The 51 Best Python Books to Consider Reading Right Now

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October 21, 2022Best Practices

The Best Python Books

Python Crash Course, 2nd Edition: A Hands-On, Project-Based Introduction to Programming

“Python Crash Course is the world’s best-selling guide to the Python programming language. In the first half of the book, you’ll learn basic programming concepts, such as variables, lists, classes, and loops, and practice writing clean code with exercises for each topic. You’ll also learn how to make your programs interactive and test your code safely before adding it to a project. In the second half, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, a set of data visualizations with Python’s handy libraries, and a simple web app you can deploy online.”

Learning Python, 5th Edition

“Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today.”

Automate the Boring Stuff with Python, 2nd Edition: Practical Programming for Total Beginners

“In this fully revised second edition of the best-selling classic Automate the Boring Stuff with Python, you’ll learn how to use Python to write programs that do in minutes what would take you hours to do by hand–no prior programming experience required. You’ll learn the basics of Python and explore Python’s rich library of modules for performing specific tasks, like scraping data off websites, reading PDF and Word documents, and automating clicking and typing tasks.”

Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and The Cloud

“[This title] offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs), and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science.”

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

“Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.”

Head First Python: A Brain-Friendly Guide

“With Head First Python, you’ll quickly grasp Python’s fundamentals, working with the built in data structures and functions. Then you’ll move on to building your very own webapp, exploring database management, exception handling, and data wrangling. If you’re intrigued by what you can do with context managers, decorators, comprehensions, and generators, it’s all here. This second edition is a complete learning experience that will help you become a bonafide Python programmer in no time.”

Python All-in-One For Dummies

“Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. It covers the basics of the language, explains its syntax through application in high-profile industries, and shows how Python can be applied to projects in the enterprise. It also delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics, and data analysis. This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox..”

Fluent Python: Clear, Concise, and Effective Programming

“With this hands-on guide, you’ll learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—features. Author Luciano Ramalho takes you through Python’s core language features and libraries, and shows you how to make your code shorter, faster, and more readable at the same time. Many experienced programmers try to bend Python to fit patterns they learned from other languages, and never discover Python features outside of their experience. With this book, those Python programmers will thoroughly learn how to become proficient in Python 3.”

Introducing Python: Modern Computing in Simple Packages

“Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned. You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips.”

Murach’s Python Programming

“If you want to learn how to program but don’t know where to start, this is the right book and the right language for you. From the first page, our unique self-paced approach will help you build competence and confidence in your programming skills. And Python is the best language ever for learning how to program because of its simplicity and breadth; two features that are hard to find in a single language. The book’s  self-paced approach also works for experienced programmers, helping you learn faster and better than you’ve ever learned a language before. By the time you’re through, you will have mastered all of the Python skills that are needed on the job, including those for object-oriented, database, and GUI programming.”

Learn Python 3 the Hard Way: A Very Simple Introduction to the Terrifyingly Beautiful World of Computers and Code

“In Learn Python 3 the Hard Way, you’ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises. This book is perfect for total beginners with zero programming experience.”

Python Cookbook, Third Edition

“If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms. Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.”

Python for Finance: Mastering Data-Driven Finance

“Updated for Python 3, the second edition of this hands on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full fledged framework for Monte Carlo simulation based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.”

Classic Computer Science Problems in Python

“Classic Computer Science Problems in Python deepens your knowledge of problem-solving techniques from the realm of computer science by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you’ll remember important things you’ve forgotten and discover classic solutions to your “new” problems! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.”

Python Programming: An Introduction to Computer Science

“This third edition of John Zelle’s Python Programming continues the tradition of updating the text to reflect new technologies while maintaining a time-tested approach to teaching introductory computer science. An important change to this edition is the removal of most uses of eval and the addition of a discussion of its dangers. In our increasingly connected world, it’s never too early to begin considering computer security issues. This edition also uses several new graphics examples, developed throughout chapters 4-12.”

The Python Workshop: A New, Interactive Approach to Learning Python

“The Python Workshop focuses on building up your practical skills so that you can work towards building up your machine learning skills as a data scientist, write scripts that help automate your life and save you time, or even create your own games and desktop applications. You’ll build and iterate on your code like a software developer, learning along the way. This process means that you’ll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.”

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

“By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started.”

Python for DevOps: Learn Ruthlessly Effective Automation

“This practical resource shows you how to use Python for everyday Linux systems administration tasks with today’s most useful DevOps tools, including Docker, Kubernetes, and Terraform. Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you’ll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to “get stuff done” in Python? This is your guide.”

Serious Python: Black-Belt Advice on Deployment, Scalability, Testing, and More

“You’ll cover a range of advanced topics like multithreading and memorization, get advice from experts on things like designing APIs and dealing with databases, and learn Python internals to help you gain a deeper understanding of the language itself. Written for developers and experienced programmers, Serious Python brings together over 15 years of Python experience to teach you how to avoid common mistakes, write code more efficiently, and build better programs in less time.”

Effective Python: 90 Specific Ways to Write Better Python

“This second edition of Effective Python will help you master a truly “Pythonic” approach to programming, harnessing Python’s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers’ best-selling Effective C++, Brett Slatkin brings together 90 Python best practices, tips, and shortcuts, and explains them with realistic code examples so that you can embrace Python with confidence. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance.”

Cracking Codes with Python: An Introduction to Building and Breaking Ciphers

“Learn how to program in Python while making and breaking ciphers—algorithms used to create and send secret messages! After a crash course in Python programming basics, you’ll learn to make, test, and hack programs that encrypt text with classical ciphers like the transposition cipher and Vigenère cipher. You’ll begin with simple programs for the reverse and Caesar ciphers and then work your way up to public key cryptography, the type of encryption used to secure today’s online transactions, including digital signatures, email, and Bitcoin.”

Deep Learning with Python

“Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You’ll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you’ll have the knowledge and hands-on skills to apply deep learning in your own projects.”

Python for Everybody: Exploring Data in Python 3

“Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. This book uses the Python 3 language. The earlier Python 2 version of this book is titled “Python for Informatics: Exploring Information”. There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.py4e.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.”

Learn Python Quickly: A Complete Beginner’s Guide to Learning Python, Even If You’re New to Programming

“This book follows a step by step guide, walking you through everything you need to know about Python in an easy to follow fashion. It will teach you all the basics of Python, and even some of the more advanced Python concepts, taking you from beginner to intermediate Python programmer. The exercises in this book are designed to help you practice using the skills you’ve learned in the various sections. The final two projects will let you practice putting everything you’ve learned together and teaching you how to manipulate text, work with images, and create a simple Graphical User Interface (GUI).”

The Hitchhiker’s Guide to Python: Best Practices for Development

“The Hitchhiker’s Guide to Python takes the journeyman Pythonista to true expertise. This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhiker’s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.”

Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2

“Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you’ll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.”

Programming Python: Powerful Object-Oriented Programming

“Programming Python will show you how, with in depth tutorials on the language’s primary application domains: system administration, GUIs, and the Web. You’ll also explore how Python is used in databases, networking, front end scripting layers, text processing, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Python’s many roles in practical, real world programming. Completely updated for version 3.x, Programming Python also delves into the language as a software development tool, with many code examples scaled specifically for that purpose.”

Python Data Science Handbook: Essential Tools for Working with Data

“Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.”

Mastering Python Networking: Your one-stop solution to using Python for network automation, programmability, and DevOps

“In Mastering Python Networking, Third edition, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This new edition is completely revised and updated to work with Python 3. In addition to new chapters on network data analysis with ELK stack (Elasticsearch, Logstash, Kibana, and Beats) and Azure Cloud Networking, it includes updates on using newer libraries such as pyATS and Nornir, as well as Ansible 2.8. Each chapter is updated with the latest libraries with working examples to ensure compatibility and understanding of the concepts.”

Data Science from Scratch: First Principles with Python

“Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with New material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today’s messy glut of data.”

Python Pocket Reference: Python In Your Pocket

“Updated for both Python 3.4 and 2.7, this convenient pocket guide is the perfect on-the-job quick reference. You’ll find concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python tools. The handy index lets you pinpoint exactly what you need. Written by Mark Lutz—widely recognized as the world’s leading Python trainer—Python Pocket Reference is an ideal companion to O’Reilly’s classic Python tutorials, Learning Python and Programming Python, also written by Mark.”

Data Science Projects with Python: A case study approach to successful data science projects using Python, pandas, and scikit-learn

“Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The book will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive.You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package.”

Fundamentals of Python: First Programs

“This book’s easygoing approach is ideal, no matter what your background. The approach starts with simple algorithmic code and then scales into working with functions, objects, and classes as the problems become more complex and require new abstraction mechanisms. Rather than working only with numeric or text-based applications like other introductory texts, this edition presents graphics, image manipulation, GUIs, and simple networked client/server applications. The author uses Python’s standard Turtle graphics module to introduce graphics and to provide open source frameworks for easy image processing and GUI application development.”

Starting Out with Python

“With the knowledge acquired using Python, students gain confidence in their skills and learn to recognize the logic behind developing high-quality programs.  Starting Out with Python discusses control structures, functions, arrays, and pointers before objects and classes. As with all Gaddis texts, clear and easy-to-read code listings, concise and practical real-world examples, focused explanations, and an abundance of exercises appear in every chapter. Updates to the 4th Edition include revised, improved problems throughout, and new Turtle Graphics sections that provide flexibility as assignable, optional material.”

Pandas 1.x Cookbook: Practical recipes for scientific computing, time series analysis, and exploratory data analysis using Python

“This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.”

The Quick Python Book

“The Quick Python Book, Third Edition is a comprehensive guide to the Python language by a Python authority, Naomi Ceder. With the personal touch of a skilled teacher, she beautifully balances details of the language with the insights and advice you need to handle any task. Extensive, relevant examples and learn-by-doing exercises help you master each important concept the first time through. Whether you’re scraping websites or playing around with nested tuples, you’ll appreciate this book’s clarity, focus, and attention to detail.”

Trading Evolved: Anyone can Build Killer Trading Strategies in Python

“Systematic trading allows you to test and evaluate your trading ideas before risking your money. By formulating trading ideas as concrete rules, you can evaluate past performance and draw conclusions about the viability of your trading plan. Trading Evolved will guide you all the way, from getting started with the industry standard Python language, to setting up a professional backtesting environment of your own. The book will explain multiple trading strategies in detail, with full source code, to get you well on the path to becoming a professional systematic trader. This is a highly practical book, where every aspect is explained, all source code shown and no holds barred.”

Numerical Python: Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

“Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problem.”

Introduction to Computing Using Python: An Application Development Focus

“Perkovic’s Introduction to Programming Using Python: An Application Development Focus, 2e is more than just an introduction to programming. It is an inclusive introduction to Computer Science that takes the pedagogical approach of “the right tool for the job at the right moment,” and focuses on application development.  The approach is hands-on and problem-oriented, with practice problems and solutions appearing throughout the text. The text is imperative-first, but does not shy away from discussing objects early where appropriate. Discussions of user-defined classes and Object-Oriented Programming appear later in the text, when students have more background and concepts can be motivated.”

Deep Learning from Scratch: Building with Python from First Principles

“This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You’ll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way. Author Seth Weidman shows you how neural networks work using a first principles approach. You’ll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you’ll be set up for success on all future deep learning projects.”

Think Python: How to Think Like a Computer Scientist

“This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser.”

Python Automation Cookbook: 75 Python automation ideas for web scraping, data wrangling, and processing Excel, reports, emails, and more

“In this updated and extended version of Python Automation Cookbook, each chapter now comprises the newest recipes and is revised to align with Python 3.8 and higher. The book includes three new chapters that focus on using Python for test automation, machine learning projects, and for working with messy data. This edition will enable you to develop a sharp understanding of the fundamentals required to automate business processes through real-world tasks, such as developing your first web scraping application, analyzing information to generate spreadsheet reports with graphs, and communicating with automatically generated emails.”

Artificial Intelligence with Python: A Comprehensive Guide to Building Intelligent Apps for Python Beginners and Developers

“This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. Starting with AI basics you’ll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios.”

Architecture Patterns with Python: Enabling Test-Driven Development, Domain-Driven Design, and Event-Driven Microservices

“With this hands-on guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity—and get the most value out of their test suites. Each pattern is illustrated with concrete examples in beautiful, idiomatic Python, avoiding some of the verbosity of Java and C# syntax. Patterns include dependency inversion and its links to ports and adapters, domain-driven design’s distinction between Entities, Value Objects, and Aggregates, and Repository and Unit of Work patterns for persistent storage.”

Python by Example: Learning to Program in 150 Challenges

“This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader’s hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files.”

Introduction to Machine Learning with Python: A Guide for Data Scientists

“If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.”

Django 3 By Example: Build Powerful and reliable Python web applications from scratch

“In this book, you will build a blog application, a social image bookmarking website, an online shop, and an e-learning platform. Step-by-step guidance will teach you how to integrate popular technologies, enhance your applications with AJAX, create RESTful APIs, and set up a production environment for your Django projects. By the end of this book, you will have mastered Django 3 by building advanced web applications. This book is intended for developers with Python knowledge who wish to learn Django in a pragmatic way.”

Learn Python Programming: The no-nonsense, beginner’s guide to programming, data science, and web development with Python 3.7

“Learn Python Programming is a quick, thorough, and practical introduction to Python – an extremely flexible and powerful programming language that can be applied to many disciplines. You will explore the foundations of Python programming and learn how Python can be manipulated to achieve results. Explore different programming paradigms and find the best approach to a situation; understand how to carry out performance optimization and effective debugging; control the flow of a program; and utilize an interchange format to exchange data. You’ll also walk through cryptographic services in Python and understand secure tokens.”

Python Tricks: A Buffet of Awesome Python Features

“With Python Tricks: The Book you’ll discover Python’s best practices and the power of beautiful & Pythonic code with simple examples and a step-by-step narrative. You’ll get one step closer to mastering Python, so you can write beautiful and idiomatic code that comes to you naturally. Learning the ins and outs of Python is difficult—and with this book you’ll be able to focus on the practical skills that really matter. Discover the “hidden gold” in Python’s standard library and start writing clean and Pythonic code today.”

PYTHON

“In his book, Oliver Simpson teaches you everything there is to know about Python machine learning, data science, data analysis, and programming. Once you get the hang of the basics, this crash course will help you use all this knowledge for practical tasks and start programming in seven days! Readers will discover the basics of machine learning, essential skills for Python programming, how to master data science, and more.”

Test-Driven Development with Python: Obey the Testing Goat: Using Django, Selenium, and JavaScript

“By taking you through the development of a real web application from beginning to end, the second edition of this hands-on guide demonstrates the practical advantages of test-driven development (TDD) with Python. You’ll learn how to write and run tests before building each part of your app, and then develop the minimum amount of code required to pass those tests. In the process, you’ll learn the basics of Django, Selenium, Git, jQuery, and Mock, along with current web development techniques.”

NOW READ: The Best Python Certifications Online

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