order to make it work. As making mistakes is very common, we would say normal, in programming, learning how to interpret the error messages and fix codes is extremely important from a pedagogical perspective. The book always challenges students with a series of "fix the code" questions at the end of each a topic. We adopt this structure because we found that students learn how to successfully write algorithms in Python when they understand its logic and the meaning of every single element of the algorithm. We have experimented that this natural progression, from the most basic elements to very complex scripts, raises students' self-confidence and proficiency in writing their own algorithms. Hence, the structure of the textbook greatly helps students and instructors to gradually acquire the "programming" mindset. Also, our teaching experience indicates that, as with any other language, students learn by practicing. For this reason our textbook, is rich in exercises of increasing complexity.
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Developer's Guide to AI
A practical, accessible guide that shows working software developers how to integrate real AI features into the applications they already build—using JavaScript, Python, APIs, and modern cloud services, without needing a data-science background.Working developers everywhere now use AI tools, but most still struggle to turn prompts and prototypes into reliable software features. The Developer’s Guide to AI teaches engineers how to build real, maintainable AI capabilities using the tools they already know—JavaScript, Python, APIs, vector search, and simple agent workflows—without advanced math or machine learning.Readers learn where AI belongs in an application, how to design around real-world constraints like latency and cost, and how to avoid the brittle prototypes that fail under changing requirements. With clear examples and production-focused patterns, this book helps developers ship AI features that last.
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