Last updated on November 16th, 2017
Python is a very popular high-level language created by Guido van Rossum and first released in 1991. Python is named after the greatest comedy act of all time, Monty Python. Python can be used to create pretty much any type of application. Python has been popular for many years and it’s popularity shows no signs of stopping anytime soon. Been an in-demand language, knowing Python is definitely something beneficial for your career as a software developer. Python is a very widely used programming languages that can do almost anything. Having working knowledge of high level programming languages is something any software developer should have. Whether it is a script you need to run or a complete application, Python is something you can use in your daily life as a programmer. Here’s a list of some of the best Python books, courses, videos and tutorials in 2017 to help you learn Python.
Complete Python Bootcamp: Go from zero to hero in Python by Jose Portilla will make you a professional Python developer. This Python course is a complete Python bootcamp that goes in-depth and detail. You start at Python basics and go all the way to Python advanced features and techniques.This course teaches how to use both Python 2 and Python 3. Advanced Python features, like the collections module and timestamps are thoroughly explained. Complex topics like Python Decorators and Python Generators are explained in great detail. You will learn everything about Object Oriented Programming in Python. You will be able to make Python games. Some of the games you will make with Python are like Tic Tac Toe and Blackjack. you will learn how to create .py files. A particular focus is placed on the Jupyter Notebook system. You will use Jupyter Notebook system to create GUIs. This course includes Python quizzes, Python tests, and Python homework assignments. This Python online bootcamp is one of the best Python tutorials in 2017 for beginners.
Learning Python for Data Analysis and Visualization by Jose Portilla will teach you how to use Python to analyze and visualize data. This Python Data Analysis tutorial will teach how to use scientific computing modules and libraries to analyze data. You are required to have an intermediate skill level of Python programming. This course will show you how to work with various data formats with Python like JSON, HTML, and MS Excel Worksheets. Create and manipulate arrays using Numpy and Python. Use Pandas to create and analyze data sets. Create beautiful data visualization using Matplotlib and Seaborn libraries. You will build an amazing portfolio of Python data analysis projects. This Python visualization tutorial will help you understand Machine Learning and SciKit Learn. This is one of the best Python Data Analysis and Visualization tutorials in 2017.
Python for Data Science and Machine Learning Bootcamp by Jose Portilla will teach you how to use Python for Data Science and Machine Learning. You will use different Python frameworks and libraries such as NumPy, Pandas, Seaborn, Matplotlib, Scikit-Learn, Tensorflow and more. This Python tutorial will show you how to use Python to implement Machine Learning algorithms. You will use SciKit-Learn for Machine Learning. This tutorial will show you how use Matplotlib and Seaborn for data visualizations. Use Spark for Big Data analysis. You will understand what Natural Language Processing is along with Spam Filters. K Nearest Neighbors and K Means Clustering are discussed. You will learn all about Neural Networks. This Python data Science training will teach you how to support Vector Machines. Decision Trees and Random Forests are both explained. This is one of the best Data Science Python courses in 2017.
Python for Data Structures, Algorithms, and Interviews! by Jose Portilla will teach you how to master your Python job interview. This Python interview tutorial will teach you how to succeed in Python coding interviews and get a Python developer job. Python developers can make high salaries. This course will help you understand all major Python Data Structures and Python Algorithms. Non-technical Python interview questions and answers are discussed. You will prepare from 4 different Python mock interviews. These Python interview videos will help you understand and be able to explain everything you need to get a Python job. This is one of the best online training courses for mastering Python interviews in 2017.
Python for Financial Analysis and Algorithmic Trading by Jose Portilla will teach you how to use Python to conduct rigorous financial analysis and pursue algorithmic trading. This Python Trading course will guide you through everything you need to know to use Python for Finance and Algorithmic Trading. You will start off by learning the fundamentals of Python. Then you will proceed to learn about the various core libraries used in the Py-Finance Ecosystem, including jupyter, numpy, pandas, matplotlib, statsmodels, zipline, Quantopian, etc. You will be able to calculate financial statistics, such as daily returns, cumulative returns, volatility, etc. Use ARIMA models on Time Series Data. You will be able to optimize portfolio allocations. This Python Algorithmic Trading tutorial will help you learn about the Efficient Market Hypothesis. Use of NumPy will be made to quickly work with Numerical Data. You will use Pandas for Analyze and Visualize Data. Matplotlib will be used to create custom plots. You will learn how to use statsmodels for Time Series Analysis. This is one of the best Python Algorithmic Trading and Financial Analysis tutorials in 2017.
Machine Learning A-Z: Hands-On Python & R In Data Science by Kirill Eremenko, Hadelin de Ponteves and SuperDataScience Team will teach you Machine Learning using Python & R. These Python videos will teach you everything related to Machine Learning. You will build an army of powerful Machine Learning models. Then you will combine them to solve any problem. You will be able to handle different topics like Reinforcement Learning, NLP and Deep Learning. Using the knowledge you gain, you will know which Machine Learning model to use depending on the problem. This is one of the best Machine Learning Python tutorials in 2017.
Spark and Python for Big Data with PySpark by Jose Portilla will teach you how to use Python and Spark together to analyze Big Data. This Python and Spark tutorial will teach how to analyze huge data sets. Spark can perform up to 100x faster than Hadoop MapReduce. Spark 2.0 DataFrame framework is new in 2017, making it ideal to learn. Python and Apache Spark skills will help you in the Big Data job market. This Python and Apache tutorial will teach the basics with a crash course in Python. Then it teaches you how to use Spark DataFrames with the latest Spark 2.0 syntax. You will use the MLlib Machine Library with the DataFrame syntax and Spark. The latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees are all covered in this course. You will use Spark with Random Forests for classification. Use Spark’s MLlib to create Powerful Machine Learning Models. You will learn how to use Spark’s Gradient Boosted Trees. This PySpark tutorial will even teach you to use Spark Streaming to analyze tweets in real time. Using Spark and Natural Language Processing, you will build a Spam filter. The DataBricks Platform is introduced. You will set up on Amazon Web Services EC2 for Big Data Analysis. Make use of AWS Elastic MapReduce Services. You will work with a Spark Environment on Linux. This is one of the best Python PySpark and Apache Spark tutorials in 2017.
Zero to Deep Learning with Python and Keras by Jose Portilla and Francesco Mosconi will teach to understand and build Deep Learning models for images, text, sound and more using Python and Keras. This Python Deep Learning tutorial will help you understand and apply Deep Learning techniques to a variety of problems. The course is aimed at beginners and intermediate Python programmers and data scientists. You will start off with a review of Deep Learning applications and a recap of Machine Learning tools and techniques. Then you will learn about Artificial Neural Networks. You will understand how to solve Regression and Classification problems. You will use Python and Keras to build deep learning models. This Keras tutorial will teach you to apply deep learning to solve supervised and unsupervised learning problems involving images, text, sound, time series and tabular data. You will be able to look at the internals of a deep learning model without feeling overwhelmed and be able to change its parameters. This Python Deep learning course will teach you to build, train and usefully connected, convolutional and recurrent neural networks. This is one of the best Python Deep Learning and Keras tutorials in 2017.
Python Network Programming – Part 1: Build 7 Python Apps by Mihai Catalin Teodosiu will teach from zero programming to building great network apps with Python. This Python Network Programming tutorial will help you master all the Python key concepts starting from scratch. You need to fa Cisco IOS image to load into GNS3 or practice all the concepts on real network devices. After finishing this Python Networking tutorial, you will be able to create Python apps to automate daily networking tasks. Networking tasks like configuring devices, collecting information about the network, network discovery or testing by client simulations, etc. will be some of the tasks you will automate via Python. Use Python for connecting via SSH to any network device. Learn how to use Python for building customized network packets and send them to a network device. Connect via Telnet or SSH to any network device with Python. Query SNMP objects with Python on any network device. Use Python for querying, populating and updating a MySQL database. You will make use of Python for capturing, decoding and analyzing network packets. Build customized network packets and send them to a network device with the help of Python. Apply all these Python skills to build various tools for network interaction. The Python skills you gain will help you make more money or get a better job as a Python Network Engineer in 2017. This is one of the best Python Network Programming tutorials in 2017.
Automate the Boring Stuff with Python Programming by Al Sweigart is a Python course for non-programmers. This course is aimed at workers, students, administrators and anyone that wishes to get started with Python. You will get started by building simple Python programs related to automation. Then you will build Python programs that do interesting every day tasks. Programmatically generate and update Excel spreadsheets with Python. Using Python, you will crawl web sites and pull information from online sources. Write Python programs that can do text pattern recognition with “regular expressions” or regex. Parse PDFs and Word documents with the help of Python. Write Python programs that send out email notifications. You will use Python’s debugging tools to quickly figure out bugs in your code.This is one of the best Python tutorials for beginners in 2017 as it requires no programming experience.
The Python Mega Course: Build 10 Real World Applications by Ardit Sulce teaches you Python by 10 real world Python applications. You will learn how to use Python for websites, databases, web scraping, data science, web visualizations, image processing & more. This Python projects tutorial will show you how to build 10 different Python apps. You will use different Python based frameworks and libraries to build these Python apps. Using Flask, you will build web applications. You will do data analysis and build interactive data visualizations with Pandas and Bokeh. Scarp data from websites with Beautiful Soup. Use Smtplib for sending automated emails. Use Tkinter for building desktop applications. Do scientific computing with Numpy. Use Folium for building interactive web maps. Do batch geocoding of addresses with Geopy. This is one of the best Python application development courses in 2017.
Python Regular Expressions – Real World Applied Python by Chandra Lingam will teach you pattern matching skills for log mining, big data parsing, cleanup and preparation with regex in Python. You will be able to confidently use regular expression as a powerful text processing tool for data parsing, cleanup and preparation. This Python Regex tutorial will teach you how to use regular expression as a powerful text processing tool. You will minimize effort spent on custom development for data cleanup. This Python Regex tutorial will help you understand potential performance issues and techniques to address them. You will learn practical tips to use Python Regular Expressions. This is one of the best Python Regular Expression tutorials in 2017.
Python Crash Course by Eric Matthes is a fast-paced ride through the world of programming with Python. Eric Matthes is a high school math and science teacher who teaches Python.
Python Crash Course will teach you everything you need to know to write your own programs and it will teach you fast. This does not mean that it is not through or doesn’t give an explanation of what exactly you are doing. Basic programming concepts like classes and loops are explained while you are shown how to write good code and test it extensively. Python Crash Course walks you through three epic projects where you will build a game, build data visualizations and a simple web app. After completing these three projects, you will have all the skills necessary to build anything and everything in Python. This is one of the best Python 3 and Python 2 books in 2017.
Python Crash Course has a great style of writing that is easy to read and understand, making sure beginners will not be overwhelmed at all. This book is packed with fundamentals that are useful to programmers of any skill level. Python Crash Course is the fastest way to get up to speed with Python. This is one of the fastest, quickest and best Python books for beginners in 2017.
Learning Python by Mark Lutz is considered by many as the best books for learning Python. Mark Lutz is a leading Python trainer and author.
Learning Python is a comprehensive and in-depth look at the Python language and all its features. This book is packed with exercises, advanced language features, and even illustrations to give you the best education in Python. features such as Python’s syntax and statements are explored. More advanced Python features such as decorators, metaclasses and descriptors are also taught. Learning Python does not miss pretty much anything related to Python. This book is as detailed as it gets. This is one of the best Python books for programmers.
Learning Python is a great to begin Python, regardless if you’re a beginner or an advanced developer. This is a very conclusive and thorough book on Python, with over 1500 pages. Learning Python still remains one of the best ways to get started with python. This is one of the best Python books for beginners in 2017.
Fluent Python: Clear, Concise, and Effective Programming by Luciano Ramalho is for python developers who wish to ascend to the next level. Luciano Ramalho was a Web developer before the Netscape IPO in 1995, and switched from Perl to Java to Python in 1998.
Fluent Python is for programmers that are already familiar and comfortable with Python but what to reach the next level of proficiency. This hands-on guide teaches you how to write even better Python code by using often neglected features of Python. You are taught how to write better code by making your code more elegant and using Python features properly in a more efficient way. Data structures, Functions as objects and meta-programming are some of the things Fluent Python teaches you. This is one of the best advanced Python books.
Fluent Python is aimed at Python developers who are serious about becoming better at Python. A wide range of topics and subjects is touched upon by the book that builds on your existing knowledge of Python. This is one of the best python programming language books.
Effective Python: 59 Specific Ways to Write Better Python by Brett Slatkin is a Senior Staff Software Engineer at Google.
topics addressed include algorithms, objects, collaboration, etc. By the end of it all, will teach you how to write good Python code that is effective and easy to maintain.
Python Cookbook by
Python Cookbook is packed with practical Python recipes that cover a wide range of Python topics including data structures, algorithms, metaprogramming, etc.. The recipes also come with detailed code samples that tell you how and why to use them. Testing and debugging are also touched upon. Python Cookbook is all about writing code that is more robust, cleaner and faster.
Python Cookbook is a well written cookbook filled with all kinds of recipes that can be used by Python programmers. It is well organized and easy to follow along. Any aspiring Python chef needs to have this on their bookshelves. This is one of the best Python question and answer books in 2017.
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron will help you gain an intuitive understanding of the concepts and tools for building intelligent systems. This Python Machine Learning book will help you learn a range of techniques including simple linear regression and progressing to deep neural networks. You will explore several training models, including support vector machines, decision trees, random forests, and ensemble methods. This Python Machine Learning book will help you apply practical code examples without acquiring excessive machine learning theory or algorithm details
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow
Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow by Sebastian Raschka and Vahid Mirjalili is a practical approach to key frameworks in data science, machine learning, and deep learning. You will learn to use TensorFlow, make use of Keras neural network library and leverage scikit-learn. This Python Machine Learning will help you explore machine learning techniques using challenging real-world data.
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