Python Mastery Bootcamp: From Beginner to Expert

Python Mastery Bootcamp: From Beginner to Expert, available at $59.99, has an average rating of 4.8, with 74 lectures, 1 quizzes, based on 5 reviews, and has 24 subscribers.

You will learn about Python Syntax, comments, datatypes, variables, numbers, casting, strings, booleans, operators, list, tuples, sets, dictionary if…else, while loop, for loop, functions, lambda, array, classes, objects, inheritance, iterators, scope, modules, dates, maths, json regex, pip, try…except, user input, string formating, rapid prototyping, or for production-ready software development, handle big data and perform complex mathematics, software to create workflows This course is ideal for individuals who are Python is one of the most loved programming languages by developers, data scientists, software engineers, and even hackers because of its versatility, flexibility, and object-oriented features. or For anyone looking to switch careers into the tech world through coding It is particularly useful for Python is one of the most loved programming languages by developers, data scientists, software engineers, and even hackers because of its versatility, flexibility, and object-oriented features. or For anyone looking to switch careers into the tech world through coding.

Enroll now: Python Mastery Bootcamp: From Beginner to Expert

Summary

Title: Python Mastery Bootcamp: From Beginner to Expert

Price: $59.99

Average Rating: 4.8

Number of Lectures: 74

Number of Quizzes: 1

Number of Published Lectures: 74

Number of Published Quizzes: 1

Number of Curriculum Items: 75

Number of Published Curriculum Objects: 75

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Python Syntax, comments, datatypes, variables, numbers, casting, strings, booleans, operators, list, tuples, sets, dictionary
if…else, while loop, for loop, functions, lambda, array, classes, objects, inheritance, iterators, scope, modules, dates, maths, json
regex, pip, try…except, user input, string formating, rapid prototyping, or for production-ready software development,
handle big data and perform complex mathematics, software to create workflows

Who Should Attend

Python is one of the most loved programming languages by developers, data scientists, software engineers, and even hackers because of its versatility, flexibility, and object-oriented features.
For anyone looking to switch careers into the tech world through coding

Target Audiences

Python is one of the most loved programming languages by developers, data scientists, software engineers, and even hackers because of its versatility, flexibility, and object-oriented features.
For anyone looking to switch careers into the tech world through coding

What is Python?

Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.

It is used for:

web development (server-side),
software development,
mathematics,
system scripting.

What can Python do?

Python can be used on a server to create web applications.
Python can be used alongside software to create workflows.
Python can connect to database systems. It can also read and modify files.
Python can be used to handle big data and perform complex mathematics.
Python can be used for rapid prototyping, or for production-ready software development.

Why Python?

Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
Python has a simple syntax similar to the English language.
Python has syntax that allows developers to write programs with fewer lines than some other programming languages.
Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick.
Python can be treated in a procedural way, an object-oriented way or a functional way.

Good to know

The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular.
In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files.

Python Syntax compared to other programming languages

Python was designed for readability, and has some similarities to the English language with influence from mathematics.
Python uses new lines to complete a command, as opposed to other programming languages which often use semicolons or parentheses.
Python relies on indentation, using whitespace, to define scope; such as the scope of loops, functions and classes. Other programming languages often use curly-brackets for this purpose.

Course Curriculum

Chapter 1: Install Python and jupyter notebook step by step

Lecture 1: Start with Python

Lecture 2: How to Install Anaconda & Jupyter Notebook in windows step by step

Lecture 3: Install Anaconda & Jupyter Notebook

Lecture 4: Ask Anything Any Time

Chapter 2: Complete Python Tutorial For Beginners to Expert

Lecture 1: Learn Basic of Python Syntax, Python Indentation

Lecture 2: Create Variable in Python

Lecture 3: Variable Names in Python

Lecture 4: Assign Multiple Values to Variable in Python

Lecture 5: Output Variables in Python

Lecture 6: Global Variables in Python

Lecture 7: Built in datatype in python

Lecture 8: Numeric Data Type in Python

Lecture 9: Strings in Python

Lecture 10: Python String Slicing

Lecture 11: How to Split Strings in Python

Lecture 12: String Concatenation in Python

Lecture 13: String Formatting In Python

Lecture 14: Boolean Value in Python

Lecture 15: Operators In Python

Lecture 16: Python Lists And List Functions

Lecture 17: How to Access List Items in Python

Lecture 18: How to Change List Items in Python

Lecture 19: How to add List Items in Python

Lecture 20: How to remove Items From List

Lecture 21: How to Loop Through List in Python

Lecture 22: Python List Comprehensions

Lecture 23: How to Sort Lists in Python

Lecture 24: How to copy list in python

Lecture 25: How to join Two list in python

Lecture 26: Learn Python Tuples || Create Tuple in Python

Lecture 27: How to access tuple items python

Lecture 28: How to Update/Add/Remove an Item from Tuple in Python

Lecture 29: Unpacking a Tuple in Python

Lecture 30: Loop Through Python Tuple || Iterate Through Python Tuples

Lecture 31: how to join tuples in python

Lecture 32: Sets in Python

Lecture 33: How to Access items in Python Sets

Lecture 34: How To Add Set Items in Python

Lecture 35: How to remove an item from a set

Lecture 36: How to Join Two Sets in Python

Lecture 37: How To Use Dictionaries In Python

Lecture 38: How to access dictionary items in python

Lecture 39: Deleting & Clearing Python Dictionary items

Lecture 40: How to Iterate Loop Through a Dictionary in Python

Lecture 41: How to Copy Dictionary in Python || Python Dictionary Copy Function

Lecture 42: If Elif Else Statement in Python dictionary

Lecture 43: While Loop in Python

Lecture 44: For Loops in Python

Lecture 45: How To Use Functions In Python

Lecture 46: Lambda functions in Python

Lecture 47: What is Scope in Python || Scope, Global Variables and Global Keyword

Lecture 48: Modules in Python Explained | Python Built in Modules

Lecture 49: What are Math Modules in Python

Lecture 50: Try Except Exception Handling in Python || Exception Handling in Python

Lecture 51: Taking User Input in Python || User input in Python

Lecture 52: String Formatting In Python || How To Format String In Python

Lecture 53: File Handling in Python || Python File Handling || Python Tutorial for Beginners

Lecture 54: Ask Anything Any Time

Chapter 3: Bonus Content – Python Numpy

Lecture 1: Python Numpy Introduction and Installation

Lecture 2: How to Create NumPy Arrays || Creating 1 2 3 4 Dimensional Array

Lecture 3: Access Elements From a 2D 3D Numpy Array in Python

Lecture 4: NumPy Array Slicing || Slicing in Numpy Arrays || Slicing 2 D 3 D Array

Lecture 5: Data Type of NumPy Array

Lecture 6: Copy vs Views Numpy Python Array || NumPy Copy vs View || Python Numpy Tutorial

Lecture 7: NumPy Array Shape || Get Shape of Array

Lecture 8: NumPy Array Reshaping || 1D into 2D & 3D || Complete Python Numpy Tutorial

Lecture 9: NumPy Array Iterating || nditer 2D & 3D

Lecture 10: NumPy Joining Array || Concatenate & Stack || Complete Python Numpy Tutorial

Lecture 11: NumPy Splitting Array || np.array_split

Lecture 12: NumPy Searching Array || where & searchsorted

Lecture 13: NumPy Sorting Array || Sort() 1D, 2D, 3D Array

Lecture 14: NumPy Filter Array || Creating the Filter Array

Lecture 15: Numpy random Number

Lecture 16: Ask Anything Any Time

Instructors

Sharad Khare
Data Scientist || Data Analyst || AI-ML-DL Researcher

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4 stars: 1 votes
5 stars: 4 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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