Showing posts with label book. Show all posts
Showing posts with label book. Show all posts

Tuesday 27 February 2024

Data Engineering with AWS: Acquire the skills to design and build AWS-based data transformation pipelines like a pro 2nd ed. Edition


Looking to revolutionize your data transformation game with AWS? Look no further! From strong foundations to hands-on building of data engineering pipelines, our expert-led manual has got you covered.

Key Features

Delve into robust AWS tools for ingesting, transforming, and consuming data, and for orchestrating pipelines

Stay up to date with a comprehensive revised chapter on Data Governance

Build modern data platforms with a new section covering transactional data lakes and data mesh

Book Description

This book, authored by a seasoned Senior Data Architect with 25 years of experience, aims to help you achieve proficiency in using the AWS ecosystem for data engineering. This revised edition provides updates in every chapter to cover the latest AWS services and features, takes a refreshed look at data governance, and includes a brand-new section on building modern data platforms which covers; implementing a data mesh approach, open-table formats (such as Apache Iceberg), and using DataOps for automation and observability.

You'll begin by reviewing the key concepts and essential AWS tools in a data engineer's toolkit and getting acquainted with modern data management approaches. You'll then architect a data pipeline, review raw data sources, transform the data, and learn how that transformed data is used by various data consumers. You’ll learn how to ensure strong data governance, and about populating data marts and data warehouses along with how a data lakehouse fits into the picture. After that, you'll be introduced to AWS tools for analyzing data, including those for ad-hoc SQL queries and creating visualizations. Then, you'll explore how the power of machine learning and artificial intelligence can be used to draw new insights from data. In the final chapters, you'll discover transactional data lakes, data meshes, and how to build a cutting-edge data platform on AWS.

By the end of this AWS book, you'll be able to execute data engineering tasks and implement a data pipeline on AWS like a pro!

What you will learn

Seamlessly ingest streaming data with Amazon Kinesis Data Firehose

Optimize, denormalize, and join datasets with AWS Glue Studio

Use Amazon S3 events to trigger a Lambda process to transform a file

Load data into a Redshift data warehouse and run queries with ease

Visualize and explore data using Amazon QuickSight

Extract sentiment data from a dataset using Amazon Comprehend

Build transactional data lakes using Apache Iceberg with Amazon Athena

Learn how a data mesh approach can be implemented on AWS

Who this book is for

This book is for data engineers, data analysts, and data architects who are new to AWS and looking to extend their skills to the AWS cloud. Anyone new to data engineering who wants to learn about the foundational concepts, while gaining practical experience with common data engineering services on AWS, will also find this book useful. A basic understanding of big data-related topics and Python coding will help you get the most out of this book, but it’s not a prerequisite. Familiarity with the AWS console and core services will also help you follow along.

Table of Contents

An Introduction to Data Engineering

Data Management Architectures for Analytics

The AWS Data Engineer’s Toolkit

Data Governance, Security, and Cataloging

Architecting Data Engineering Pipelines

Ingesting Batch and Streaming Data

Transforming Data to Optimize for Analytics

Identifying and Enabling Data Consumers

A Deeper Dive into Data Marts and Amazon Redshift

Orchestrating the Data Pipeline

Hard Copy: Data Engineering with AWS: Acquire the skills to design and build AWS-based data transformation pipelines like a pro 2nd ed. Edition

Monday 29 January 2024

Learn Python Programming: An in-depth introduction to the fundamentals of Python, 3rd Edition


Get up and running with Python 3.9 through concise tutorials and practical projects in this fully updated third edition.

Purchase of the print or Kindle book includes a free eBook in PDF format.

Key Features

Extensively revised with richer examples, Python 3.9 syntax, and new chapters on APIs and packaging and distributing Python code

Discover how to think like a Python programmer

Learn the fundamentals of Python through real-world projects in API development, GUI programming, and data science

Book Description

Learn Python Programming, Third Edition is both a theoretical and practical introduction to Python, an extremely flexible and powerful programming language that can be applied to many disciplines. This book will make learning Python easy and give you a thorough understanding of the language. You'll learn how to write programs, build modern APIs, and work with data by using renowned Python data science libraries.

This revised edition covers the latest updates on API management, packaging applications, and testing. There is also broader coverage of context managers and an updated data science chapter.

The book empowers you to take ownership of writing your software and become independent in fetching the resources you need. You will have a clear idea of where to go and how to build on what you have learned from the book.

Through examples, the book explores a wide range of applications and concludes by building real-world Python projects based on the concepts you have learned.

What you will learn

Get Python up and running on Windows, Mac, and Linux

Write elegant, reusable, and efficient code in any situation

Avoid common pitfalls like duplication, complicated design, and over-engineering

Understand when to use the functional or object-oriented approach to programming

Build a simple API with FastAPI and program GUI applications with Tkinter

Get an initial overview of more complex topics such as data persistence and cryptography

Fetch, clean, and manipulate data, making efficient use of Python’s built-in data structures

Who this book is for

This book is for everyone who wants to learn Python from scratch, as well as experienced programmers looking for a reference book. Prior knowledge of basic programming concepts will help you follow along, but it’s not a prerequisite.

Table of Contents

A Gentle Introduction to Python

Built-In Data Types

Conditionals and Iteration

Functions, the Building Blocks of Code

Comprehensions and Generators

OOP, Decorators, and Iterators

Exceptions and Context Managers

Files and Data Persistence

Cryptography and Tokens


Debugging and Profiling

GUIs and Scripting

Data Science in Brief

Introduction to API Development

Packaging Python Applications

Hard Copy : Learn Python Programming: An in-depth introduction to the fundamentals of Python, 3rd Edition

Python Object-Oriented Programming: Build robust and maintainable object-oriented Python applications and libraries, 4th Edition


A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniques

Key Features

Build an intuitive understanding of object-oriented design, from introductory to mature programs

Learn the ins and outs of Python syntax, libraries, and best practices

Examine a machine-learning case study at the end of each chapter

Book Description

Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning.

Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python's classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python's exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem.

By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs.

What you will learn

Implement objects in Python by creating classes and defining methods

Extend class functionality using inheritance

Use exceptions to handle unusual situations cleanly

Understand when to use object-oriented features, and more importantly, when not to use them

Discover several widely used design patterns and how they are implemented in Python

Uncover the simplicity of unit and integration testing and understand why they are so important

Learn to statically type check your dynamic code

Understand concurrency with asyncio and how it speeds up programs

Who this book is for

If you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary.

Table of Contents

Object-Oriented Design

Objects in Python

When Objects Are Alike

Expecting the Unexpected

When to Use Object-Oriented Programming

Abstract Base Classes and Operator Overloading

Python Data Structures

The Intersection of Object-Oriented and Functional Programming

Strings, Serialization, and File Paths

The Iterator Pattern

Common Design Patterns

Advanced Design Patterns

Testing Object-Oriented Programs


Hard Copy: Python Object-Oriented Programming: Build robust and maintainable object-oriented Python applications and libraries, 4th Edition

Monday 6 November 2023

Python - The Bible: 3 Manuscripts in 1 Book: Python Programming for Beginners - Python Programming for Intermediates - Python Programming for Advanced


Python Programming for Beginners - Learn the Basics of Python in 7 Days!

Here's what you'll learn from this book:

  • Introduction 
  • Understanding Python: A Detailed Background 
  • How Python Works 
  • Python Glossary 
  • How to Download and Install Python 
  • Python Programming 101: Interacting with Python in Different Ways 
  • How to Write Your First Python Program 
  • Variables, Strings, Lists, Tuples, Dictionaries 
  • About User-Defined Functions 
  • How to Write User-Defined Functions in Python 
  • About Coding Style 
  • Practice Projects: The Python Projects for Your Practice

Python Programming for Intermediates - Learn the Basics Of Python in 7 Days!

Here's what you'll learn from this book:

  • Shallow Copy and Deep Copy 
  • Objects and Classes in Python - Including Python Inheritance, Multiple Inheritances, and so On
  • Recursion in Python 
  • Debugging and Testing 
  • Fibonacci Sequence (definition) and Monitization in Python 
  • Arguments in Python 
  • Namespaces in Python and Python Modules 
  • Simple Python Projects for Intermediates

Python Programming for Advanced - Learn the Basics of Python in 7 Days!

Here's what you'll learn from this book:

  • File management
  • Python Iterator
  • Python Generator
  • Regular Expressions 
  • Python Closure
  • Python Property
  • Python Assert
  • Simple Recap Projects 
  • Start Coding Now! 

Popular Posts


AI (27) Android (24) AngularJS (1) Assembly Language (2) aws (17) Azure (7) BI (10) book (4) Books (118) C (77) C# (12) C++ (82) Course (62) Coursera (180) Cybersecurity (22) data management (11) Data Science (96) Data Strucures (6) Deep Learning (9) Django (6) Downloads (3) edx (2) Engineering (14) Excel (13) Factorial (1) Finance (6) flutter (1) FPL (17) Google (19) Hadoop (3) HTML&CSS (46) IBM (25) IoT (1) IS (25) Java (92) Leet Code (4) Machine Learning (44) Meta (18) MICHIGAN (5) microsoft (4) Pandas (3) PHP (20) Projects (29) Python (757) Python Coding Challenge (238) Questions (2) R (70) React (6) Scripting (1) security (3) Selenium Webdriver (2) Software (17) SQL (40) UX Research (1) web application (8)


Person climbing a staircase. Learn Data Science from Scratch: online program with 21 courses