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Top Python Books You Must Read in 2020

Of all the skills that we learn when growing up, possibly none is more significant than the ability to read. Each book that we read is an opportunity to learn something new as those who read can educate themselves in any area of life they would like to. While it can be easy to watch a  YouTube  Video  or listen to a podcast, reading still takes the cake when it comes to comprehension and increasing your knowledge.

We are in an age that is overflowing with new information. This makes critical reading the best way to rationalize and relate to further information. Reading big data books helps you train your brain, expand your vocabulary, lower stress, increase wellness and discover something new about yourself.

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One of the widely used programming languages globally is Python; praised for its user-friendliness, emphasis on simplicity and enhanced code readability, making it a most favorable choice for many developers around the world. And while JavaScript, Java, R, and other languages still play a considerably helpful role in writing code, Python is considered easy to learn, has a large library of toolkits, and integrates with other popular languages such as C and C++.

In the current business market where there’s a tidal change in technology, equipping yourself with soft Data Science skills is a considerably helpful move. And to ease the process, different Data Science Certified Bodies have been offering Data Science programs and self – learning platforms such as our 4IR Club which is a deliberate plunge into an online space where you can interact with materials to self – learn, re-tool, re-skill and self-adapt to the market demand. So to help you even more, here is a list of 10 python books to busy yourself with.

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1. Python Crash Course by Eric Matthes

Difficulty Level: Beginners

As the name suggests, Python Crash Course is a two-part book written to act as a quick crash course for readers with little to no programming exposure. It simplifies all the introductory concepts for beginners so they can start implementing their knowledge on easy practice exercises suggested in the book such as creating data visualization programs, and coding a 2D game. The expectation is that the book would give you hands-on experience (both in theory and practically) to hopefully turn you into a data scientist in a couple of weeks!

2. Learning Python by Mark Lutz

Difficulty Level: Beginners

“Learning Python” is a beginner book that depthly covers all the fundamentals of Python. It is a two-part series; tackling the basics of Python programming in the first, and practical examples in its second series. If you have zero proficiency with programming, it would be a good idea to supplement this book with additional introductory references which we talk about in the continuation of this reading list.

3. Python Tricks: A Buffet of Awesome Python Features by Dan Bader

Difficulty Level: Beginners

In any video game, gamers have a set of cheat codes or in-house tricks they use to unlock different levels of the game and enjoy a better play experience. In like manner, learning easy 123 tricks can change your user experience when interacting with machine learning languages. The book Python Tricks brings together a collection of convenient and well-explained features, tips, and tricks from a variety of topics to make you efficient with Python.

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4. Learn Python the Hard Way by Zed Shaw

Difficulty Level: Beginners

Contrary to its title, “Learn Python the Hard Way” presents the fundamental concepts of Python at a more beginner-friendly voice before introducing more complex topics. It includes plenty of instructional videos and exercises to enhance your knowledge of Python and its recent update supports Python 3.

5. Python for Data Analysis by Wes McKinney

Difficulty Level: Intermediate

If you constantly find yourself occupied with analyzing and manipulating structured data or are simply keen on learning about how efficient Python can be for data analysis tasks, this book will be useful to you. The book explains the fundamentals of working with data in a very comprehensive manner while also touching on scientific computing. Python for Data Analysis also covers some of the most popular libraries for data analysis, such as NumPy, pandas, matplotlib, IPython, and SciPy.

6. Introduction to Machine Learning with Python by Andreas C. Müller and Sarah Guido

Difficulty Level: Intermediate

Targeted towards aspiring Machine Learning professionals in search of solutions to real-world machine learning problems, this introductory book requires zero prior experience with Machine Learning. Instead of diving into the mathematics behind the algorithms and models being used throughout, the book takes a gentler approach and explains the background and their importance. The catch however is that you are required to have some knowledge of using Python to implement the vast collection of algorithms and models covered by the libraries followed in the book, such as scikit-learn, NumPy, and matplotlib.

7. Fluent Python by Luciano Ramalho

Difficulty Level: Experts

If you’re an advanced Python fellow, there are materials for you to become better already. Python can be a very versatile and powerful programming language when used efficiently, and this very motive is the sole driving factor for the book Fluent Python. It is clear that learning Python and achieving fluency in Python are both very different things. Most developers will often achieve what they want with Python anyways but at the cost of its full potential.

The author has emphasized on highlighting some of the less utilized features and techniques to make it possible to get the most out of Python. If you have recently started learning Python, this might not be the right book for you, as you might find it hard to follow.

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Just a few words!

We tend to underestimate the power of books yet they can open a whole new world, which is immersive and teaches us valuable lessons. The amount of material that is available for our disposal to learn is not affordant of any ignorant excuse. The books we’ve covered are but tinier than a water droplet, when compared to the material ready for our use. From tips to tricks there’s no way you will find it difficult to write a clear and optimized code in Python that works beautifully.

As the drive towards the 4th industrial revolution takes center stage, it is imperative that talents are realigned to meet the demand of the emerging landscape. We have designed an online resource platform that will give you a Life Long Learning opportunity to re-engineer your career and business to be adaptive to the demands of this Revolution. Please sign up at 4IR Club  and subscribe as an individual, company or government  to access our up to date resources.

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Lastly, if you want to become a master in your craft, then begin your journey to constantly learn Data Science Skills. You can begin it with us by joining our vast array of Data Science Programs. Visit predictive analytics lab for more details or drop us an email at


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