Top 10 Python Books for Beginners & Advanced Programmers 2019

Python is a general-purpose interpreted programming language used for web development, machine learning, and complex data analysis. Python is a perfect language for beginners as it is easy to learn and understand. As the popularity of the language is soaring, the opportunities in Python programming are amplifying as well. If you wish to learn Python programming, there are plenty of books available in the market. Books provide you the ability to learn at your on time even if you are on the go and they go really in detail. We bring to you a list of 10 best Python books for beginners and advanced programmers. These books will help programmers of all skill levels, from amateurs to code wizards. The list also includes a few free Python books for beginners.

Best Python Books for Beginners

Python Crash Course

‘Python Crash Course’ by Eric Matthews is a fast-paced and comprehensive introduction to Python language for beginners, who wish to learn Python programming and write useful programs. The book aims to get you up to speed fast enough and have you writing real programs in no time at all. This book is also for programmers who have a vague understanding of the language and wish to brush up their knowledge before trying their hands on Python programming. As you work through the book, you will learn the use of libraries and tools such as Numpy and matplotlib and work with data to create stunning visualizations. You will also learn about the idea behind 2d games and Web applications and how to create them.

This 560 pages long book is majorly dissected into two parts. The first part of the book discusses the basics of Python programming and sheds lights on concepts such as dictionaries, lists, loops, and classes. You will understand the working of a Python program and learn how to write clean and readable code which creates interactive programs. The part ends with the topic of how to test your code before you add it to a project. The second part of the book follows a practical approach and will help you test your knowledge by presenting three different projects, an arcade game, a simple web application and data visualizations using Python’s libraries.

Head-First Python (2nd edition)

‘Head-First Python’ by Paul Barry is a quick and easy fix for you if you wish to learn the basics of Python programming without having to slog through counterproductive tutorials and books. The book will help you in gaining a quick grasp of the fundamentals of Python programming and working with built-in functions and data structures. The book then moves to help you build your own web application, exception handling, data wrangling, and other concepts. Head first Python makes use of a visual format rather than a text-based approach, helping you to see and learn better.

The author is Paul Barry, a lecturer at the Institute of Technology, Carlow, Ireland. Before entering the academic world, he worked for over a decade in the IT industry. He is the author of certain well-known programming books, such as Programming the Network with Perl, Head First Programming and Head First Python.

 

Learn Python the Hard Way (3rd Edition)

‘Learn Python the Hard Way’ by Zed A. Shaw (3rd Edition) is a collection of 52 perfectly collated exercises. You will have to read the code and type it precisely. Once typed, you will have to fix the mistakes in the code for a better understanding and watch the programs run. These exercises will help you understand the working of software, structure of a well-written program and how to avoid and find common mistakes in code using some tricks that professional programmers have up their sleeves.

The book begins it all by helping you install a complete Python environment, which helps you in writing optimized code. The book then discusses various topics, such as basic mathematics, variables, strings, files, loops, program design, and data structures among many others. The book is ideal for beginners who wish to learn Python programming through the crux of the language. The author is Zed A. Shaw, who is the creator of the Hard Way series which includes books on C, Python and Ruby programming language.

Python Programming: An Introduction to Computer Science (3rdEdition)

‘Python Programming’ by John Zelle is the third edition of the original Python programming book published in 2004, the second edition of which was released in 2010. Instead of treating this book as a source to Python programming, it should be taken as an introduction to the art of programming. This book will introduce you to computer science, programming, and other concepts, only using Python language as the medium for beginners. The book will discuss its contents in a style that is most suitable for beginners, who will find the concepts in the book easy to understand and interesting.

The third edition of this extremely successful book follows the path paved by the first edition and continues to test students through a time-tested approach while teaching introductory computer science. The most notable change in this edition is the removal of nearly every use of python eval() library and the addition of a section which discusses its negatives. The latest version also uses new graphic examples.

Free Python Books for Beginners

Learning with Python: How to Think Like a Computer Scientist

‘Learning with Python’ by Allen Downey, Jeff Elkner and Chris Meyers is an introduction to Python programming and using the language to create wonderful real-world programs. The book is divided into 20 sections and also includes a contributors list and a way forward. The initial sections discuss the basics of programming and what makes up a program. Then it moves on to basic Python concepts such as variables, functions, conditionals, fruitful functions and iteration. Towards the end, the book discusses the core concepts such as objects, inheritance, lists, stacks, queues, trees and debugging.

The book is available for free in a variety of formats, which include PDF, Postscript, Gzipped Rar and HTML. Users are free to download and print these files as the book is licensed under the GNU Free Documentation License. The book has also been translated in Spanish, Italian, German and Czech, and available for download.

A Byte of Python

‘A Byte of Python’ by C.H. Swaroop is a free book on Python programming with an aim to guide the beginner audience to an understanding of the Python language. The book will discuss the Python 3 version majorly, but will also help you adapt to the older versions of the language. The book is available in over 26 languages including Turkish, Swedish, French, Chinese, German, Spanish, Russian, Ukrainian, Portuguese and Korean. The translations have been provided by active community members who vigorously work to keep the edits going on as the book is updated.

The book initiates its approach with an introduction to what the book is about and what it demands from the readers concerning dedication. Then it describes Python and how it has emerged as one of the most powerful languages in the programming world. It then moves on to Python concepts and describes them in detail along with examples at every step. It culminates with how you can continue learning Python after reading this book and leaves you with a problem to solve, testing your skills even at the last step.

 

Best Python Books Advanced Programmers

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

Many commercial applications and projects have employed machine learning as an integral ingredient, and the number of applications doing so has only risen over the years. This book by Sarah Guido and Andreas C. Muller will teach you how to use Python programming language to build your own machine learning solutions. As the amount of data usage increases with the second, the limitation to machine learning applications is only our imagination.

Throughout the course of this book, you will learn about the steps required to create a rich machine-learning application using Python and scikit-learn library. The book will introduce you to the fundamental concepts and uses of machine learning, before moving on to the pros and cons of popular machine learning algorithms. You will then learn about the advanced methods for model evaluation and the concept of pipelines, which is used for encapsulating your workflow and chaining models. In conclusion, the book will provide suggestions to help you improve your data science skills.

 

Fluent Python: Clear, Concise, and Effective Programming

‘Fluent Python’ by Luciano Ramalho will be your hands-on-guide that will help you learn how to write effective Python code by using the most neglected yet best features of the language. The author will take you through the features and libraries of the language, and will help you make the code shorter, faster and readable.

The book covers various concepts including python data model, data structures, functions as objects, object-oriented idioms, control flow, and metaprogramming. Using this book, advanced Python programmers will learn about Python 3 and how to become proficient in this version of the language. The author is Luciano Ramalho, a Web Developer who has worked with some of the largest news portals in Brazil using Python and has his own Python training company.

Python Cookbook: Recipes for Mastering Python 3

‘Python Cookbook’ by David Beazley and Brian K. Jones will help you master your programming skills in Python 3 or help you update older Python 2 code. This cookbook is filled with recipes tried and tested with Python 3.3 is the ticket for experienced Python programmers who wish to take the approach to modern tools and idioms rather than just standard coding. The book has complete recipes for a variety of topics, covering Python language and its uses, along with tasks common to a large number of application domains.

Some of the topics covered in the book are but not limited to strings, data structures, iterators, functions, classes, modules, packages, concurrency, testing, debugging and exceptions. Throughout the book, the recipes mentioned above will presuppose that you have the necessary knowledge to understand the topics in the book. Each recipe contains sample code the reader can use in their projects. The code is followed by a discussion about the working of the code and why the solution works.

 

Programming Python: Powerful Object-Oriented Programming

‘Programming Python’ by Mark Lutz is ideal for programmers who have understood the fundamentals of Python programming and ready to learn how to use their skills to get real work done. This book includes in-depth tutorials on various application domains of Python, such as GUIs, the Web and system administration. The book will also discuss how the language is used in databases, text processing, front-end scripting layers, networking and much more.

he book will explain the commonly used tools, language syntax, and programming techniques through a brief yet clear approach. The book is filled with many examples that show the correct usage and common idioms. The book also digs into the language as a software development tool, along with multiple examples illustrated particularly for that purpose.

 

If you are looking for online Python tutorials or courses, then http://www.simpliv.com has a great list of community-curated and recommended top Python tutorials: Python tutorials and courses

Top Courses to Learn Python in Depth – Best of Lot

There is no doubt that Python is currently the world’s #1 programming language and the biggest advantage of that is it’s bringing more and more people into the programming world. In recent years, I have seen more people learning Python than any other languages, yes, not even JavaScript. Many of them learning Python to explore some awesome Data Science and Machine learning libraries provided by Python. Some people are also learning Python for web development and there are still many developers who are learning Python for scripting and automating trivial tasks. It doesn’t matter why you are learning Python at this moment, it’s a great thing in itself that you have decided to learn Python.

Top 10 Free Courses to Learn Python in Depth - Best of Lot

Even though I am a Java programmer and I have spent all my career coding in Java, I value Python very high for its versatility.

It not just become one more tool in your arsenal but also allows you to explore areas like Data Science and Machine learning, which is available or easy with Java or any other mainstream programming language like C++ or JavaScript.

It’s always a good decision to learn Python, so don’t worry if you are a beginner programmer or C++/Java expert trying to learn Python. Any time and money invested in learning Python will go a long way and pay rich dividends much like learning UNIX, SQL, and Data Structure and Algorithms.

In short, Python is here for a long run and I believe it has already survived the crucial 20+ years.

Some people like to start with free resources which are not bad because it encourages you to explore. Also free doesn’t mean garbage or bad, even though they are not as comprehensive as some of the paid resource they are still better with many others.

If you decide to learn Python and looking for some awesome resources then you have come to the right place. Earlier, I have shared a lot of free books, courses, and articles about Python and today I am going to share some more free courses to learn Python.

Without any further ado, here is my list of free Python programming courses for beginner and intermediate Python programmers. The course not just contains basic Python programming courses but also using OOP in Python and a Data Science with Python course, mainly for programmers who are learning Python for Data Science and Machine learning.

Top 10 Free Courses to Learn Python in Depth - Best of Lot1

Python Programming Resources you may like to explore

Python 1200: Practice for BEGINNERS
Learn Python from Basic to Advance with Projects in a day
Python Programming Tutorials For Beginners
Learn Python in a Day
Learn Programming with Python in 100 Steps
Python for Beginners: A Python Mega Course with 10 Projects
Learn Python Programming – Easy as Pie
Spark for Data Science with Python
Machine Learning, NLP & Python-Cut to the Chase
Image Processing Applications on Raspberry Pi – From Scratch
Python for Beginners 2017
Learn Python GUI with Tkinter: The Complete Guide
Selenium with Python
Guide to Python Programming Language
Python GUI Programming Projects using Tkinter and Python 3
Complete Python Course Go from zero to hero in Python
The Python 3 New Features from Python Enhancement Proposal
Learn Python Programming
Selenium WebDriver With Python 3.x – Novice To Ninja
Learn Python 3 from scratch to become a developer in demand
Learn Python Django – A Hands-On Course
Python Programming & Data Handling
Python for Beginners
Create Your Calculator: Learn Python Programming Basics Fast
The Complete Python Training for 2019: Work on 10 Projects
Fundamentals of Python for Data Mining
Python for Data Science, Data Analysis & Visualization: 2019
Python For Beginners In Arabic تعلم لغة البايثون
Complete Course of Machine Learning: Data Science in Python
Complete Python Beginners Bootcamp: Python Deluxe Edition
Python Acelerado
Python Pro – Python Basics for Machine Learning
GUI Automation using Python| Python Automation
Data Structures and Algorithms in Python
Machine Learning Basics: Classification models in Python
Python For Beginners With Exercises

That’s all about some of the best Python courses from Programmers and developers. Anyone who wants to learn Python for web development, data science, machine learning, deep learning, or automation can benefit from these free courses. I have also included some courses on Django, a popular web development framework for Python developers, so if you are thinking to start web development with Python you can take a look at those as well.

5 Best Python Online Courses on Simpliv

Learn Python Programming

Learn Python.jpg

A Note on the Python versions 2 and 3: The code-alongs in this class all use Python 2.7. Source code (with copious amounts of comments) is attached as a resource with all the code-alongs. The source code has been provided for both Python 2 and Python 3 wherever possible.

What’s Covered:

  • Introductory Python: Functional language constructs; Python syntax; Lists, dictionaries, functions and function objects; Lambda functions; iterators, exceptions and file-handling
  • Database operations: Just as much database knowledge as you need to do data manipulation in Python
  • Auto-generating spreadsheets: Kill the drudgery of reporting tasks with xlsxwriter; automated reports that combine database operations with spreadsheet auto-generation
  • Text processing and NLP: Python’s powerful tools for text processing – nltk and others.
  • Website scraping using Beautiful Soup: Scrapers for the New York Times and Washington Post
  • Machine Learning : Use sk-learn to apply machine learning techniques like KMeans clustering
  • Hundreds of lines of code with hundreds of lines of comments
  • Drill #1: Download a zip file from the National Stock Exchange of India; unzip and process to find the 3 most actively traded securities for the day
  • Drill #2: Store stock-exchange time-series data for 3 years in a database. On-demand, generate a report with a time-series for a given stock ticker
  • Drill #3: Scrape a news article URL and auto-summarize into 3 sentences
  • Drill #4: Scrape newspapers and a blog and apply several machine learning techniques – classification and clustering to these

How We Need to Keep Grow Up

 

Spark for Data Science with Python

Data Science in R

Taught by a 4 person team including 2 Stanford-educated, ex-Googlers and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with Java and with billions of rows of data.

Get your data to fly using Spark for analytics, machine learning and data science

Let’s parse that.

  • What’s Spark? If you are an analyst or a data scientist, you’re used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.
  • Analytics: Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease.
  • Machine Learning and Data Science : Spark’s core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We’ll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets.

How We Need to Keep Grow Up

 

Machine Learning, NLP & Python-Cut to the Chase

Machine Learningawf.jpg

Prerequisites: No prerequisites, knowledge of some undergraduate level mathematics would help but is not mandatory. Working knowledge of Python would be helpful if you want to run the source code that is provided.

Taught by a Stanford-educated, ex-Googler and an IIT, IIM – educated ex-Flipkart lead analyst. This team has decades of practical experience in quant trading, analytics and e-commerce.

This course is a down-to-earth, shy but confident take on machine learning techniques that you can put to work today

Let’s parse that.

The course is down-to-earth : it makes everything as simple as possible – but not simpler

The course is shy but confident : It is authoritative, drawn from decades of practical experience -but shies away from needlessly complicating stuff.

You can put ML to work today : If Machine Learning is a car, this car will have you driving today. It won’t tell you what the carburetor is.

The course is very visual : most of the techniques are explained with the help of animations to help you understand better.

This course is practical as well : There are hundreds of lines of source code with comments that can be used directly to implement natural language processing and machine learning for text summarization, text classification in Python.

The course is also quirky. The examples are irreverent. Lots of little touches: repetition, zooming out so we remember the big picture, active learning with plenty of quizzes. There’s also a peppy soundtrack, and art – all shown by studies to improve cognition and recall.

 

How We Need to Keep Grow Up

 

Image Processing Applications on Raspberry Pi – From Scratch

Image Processing Applications on Raspberry Pi - From Scratch

Image Processing Applications on Raspberry Pi is a beginner course on the newly launched Raspberry Pi 3 and is fully compatible with Raspberry Pi 2 and Raspberry Pi Zero.

The course is ideal for those who are new to the Raspberry Pi and want to explore more about it.

You will learn the components of Raspberry Pi, connecting components to Raspberry Pi, installation of NOOBS operating system, basic Linux commands, Python programming and building Image Processing applications on Raspberry Pi.

This course will take beginners without any coding skills to a level where they can write their own programs.

Basics of Python programming language are well covered in the course.

Building Image Processing applications are taught in the simplest manner which is easy to understand.

Users can quickly learn hardware assembly and coding in Python programming for building Image Processing applications. By the end of this course, users will have enough knowledge about Raspberry Pi, its components, basic Python programming, and execution of Image Processing applications in the real time scenario.

The course is taught by an expert team of Electronics and Computer Science engineers, having PhD and Postdoctoral research experience in Image Processing.

Anyone can take this course. No engineering knowledge is expected. Tutor has explained all required engineering concepts in the simplest manner.

The course will enable you to independently build Image Processing applications using Raspberry Pi.

This course is the easiest way to learn and become familiar with the Raspberry Pi platform.

By the end of this course, users will build Image Processing applications which includes scaling and flipping images, varying brightness of images, perform bit-wise operations on images, blurring and sharpening images, thresholding, erosion and dilation, edge detection, image segmentation. User will also be able to build real-world Image Processing applications which includes real-time human face eyes nose detection, detecting cars in video, real-time object detection, human face recognition and many more.

The course provides complete code for all Image Processing applications which are compatible on Raspberry Pi 3/2/Zero.

 

How We Need to Keep Grow Up

 

Python for Beginners 2017

Machine Learning, NLP & Pythonz.jpg

See why over 350,000 Simpliv members learn coding from Mark Lassoff and LearnToProgram.tv!

Few programming languages provide you with the flexibility and pure power of Python.

If you’re becoming a professional developer, or are early in your development career, adding the Python skill set isn’t just a resume embellishment. It’s an empowering language that will allow you to write procedural code in many types of environments and for many uses.

Python is commonly used for server side programming for complex web applications or as a middle tier language providing web services or a communication layer with larger ecommerce systems. That being said, it’s also a great language for beginners. The clear syntax makes it very easy to learn, and the powerful libraries make all types of programming possible. There are libraries for everything from games and graphics to complex mathematics to network and embedded programming.

 

How We Need to Keep Grow Up

Learn Python Programming

 

#cyber #onlinesecurityA Note on the Python versions 2 and 3: The code-alongs in this class all use Python 2.7. Source code (with copious amounts of comments) is attached as a resource with all the code-alongs. The source code has been provided for both Python 2 and Python 3 wherever possible.

What’s Covered:

  • Introductory Python: Functional language constructs; Python syntax; Lists, dictionaries, functions and function objects; Lambda functions; iterators, exceptions and file-handling
  • Database operations: Just as much database knowledge as you need to do data manipulation in Python
  • Auto-generating spreadsheets: Kill the drudgery of reporting tasks with xlsxwriter; automated reports that combine database operations with spreadsheet auto-generation
  • Text processing and NLP: Python’s powerful tools for text processing – nltk and others.
  • Website scraping using Beautiful Soup: Scrapers for the New York Times and Washington Post
  • Machine Learning : Use sk-learn to apply machine learning techniques like KMeans clustering
  • Hundreds of lines of code with hundreds of lines of comments
  • Drill #1: Download a zip file from the National Stock Exchange of India; unzip and process to find the 3 most actively traded securities for the day
  • Drill #2: Store stock-exchange time-series data for 3 years in a database. On-demand, generate a report with a time-series for a given stock ticker
  • Drill #3: Scrape a news article URL and auto-summarize into 3 sentences
  • Drill #4: Scrape newspapers and a blog and apply several machine learning techniques – classification and clustering to these

Using discussion forums

Learn Python Programming qw.jpg

Please use the discussion forums on this course to engage with other students and to help each other out. Unfortunately, much as we would like to, it is not possible for us at Loonycorn to respond to individual questions from students:-(

We’re super small and self-funded with only 2 people developing technical video content. Our mission is to make high-quality courses available at super low prices.

The only way to keep our prices this low is to *NOT offer additional technical support over email or in-person*. The truth is, direct support is hugely expensive and just does not scale.

We understand that this is not ideal and that a lot of students might benefit from this additional support. Hiring resources for additional support would make our offering much more expensive, thus defeating our original purpose.

It is a hard trade-off.

Thank you for your patience and understanding!

Who is the target audience?

Pythonhsh.jpg

  • Yep! Folks with zero programming experience looking to learn a new skill
  • Machine Learning and Language Processing folks looking to apply concepts in a full-fledged programming language
  • Yep! Computer Science students or software engineers with no experience in Java, but experience in Python, C++ or even C#. You might need to skip over some bits, but in general the class will still have new learning to offer you 🙂
Basic knowledge
  • No prior programming experience is needed 🙂
  • The course will use a Python IDE (integrated development environment) called iPython from Anaconda. We will go through a step-by-step procedure on downloading and installing this IDE.
What you will learn
  • Pick up programming even if you have NO programming experience at all
  • Write Python programs of moderate complexity
  • Perform complicated text processing – splitting articles into sentences and words and doing things with them
  • Work with files, including creating Excel spreadsheets and working with zip files
  • Apply simple machine learning and natural language processing concepts such as classification, clustering and summarization
  • Understand Object-Oriented Programming in a Python context

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Basic Python Interview Questions and Answers

Q1. What are the key features of Python?

Ans: These are the few key features of Python:

  • Python is an interpreted language. That means that, unlike languages like C and its variants, Python does not need to be compiled before it is run. Other interpreted languages include PHP and Ruby.
  • Python is dynamically typed, this means that you don’t need to state the types of variables when you declare them or anything like that. You can do things like x=111 and then x="I'm a string" without error
  • Python is well suited to object orientated programming in that it allows the definition of classes along with composition and inheritance. Python does not have access specifiers (like C++’s publicprivate), the justification for this point is given as “we are all adults here”
  • In Python, functions are first-class objects. This means that they can be assigned to variables, returned from other functions and passed into functions. Classes are also first class objects
  • Writing Python code is quick but running it is often slower than compiled languages. Fortunately,Python allows the inclusion of C based extensions so bottlenecks can be optimized away and often are. The numpy package is a good example of this, it’s really quite quick because a lot of the number crunching it does isn’t actually done by Python
  • Python finds use in many spheres – web applications, automation, scientific modelling, big data applications and many more. It’s also often used as “glue” code to get other languages and components to play nice.

Q2. What is the difference between deep and shallow copy?

Ans: Shallow copy is used when a new instance type gets created and it keeps the values that are copied in the new instance. Shallow copy is used to copy the reference pointers just like it copies the values. These references point to the original objects and the changes made in any member of the class will also affect the original copy of it. Shallow copy allows faster execution of the program and it depends on the size of the data that is used.

Deep copy is used to store the values that are already copied. Deep copy doesn’t copy the reference pointers to the objects. It makes the reference to an object and the new object that is pointed by some other object gets stored. The changes made in the original copy won’t affect any other copy that uses the object. Deep copy makes execution of the program slower due to making certain copies for each object that is been called.

Q3. What is the difference between list and tuples?

Ans: Lists are mutable i.e they can be edited. Syntax: list_1 = [10, ‘Chelsea’, 20]

Tuples are immutable (tuples are lists which can’t be edited). Syntax: tup_1 = (10, ‘Chelsea’ , 20)

Q4. How is Multithreading achieved in Python?

Ans:

  1. Python has a multi-threading package but if you want to multi-thread to speed your code up.
  2. Python has a construct called the Global Interpreter Lock (GIL). The GIL makes sure that only one of your ‘threads’ can execute at any one time. A thread acquires the GIL, does a little work, then passes the GIL onto the next thread.
  3. This happens very quickly so to the human eye it may seem like your threads are executing in parallel, but they are really just taking turns using the same CPU core.
  4. All this GIL passing adds overhead to execution. This means that if you want to make your code run faster then using the threading package often isn’t a good idea.

Q5. How can the ternary operators be used in python?

Ans: The Ternary operator is the operator that is used to show the conditional statements. This consists of the true or false values with a statement that has to be evaluated for it.

Syntax:

The Ternary operator will be given as:
[on_true] if [expression] else [on_false]x, y = 25, 50big = x if x < y else y

Example:

The expression gets evaluated like if x<y else y, in this case if x<y is true then the value is returned as big=x and if it is incorrect then big=y will be sent as a result.

GET STARTED WITH PYTHON

Q6. How is memory managed in Python?

Ans:

  1. Python memory is managed by Python private heap space. All Python objects and data structures are located in a private heap. The programmer does not have an access to this private heap and interpreter takes care of this Python private heap.
  2. The allocation of Python heap space for Python objects is done by Python memory manager. The core API gives access to some tools for the programmer to code.
  3. Python also have an inbuilt garbage collector, which recycle all the unused memory and frees the memory and makes it available to the heap space.

Q7. Explain Inheritance in Python with an example.

Ans: Inheritance allows One class to gain all the members(say attributes and methods) of another class. Inheritance provides code reusability, makes it easier to create and maintain an application. The class from which we are inheriting is called super-class and the class that is inherited is called a derived / child class.

They are different types of inheritance supported by Python:

  1. Single Inheritance – where a derived class acquires the members of a single super class.
  2. Multi-level inheritance – a derived class d1 in inherited from base class base1, and d2 is inherited from base2.
  3. Hierarchical inheritance – from one base class you can inherit any number of child classes
  4. Multiple inheritance – a derived class is inherited from more than one base class.

Q8. Explain what Flask is and its benefits?

Ans: Flask is a web micro framework for Python based on “Werkzeug, Jinja2 and good intentions” BSD license. Werkzeug and Jinja2 are two of its dependencies. This means it will have little to no dependencies on external libraries.  It makes the framework light while there is little dependency to update and less security bugs.

A session basically allows you to remember information from one request to another. In a flask, a session uses a signed cookie so the user can look at the session contents and modify. The user can modify the session if only it has the secret key Flask.secret_key.

Q9. What is the usage of help() and dir() function in Python?

Ans: Help() and dir() both functions are accessible from the Python interpreter and used for viewing a consolidated dump of built-in functions.

  1. Help() function: The help() function is used to display the documentation string and also facilitates you to see the help related to modules, keywords, attributes, etc.
  2. Dir() function: The dir() function is used to display the defined symbols.

Q10. Whenever Python exits, why isn’t all the memory de-allocated?

Ans:

  1. Whenever Python exits, especially those Python modules which are having circular references to other objects or the objects that are referenced from the global namespaces are not always de-allocated or freed.
  2. It is impossible to de-allocate those portions of memory that are reserved by the C library.
  3. On exit, because of having its own efficient clean up mechanism, Python would try to de-allocate/destroy every other object.

Q11. What is dictionary in Python?

Ans: The built-in datatypes in Python is called dictionary. It defines one-to-one relationship between keys and values. Dictionaries contain pair of keys and their corresponding values. Dictionaries are indexed by keys.

Let’s take an example:

The following example contains some keys. Country, Capital & PM. Their corresponding values are India, Delhi and Modi respectively.

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dict={'Country':'India','Capital':'Delhi','PM':'Modi'}
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print dict[Country]
India
1
print dict[Capital]
Delhi
1
print dict[PM]
Modi

Q12. What is monkey patching in Python?

Ans: In Python, the term monkey patch only refers to dynamic modifications of a class or module at run-time.

Consider the below example:

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# m.py
class MyClass:
def f(self):
print "f()"

We can then run the monkey-patch testing like this:

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import m
def monkey_f(self):
print "monkey_f()"
m.MyClass.f = monkey_f
obj = m.MyClass()
obj.f()

The output will be as below:

monkey_f()

As we can see, we did make some changes in the behavior of f() in MyClass using the function we defined, monkey_f(), outside of the module m.

Q13. What does this mean: *args**kwargs? And why would we use it?

Ans: We use *args when we aren’t sure how many arguments are going to be passed to a function, or if we want to pass a stored list or tuple of arguments to a function. **kwargsis used when we don’t know how many keyword arguments will be passed to a function, or it can be used to pass the values of a dictionary as keyword arguments. The identifiers args and kwargs are a convention, you could also use *bob and **billy but that would not be wise.

Q14. Write a one-liner that will count the number of capital letters in a file. Your code should work even if the file is too big to fit in memory.

Ans:  Let us first write a multiple line solution and then convert it to one liner code.

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with open(SOME_LARGE_FILE) as fh:
count = 0
text = fh.read()
for character in text:
    if character.isupper():
count += 1

We will now try to transform this into a single line.

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count sum(1 for line in fh for character in line if character.isupper())

Q15. What are negative indexes and why are they used?

Ans: The sequences in Python are indexed and it consists of the positive as well as negative numbers. The numbers that are positive uses ‘0’ that is uses as first index and ‘1’ as the second index and the process goes on like that.

The index for the negative number starts from ‘-1’ that represents the last index in the sequence and ‘-2’ as the penultimate index and the sequence carries forward like the positive number.

The negative index is used to remove any new-line spaces from the string and allow the string to except the last character that is given as S[:-1]. The negative index is also used to show the index to represent the string in correct order.

Q16. How can you randomize the items of a list in place in Python?

Ans: Consider the example shown below:

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from random import shuffle
x = ['Keep', 'The', 'Blue', 'Flag', 'Flying', 'High']
shuffle(x)
print(x)

The output of the following code is as below.

['Flying', 'Keep', 'Blue', 'High', 'The', 'Flag']

Q17. What is the process of compilation and linking in python?

Ans: The compiling and linking allows the new extensions to be compiled properly without any error and the linking can be done only when it passes the compiled procedure. If the dynamic loading is used then it depends on the style that is being provided with the system. The python interpreter can be used to provide the dynamic loading of the configuration setup files and will rebuild the interpreter.

The steps that is required in this as:

  1. Create a file with any name and in any language that is supported by the compiler of your system. For example file.c or file.cpp
  2. Place this file in the Modules/ directory of the distribution which is getting used.
  3. Add a line in the file Setup.local that is present in the Modules/ directory.
  4. Run the file using spam file.o
  5. After successful run of this rebuild the interpreter by using the make command on the top-level directory.
  6. If the file is changed then run rebuildMakefile by using the command as ‘make Makefile’.

Q18. Write a sorting algorithm for a numerical dataset in Python.

Ans: The following code can be used to sort a list in Python:

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list = ["1", "4", "0", "6", "9"]
list = [int(i) for i in list]
list.sort()
print (list)

Q19. Looking at the below code, write down the final values of A0, A1, …An.

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A0 = dict(zip(('a','b','c','d','e'),(1,2,3,4,5)))
A1 = range(10)A2 = sorted([i for i in A1 if i in A0])
A3 = sorted([A0[s] for s in A0])
A4 = [i for i in A1 if i in A3]
A5 = {i:i*i for i in A1}
A6 = [[i,i*i] for i in A1]
print(A0,A1,A2,A3,A4,A5,A6)

Ans: The following will be the final outputs of A0, A1, … A6

A0 = {'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4} # the order may vary
A1 = range(0, 10) 
A2 = []
A3 = [1, 2, 3, 4, 5]
A4 = [1, 2, 3, 4, 5]
A5 = {0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}
A6 = [[0, 0], [1, 1], [2, 4], [3, 9], [4, 16], [5, 25], [6, 36], [7, 49], [8, 64], [9, 81]]

Q20. Explain split(), sub(), subn() methods of “re” module in Python.

Ans: To modify the strings, Python’s “re” module is providing 3 methods. They are:

  • split() – uses a regex pattern to “split” a given string into a list.
  • sub() – finds all substrings where the regex pattern matches and then replace them with a different string
  • subn() – it is similar to sub() and also returns the new string along with the no. of replacements.

Q21. How can you generate random numbers in Python?

Ans: Random module is the standard module that is used to generate the random number. The method is defined as:

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import random
random.random

The statement random.random() method return the floating point number that is in the range of [0, 1). The function generates the random float numbers. The methods that are used with the random class are the bound methods of the hidden instances. The instances of the Random can be done to show the multi-threading programs that creates different instance of individual threads. The other random generators that are used in this are:

  1. randrange(a, b): it chooses an integer and define the range in-between [a, b). It returns the elements by selecting it randomly from the range that is specified. It doesn’t build a range object.
  2. uniform(a, b): it chooses a floating point number that is defined in the range of [a,b).Iyt returns the floating point number
  3. normalvariate(mean, sdev): it is used for the normal distribution where the mu is a mean and the sdev is a sigma that is used for standard deviation.
  4. The Random class that is used and instantiated creates an independent multiple random number generators.

Q22. What is the difference between range & xrange?

Ans: For the most part, xrange and range are the exact same in terms of functionality. They both provide a way to generate a list of integers for you to use, however you please. The only difference is that range returns a Python list object and x range returns an xrange object.

This means that xrange doesn’t actually generate a static list at run-time like range does. It creates the values as you need them with a special technique called yielding. This technique is used with a type of object known as generators. That means that if you have a really gigantic range you’d like to generate a list for, say one billion, xrange is the function to use.

This is especially true if you have a really memory sensitive system such as a cell phone that you are working with, as range will use as much memory as it can to create your array of integers, which can result in a Memory Error and crash your program. It’s a memory hungry beast.

Q23. What is pickling and unpickling?

Ans: Pickle module accepts any Python object and converts it into a string representation and dumps it into a file by using dump function, this process is called pickling. While the process of retrieving original Python objects from the stored string representation is called unpickling.

Django – Python Interview Questions

Q24. Mention the differences between Django, Pyramid and Flask.

Ans:

  • Flask is a “microframework” primarily build for a small application with simpler requirements. In flask, you have to use external libraries. Flask is ready to use.
  • Pyramid is built for larger applications. It provides flexibility and lets the developer use the right tools for their project. The developer can choose the database, URL structure, templating style and more. Pyramid is heavy configurable.
  • Django can also used for larger applications just like Pyramid. It includes an ORM.

Q25. Discuss the Django architecture.

Ans: Django MVT Pattern:

Django Architecture - Python Interview Questions - EdurekaFigure:  Python Interview Questions – Django Architecture

The developer provides the Model, the view and the template then just maps it to a URL and Django does the magic to serve it to the user.

Q26. Explain how you can set up the Database in Django.

Ans: You can use the command edit mysite/setting.py , it is a normal python module with module level representing Django settings.

Django uses SQLite by default; it is easy for Django users as such it won’t require any other type of installation. In the case your database choice is different that you have to the following keys in the DATABASE ‘default’ item to match your database connection settings.

  • Engines: you can change database by using ‘django.db.backends.sqlite3’ , ‘django.db.backeneds.mysql’, ‘django.db.backends.postgresql_psycopg2’, ‘django.db.backends.oracle’ and so on
  • Name: The name of your database. In the case if you are using SQLite as your database, in that case database will be a file on your computer, Name should be a full absolute path, including file name of that file.
  • If you are not choosing SQLite as your database then settings like Password, Host, User, etc. must be added.

Django uses SQLite as default database, it stores data as a single file in the filesystem. If you do have a database server—PostgreSQL, MySQL, Oracle, MSSQL—and want to use it rather than SQLite, then use your database’s administration tools to create a new database for your Django project. Either way, with your (empty) database in place, all that remains is to tell Django how to use it. This is where your project’s settings.py file comes in.

We will add the following lines of code to the setting.py file:

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DATABASES = {
     'default': {
          'ENGINE' : 'django.db.backends.sqlite3',
          'NAME' : os.path.join(BASE_DIR, 'db.sqlite3'),
     }
}

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Q27. Give an example how you can write a VIEW in Django?

Ans: This is how we can use write a view in Django:

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from django.http import HttpResponse
import datetime
def Current_datetime(request):
     now = datetime.datetime.now()
     html = "<html><body>It is now %s</body></html>" % now
     return HttpResponse(html)

Returns the current date and time, as an HTML document

Q28. Mention what the Django templates consists of.

Ans: The template is a simple text file.  It can create any text-based format like XML, CSV, HTML, etc.  A template contains variables that get replaced with values when the template is evaluated and tags (% tag %) that controls the logic of the template.

Django Template - Python Interview Questions - EdurekaFigure: Python Interview Questions – Django Template

Q29. Explain the use of session in Django framework?

Ans: Django provides session that lets you store and retrieve data on a per-site-visitor basis. Django abstracts the process of sending and receiving cookies, by placing a session ID cookie on the client side, and storing all the related data on the server side.

Django Framework - Python Interview Questions - EdurekaFigure: Python Interview Questions – Django Framework

So the data itself is not stored client side. This is nice from a security perspective.

Q30. List out the inheritance styles in Django.

Ans: In Django, there is three possible inheritance styles:

  1. Abstract Base Classes: This style is used when you only wants parent’s class to hold information that you don’t want to type out for each child model.
  2. Multi-table Inheritance: This style is used If you are sub-classing an existing model and need each model to have its own database table.
  3. Proxy models: You can use this model, If you only want to modify the Python level behavior of the model, without changing the model’s fields.

Web Scraping – Python Interview Questions

Q31. How To Save An Image Locally Using Python Whose URL Address I Already Know?

Ans: We will use the following code to save an image locally from an URL address

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import urllib.request
urllib.request.urlretrieve("URL", "local-filename.jpg")

Q32. How can you Get the Google cache age of any URL or web page?

Ans: Use the following URL format:

http://webcache.googleusercontent.com/search?q=cache:URLGOESHERE

Be sure to replace “URLGOESHERE” with the proper web address of the page or site whose cache you want to retrieve and see the time for. For example, to check the Google Webcache age of edureka.co you’d use the following URL:

http://webcache.googleusercontent.com/search?q=cache:edureka.co

Q33. You are required to scrap data from IMDb top 250 movies page. It should only have fields movie name, year, and rating.

Ans: We will use the following lines of code:

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from bs4 import BeautifulSoup
import requests
import sys
response = requests.get(url)
soup = BeautifulSoup(response.text)
tr = soup.findChildren("tr")
tr = iter(tr)
next(tr)
for movie in tr:
title = movie.find('td', {'class': 'titleColumn'} ).find('a').contents[0]
year = movie.find('td', {'class': 'titleColumn'} ).find('span', {'class': 'secondaryInfo'}).contents[0]
rating = movie.find('td', {'class': 'ratingColumn imdbRating'} ).find('strong').contents[0]
row = title + ' - ' + year + ' ' + ' ' + rating
print(row)

The above code will help scrap data from IMDb’s top 250 list

Data Analysis – Python Interview Questions

Q34. What is map function in Python?

Ans: map function executes the function given as the first argument on all the elements of the iterable given as the second argument. If the function given takes in more than 1 arguments, then many iterables are given. #Follow the link to know more similar functions.

Q35. How to get indices of N maximum values in a NumPy array?

Ans: We can get the indices of N maximum values in a NumPy array using the below code:

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import numpy as np
arr = np.array([1, 3, 2, 4, 5])
print(arr.argsort()[-3:][::-1])

Output

[ 4 3 1 ]

Q36. How do you calculate percentiles with Python/ NumPy?

Ans: We can calculate percentiles with the following code

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import numpy as np
a = np.array([1,2,3,4,5])
p = np.percentile(a, 50)  #Returns 50th percentile, e.g. median
print(p)

Output

3

Q37. What advantages do NumPy arrays offer over (nested) Python lists?

Ans:

  1. Python’s lists are efficient general-purpose containers. They support (fairly) efficient insertion, deletion, appending, and concatenation, and Python’s list comprehensions make them easy to construct and manipulate.
  2. They have certain limitations: they don’t support “vectorized” operations like elementwise addition and multiplication, and the fact that they can contain objects of differing types mean that Python must store type information for every element, and must execute type dispatching code when operating on each element.
  3. NumPy is not just more efficient; it is also more convenient. You get a lot of vector and matrix operations for free, which sometimes allow one to avoid unnecessary work. And they are also efficiently implemented.
  4. NumPy array is faster and You get a lot built in with NumPy, FFTs, convolutions, fast searching, basic statistics, linear algebra, histograms, etc.

Q38. Explain the use of decorators.

Ans: Decorators in Python are used to modify or inject code in functions or classes. Using decorators, you can wrap a class or function method call so that a piece of code can be executed before or after the execution of the original code. Decorators can be used to check for permissions, modify or track the arguments passed to a method, logging the calls to a specific method, etc.

Q39. What is the difference between NumPy and SciPy?

Ans:

  1. In an ideal world, NumPy would contain nothing but the array data type and the most basic operations: indexing, sorting, reshaping, basic elementwise functions, et cetera.
  2. All numerical code would reside in SciPy. However, one of NumPy’s important goals is compatibility, so NumPy tries to retain all features supported by either of its predecessors.
  3. Thus NumPy contains some linear algebra functions, even though these more properly belong in SciPy. In any case, SciPy contains more fully-featured versions of the linear algebra modules, as well as many other numerical algorithms.
  4. If you are doing scientific computing with python, you should probably install both NumPy and SciPy. Most new features belong in SciPy rather than NumPy.

Q40. How do you make 3D plots/visualizations using NumPy/SciPy?

Ans: Like 2D plotting, 3D graphics is beyond the scope of NumPy and SciPy, but just as in the 2D case, packages exist that integrate with NumPy. Matplotlib provides basic 3D plotting in the mplot3d subpackage, whereas Mayavi provides a wide range of high-quality 3D visualization features, utilizing the powerful VTK engine.

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Multiple Choice Questions

Q41. Which of the following statements create a dictionary? (Multiple Correct Answers Possible)

a) d = {}
b) d = {“john”:40, “peter”:45}
c) d = {40:”john”, 45:”peter”}
d) d = (40:”john”, 45:”50”)

Answer: b, c & d.

Dictionaries are created by specifying keys and values.

Q42. Which one of these is floor division?

a) /
b) //
c) %
d) None of the mentioned

Answer: b) //

When both of the operands are integer then python chops out the fraction part and gives you the round off value, to get the accurate answer use floor division. For ex, 5/2 = 2.5 but both of the operands are integer so answer of this expression in python is 2. To get the 2.5 as the answer, use floor division using //. So, 5//2 = 2.5

Q43. What is the maximum possible length of an identifier?

a) 31 characters
b) 63 characters
c) 79 characters
d) None of the above

Answer: d) None of the above

Identifiers can be of any length.

Q44. Why are local variable names beginning with an underscore discouraged?

a) they are used to indicate a private variables of a class
b) they confuse the interpreter
c) they are used to indicate global variables
d) they slow down execution

Answer: a) they are used to indicate a private variables of a class

As Python has no concept of private variables, leading underscores are used to indicate variables that must not be accessed from outside the class.

Q45. Which of the following is an invalid statement?

a) abc = 1,000,000
b) a b c = 1000 2000 3000
c) a,b,c = 1000, 2000, 3000
d) a_b_c = 1,000,000

Answer: b) a b c = 1000 2000 3000

Spaces are not allowed in variable names.

Q46. What is the output of the following?

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try:
    if '1' != 1:
        raise "someError"
    else:
        print("someError has not occured")
except "someError":
    print ("someError has occured")

a) someError has occured
b) someError has not occured
c) invalid code
d) none of the above

Answer: c) invalid code

A new exception class must inherit from a BaseException. There is no such inheritance here.

Q47. Suppose list1 is [2, 33, 222, 14, 25], What is list1[-1] ?

a) Error
b) None
c) 25
d) 2

Answer: c) 25

The index -1 corresponds to the last index in the list.

Q48. To open a file c:\scores.txt for writing, we use

a) outfile = open(“c:\scores.txt”, “r”)
b) outfile = open(“c:\\scores.txt”, “w”)
c) outfile = open(file = “c:\scores.txt”, “r”)
d) outfile = open(file = “c:\\scores.txt”, “o”)

Answer: b) The location contains double slashes ( \\ ) and w is used to indicate that file is being written to.

Q49. What is the output of the following?

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f = None
for i in range (5):
    with open("data.txt", "w") as f:
        if i > 2:
            break
print f.closed

a) True
b) False
c) None
d) Error

Answer: a) True

The WITH statement when used with open file guarantees that the file object is closed when the with block exits.

Q50. When will the else part of try-except-else be executed?

a) always
b) when an exception occurs
c) when no exception occurs
d) when an exception occurs in to except block

Answer: c) when no exception occurs

The else part is executed when no exception occurs.

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Best computer programming for beginners

Computer Programming for Beginners3
DESCRIPTION

This course is meant to introduce people who have no programming experience to the world of computer science. With the tech industry becoming one of the most trending fields in the job market, learning how to program can be one of the most important and meaningful skills. This course will teach the basic, foundation concepts of programming in an easy-to-follow manner.

The first part of the course will get students acquainted with some basic concepts used in programming and will lay the conceptual groundwork that the rest of the course will build upon. After learning the basic terms and concepts of computer programming, the next two sections of the course allow students to practice these concepts hand-on.

Students will follow along with basic examples in two programming languages: Python and JavaScript. Both languages are easy for beginners to learn and are very user friendly. This course won’t make you an expert programmer, but it will give you an exciting first look at programming and a foundation of basic concepts with which you can start your journey learning computer programming.

Who is the target audience?

BASIC KNOWLEDGE
Computer Programming for Beginners4
  • You don’t need any prior programming knowledge or experience
  • You should be able to use a PC at beginner level.
WHAT YOU WILL LEARN

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Best Javascript Specialist – simpliv

Best Javascript Specialist
DESCRIPTION

Javascript has become the most import language you can learn.

Years ago, you could produce a web site with HTML alone. Now, Javascript is a critical technology that makes not just interactive web sites– but full web applications. Modern sites don’t just display data but generally help users complete tasks such as making a reservation or buy an item.

Javascript is a critical part of these transactions. Handling everything from dynamic screen content to interacting with remote servers, every developer needs Javascript.

And, Javascript is not just a web language any more. Due to related technologies like Node and Phone Gap Javascript can now be used in web development (client and server side) and mobile development.

This is only part of the reason that Javascript is THE language to know.

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FACT: Javascript is the most desired skill among those who hire new (junior) developers.

(This means that Javascript skills– and certification– may just be your key to a job).

If you’re reading this we don’t have to sell you upon becoming a developer. You already know it’s one of the most lucrative (and fastest growing) career tracks out there– no degree required.

What Will I Learn to Do with Javascript?

Javascript is a powerful language.

Here are just a few of things you can do with Javascript–

  • Create applications that are constantly updated via a web service. Stock market, weather, and transportation apps work with web services to provide users with current information.
  • Create apps that take advantage of the HTML5 canvas which allows data visualizations, animations and even gaming!
  • Create applications with reactive interfaces that provide users with an optimized experience.

It’s tasks like this that make Javascript critical for developers. Javascript is essential to just about any project that appears on the web or in mobile.

This is where you can separate yourself from the average developer.

As a Designated Javascript Specialist, you are qualified to create, maintain and edit Javascript code. You’ll be able to help development teams create relevant, reactive web and mobile applications or even create applications on your own.

In this certification program you’ll learn:

Best Javascript Specialist1

  • How to Output to the console
  • How to output content to the browser window by manipulating the DOM
  • The getElementById() command
  • How to use variables in Javascript
  • Arithmetic with Javascript
  • The proper use of Javascript Operators
  • How to use Number Functions
  • Using Booleans
  • How programs make decisions with conditionals
  • If Statements and If… Else Statements
  • Nested If Statements
  • How to use the Javascript Switch statement
  • For Loops, While Loops, Do…While Loops
  • For…In Loops, Endless Loops, Break and Continue Statements
  • Javascript Simple Functions, Function Parameters, Functions that Return a Value
  • Coding for Javascript Events and Call back Functions
  • Javascript Dialog Boxes
  • Creating Javascript Arrays
  • Looping Through Arrays
  • Javscript Strings and String Functions to process text
  • Javascript Date Functions
  • Processing text with Javascript Regular Expressions
  • Working with the Browser DOM
  • Accessing Web Services with the xmlHTTPRequest() Object
  • Making Requests and Parameterized Requests
  • Working with Returned Text Content
  • Working with Returned XML Content
  • Understanding JSON notation and Parsing JSON content
  • Using Generic Javascript Objects
  • Working with the Javascript Audio and Video API
  • 2D Drawing, the Canvas and Javascript
  • Faux Multithreading with Javaascript
  • Custom Objects and OOP with Javascript

How Does the Certification Program Work?

First: Complete the Course

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Each of the certification courses includes 5 to 10 hours of video training. Each course also includes lab exercises to help you retain the information in the video lectures. The courses feature study guides, practice questions, and activities, all with one goal: to help you learn new coding skills in Javascript.

The courses are designed to be completed in a few days, if significant time is invested. However, you may spread the work out for as long as you’d like. There are no calendars or limits on individual courses. Simply work with the course until you’re confident that you’ve mastered the material.

Next: Pass the Exam

Once you complete the course, you’ll be eligible to sit for the exam. The exam is composed of fifty multiple choice questions with a minimum passing score of 80%. The exam isn’t designed to be difficult, but to verify that you retained the information in the course. You have up to an hour to complete the exam. However, most people complete the exam much more quickly. If you don’t pass the exam the first time you take it, you may sit for the exam again.

When you pass the exam and complete the class, you’ll have earned your certification as a Javascript specialist. Congratulations!

Receive Your Certificate and Badge

Now that you’re certified, you’ll receive your printable, full color digital certificate. Your certificate includes a link to a digital transcript page which will serve as verification of your achievement. You can place the badge on your personal website, portfolio, or resume. You also can automatically place the badge on your LinkedIn page.

Many individuals who receive these certifications place them in their email signature and other highly visible digital real estate to set them apart from other developers.

Who should get certified?

  • Graphic and Digital Designers
  • Startup Employees
  • Marketing Designers
  • Content Specialists
  • Agency Personnel
  • Students who want to be more Employable

…Anyone else who wants this critical skillset and proof of expertise

Why Should You Be Certified?

If you’re interested in pursuing a career in development, then the Javascript Specialist Designation is the place to continue your path. Almost every digital development project involves some level of Javascript, and experts are in demand. If you’re a business owner, this certification course is a great way to learn what you need to know to style your own website. It’s also a great way to train the members of your team who work with your web site to ensure that they’re using the latest and best Javascript practices. If you’re an agency or freelancer, the Javascript Specialist Designation is a great way to validate your skills — and even justify a rate increase. If you’re a student, the Javascript Specialist Designation separates you from other graduates and verifies that you possess specialized technical skills that all employers are seeking.

The Javascript Specialist designation is tangible proof of your mastery of the critical Javascript Skillset and will drive up your value regardless of the environment in which you work.

Who is the target audience?

  • Developers who want to earn the Javacript Specialist Credential, while learning Javascript
  • Developers who want to move from Desktop apps to the Web Space
  • New Developers who want to learn an important coding skill while earning a professional credential
BASIC KNOWLEDGE
  • A functional knowledge of HTML will be helpful.
WHAT YOU WILL LEARN
Computer System Protection - Anti-Hack and Other Advanced Strategies
  • Create internal and external scripts
  • Use the event-based coding paradigm
  • Use the console for test output
  • Output conten to the browser
  • Manipulate HTML DOM elements via Javascript
  • Declare and Initialize Variables
  • Understand how Javascript variables are “typed”
  • Use arithmetic operators with Javascript variables
  • Use Javacript’s built-in math functions
  • Create and use boolean variables
  • Evaluate conditions with if statements
  • Evaluate “either-or” scenarios with if.. else
  • Make complex decisions with else if structures
  • Apply the Javascript switch statement
  • Repeat sections of code using loops
  • Apply the structure and syntax of while loops
  • Distinguish between while and do…while loops
  • Use the for loop syntax
  • Use for..in loops to loop through Javascript objects
  • Recognize situations that result in endless loops and correct them
  • Define a simple function
  • Make a function call
  • Send parameters to a function for processing
  • Use return statements to make functions more modular
  • Understand the syntax for anonymous functions
  • Work with mouse events
  • Work with keyboard events
  • Use form events to validate form data
  • Pass and use the event object to obtain event properties
  • Use alert boxes to provide user with information
  • Use confirm and prompt dialog boxes to interact with users
  • Declare a basic array
  • Access and edit array elements
  • Loop through an array to access each array element
  • Understand functions associated with the array class
  • Use string functions to manipulate string values
  • Use string functions to search and replace characters within a string
  • Use date functions to work with current date and time
  • Use date functions to work with future or past dates and times
  • Create basic regular expressions
  • Test for string matches with regular expressions
  • Engage search and replace actions with regular expressions
  • Conceptualize DOM structure (Document Object Model)
  • Use getElementById() and innerHTML()
  • Alter DOM elements dynamically
  • Add and delete elements from the DOM
  • Locate elements within the DOM tree
  • Understand the fundamentals of Service Oriented Architecture
  • Use the xmlHttpRequest() Object to communicate with web services
  • Make get-style web service requests
  • Mark post-style web service requests
  • Work with text data returned from a service
  • Parse XML data returned from a service
  • Parse JSON content returned from a service
  • Understand and use JSON notation
  • Draw on the HTML5 canvas
  • Access built in device geo-location features with Javascript
  • Create custom Javascript classes
  • Instantiate and consume Javascript objects

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