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Название: Essential Data Analytics, Data Science, and AI: A Practical Guide for a Data-Driven World
Автор: Maxine Attobrah
Издательство: Apress
Год: 2024
Страниц: 209
Язык: английский
Формат: pdf
Размер: 10.1 MB
In today's world, understanding data analytics, Data Science, and Artificial Intelligence is not just an advantage but a necessity. This book is your thorough guide to learning these innovative fields, designed to make the learning practical and engaging. The book starts by introducing data analytics, Data Science, and Artificial Intelligence (AI). It illustrates real-world applications, and, it addresses the ethical considerations tied to AI. It also explores ways to gain data for practice and real-world scenarios, including the concept of synthetic data. Next, it uncovers Extract, Transform, Load (ETL) processes and explains how to implement them using Python. Further, it covers Artificial Intelligence and the pivotal role played by Machine Learning models. Python is currently one of the most popular programming languages for completing Artificial Intelligence and Data Science tasks. This is the case because of its easy-to-read syntax, extensive libraries, strong compatibility with cross-platforms, and strong community support. This makes it easier for beginners and experienced programmers to write and understand code and encourages faster development and collaboration.
Автор: Maxine Attobrah
Издательство: Apress
Год: 2024
Страниц: 209
Язык: английский
Формат: pdf
Размер: 10.1 MB
In today's world, understanding data analytics, Data Science, and Artificial Intelligence is not just an advantage but a necessity. This book is your thorough guide to learning these innovative fields, designed to make the learning practical and engaging. The book starts by introducing data analytics, Data Science, and Artificial Intelligence (AI). It illustrates real-world applications, and, it addresses the ethical considerations tied to AI. It also explores ways to gain data for practice and real-world scenarios, including the concept of synthetic data. Next, it uncovers Extract, Transform, Load (ETL) processes and explains how to implement them using Python. Further, it covers Artificial Intelligence and the pivotal role played by Machine Learning models. Python is currently one of the most popular programming languages for completing Artificial Intelligence and Data Science tasks. This is the case because of its easy-to-read syntax, extensive libraries, strong compatibility with cross-platforms, and strong community support. This makes it easier for beginners and experienced programmers to write and understand code and encourages faster development and collaboration.