Python

Build Strong Foundation of Python 3, Learn Python for Data Science, AI, Machine Learning, GUI and More...

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39 hours

Curriculum

✔31section ✔ 254lectures ✔ 38h 51m total length

  • Introduction To The Course

  • Installing Python And PyCharm
  • Hello World Program In Python
  • Some other mathematical operations in Python
  • Strings In Python
  • Accepting input from the user in Python
  • Performing operations on a string in Python
  • Variables in Python
  • In place operators in Python.
  • Writing our very first program in PyCharm
  • Coding Challenge Part 1

  • If statement in Python
  • Elif statement in Python
  • Introduction to lists in Python
  • List operations in Python
  • List functions in Python
  • Range function in Python
  • Code reuse and functions in Python
  • For Loop in Python
  • Boolean logic in Python
  • While loop in Python

  • Passing arguments to functions in Python
  • Making function return value in Python
  • Passing functions as arguments in Python
  • Modules in Python

  • Errors & exceptions in Python
  • Exception handling in Python
  • Finally block
  • File handling
  • Reading data from file
  • Adding data to the file
  • Appending to a file

  • Dictionaries
  • Dictionary Functions
  • Tuples
  • List Slicing
  • List Comprehension
  • String formatting
  • String functions
  • Numeric functions

  • Functional programming
  • Lambdas in Python
  • Map in Python
  • Filters in Python
  • Generators in Python

  • Introduction To Object Oriented Programming, Classes & Objects
  • Class Methods
  • Creating A Class & Defining Class Attributes
  • Instance Attributes & Constructor
  • Implementing Methods In Object Oriented Programming
  • Function Based vs OOP Way Of Writing Code
  • Inheritance
  • Multiple Inheritance
  • Multi-level Inheritance
  • Recursion in Python
  • Sets
  • Itertools
  • Operator overloading in Python
  • Data hiding in Python

  • Regular expressions in Python
  • Search & find all
  • Find & replace
  • The dot metacharacter
  • Caret & dollar metacharacter
  • Character class
  • Star metacharacter
  • Group

  • Tkinter : Hello world program
  • Tkinter: Using frames
  • Tkinter: Grid layout
  • Tkinter: Self adjusting widgets
  • Tkinter: Handling button clicks
  • Tkinter: Using classes
  • Tkinter: Using drop downs
  • Tkinter: Toolbar
  • Tkinter: Making Status Bar
  • Tkinter: Message box
  • Tkinter Drawing

  • Building Calculator App Part 1
  • Building Calculator App Part 2
  • Building Calculator App Part 3
  • Building Calculator App Part 4

  • Introduction To Databases
  • Introduction To PostgreSQL
  • Installing PostgreSQL On Windows
  • Installing PostgreSQL On Mac
  • Creating A Database
  • Creating Table & Adding Data
  • Reading Data From Database
  • Setting Up Virtualenv on Mac
  • Setting Up Virtualenv On Windows
  • Installing Psycopg2
  • Connecting To Database With Python Code
  • Creating Database Tables With Python
  • Adding Data To Database Tables With Python
  • User Submitted Data To Database
  • Creating App Layout
  • Adding Entries
  • Saving Entries To Database
  • Search Functionality
  • Listing All Entries

  • Introduction to Data Analysis Using Python
  • Installing Tools For Data Analysis
  • Introduction to Pandas & Series
  • Converting Dictionaries to Series
  • Introduction to Data Frames
  • Changing Column Sequence
  • Changing Columns & Transposing Dataframe
  • Reindexing Series & DataFrames
  • Deleting Rows & Coulumns
  • Arithmetic operations on dataframe and series
  • Arithmetic operations in between dataframe and series
  • Sorting series and dataframes
  • Sorting according to values
  • Handling duplicate values
  • Calculating sum, max & min values
  • Dropping nan values
  • Loading data from a file
  • Analyzing file data
  • Creating Numpy Array
  • 19 Another way to create an array
  • Logspace & Linspace
  • Slicing a Numpy Array
  • Advanced indexing and slicing techniques
  • Broadcasting
  • Iterating using ndite
  • Plotting data using Matplotlib
  • Analysing Supermarket Sales Data Part 1: Reading CSV File
  • Analysing Supermarket Sales Data Part 2: Switching Up The Theme
  • Analysing Supermarket Sales Data Part 3: Accessing Different Parts Of Data
  • Analysing Supermarket Sales Data Part 4: Selecting Rows On A Condition
  • Analysing Supermarket Sales Data Part 5: Queries To Find Conditional Data
  • Analysing Supermarket Sales Data Part 6: Sum, Max, Min & Average
  • Analysing Supermarket Sales Data Part 7: Using GroupBy To Group Data By Location
  • Analysing Supermarket Sales Data Part 8: Finding Market Share
  • Analysing Supermarket Sales Data Part 9: Classifying Shoppers
  • Analysing Supermarket Sales Data Part 10: Analysing Memberships & Ratings
  • Analysing Supermarket Sales Data Part 11: Answering Multiple Queries
  • Analysing Supermarket Sales Data Part 12: Classifying Sales By Day
  • Analysing Supermarket Sales Data Part 13: Classifying Sales By Month
  • Analysing Supermarket Sales Data Part 14: Classifying Sales By Hour
  • Analysing Supermarket Sales Data Part 15: Classifying Payment Types With Hour

  • Django Tutorial 1: Installing Django on Windows
  • Django tutorial 2: Creating Our First Django Project
  • Django tutorial 3: Creating Our Own App
  • Django tutorial 4: Overview Of an App in Django
  • Django tutorial 5: Creating Our Own Views in Django
  • Django tutorial 6: Applying Migrations
  • Django tutorial 7: Creating Books Table in Django
  • Django tutorial 8: Final Steps in Creating Table
  • Django tutorial 9: Adding Data to the Database Tables
  • Django tutorial 10: Filtering the Results
  • Django tutorial 11: Admin Pannel in Django
  • Django tutorial 12: Creating Another View in Django
  • Django tutorial 13: Connecting to the Database
  • Django tutorial 14: Creating Templates
  • Django tutorial 15: Rendering Templates
  • Django tutorial 16: Raising a 404 Error
  • Django tutorial 17: Designing The Detail View
  • Django tutorial 18: Removing The Hardcoded Urls
  • Django tutorial 19: Namespaces in Django
  • Django tutorial 20: Using Static Files In Django
  • Django tutorial 21: Creating Our Navigation Bar
  • Django tutorial 22: Navigation Bar Touchup
  • Django tutorial 23: Using Base Templates
  • Django tutorial 24: Generic Views In Django
  • Django tutorial 25: Design Touchup
  • Django tutorial 26: Form To Add Books
  • Django tutorial 27: Form part -2

  • Using virtual environment
  • Django 2 Lecture 1 Creating a project
  • Django 2 Lecture 2 Creating An App
  • Django 2 Lecture 3 Overview of an app
  • Django 2 Lecture 4 Creating a View
  • Django 2 Lecture 5 Applying Migrations
  • Django 2 Lecture 6 Creating Models
  • Django 2 Lecture 7 Creating Database Tables
  • Django 2 Lecture 8 Adding Data To Database
  • Django 2 Lecture 9 Filtering Results
  • Django 2 Lecture 10 Creating A Super User
  • Django 2 Lecture 11 Creating Another View
  • Django 2 Lecture 12 Connecting To The Database
  • Django 2 Lecture 13 Creating Templates
  • Django 2 Lecture 14 Using Render
  • Django 2 Lecture 15 Raising 404 Error
  • Django 2 Lecture 16 Designing The Detail View
  • Django 2 Lecture 17 Removing Hard Coded URLs
  • Django 2 Lecture 18 Using Namespaces
  • Django 2 Lecture 19 Using Static Files
  • Django 2 Lecture 20 Designing Navbar
  • Django 2 Lecture 21 Navbar Touchup

  • Flask Tutorial 1: Creating Directory Structure
  • Flask Tutorial 2: Hello world
  • Flask Tutorial 3: Routing
  • Flask Tutorial 4: Variables
  • Flask Tutorial 5: Dynamic Urls
  • Flask Tutorial 6: Passing Data To The Server
  • Flask Tutorial 7: Templates
  • Flask Tutorial 8: Templates Passing Data
  • Flask Tutorial 9: Using Templates
  • Flask Tutorial 10: Passing Form Data To Templates
  • Flask Tutorial 11: Using Cookies

  • Introduction to API
  • Building a basic REST API using Django REST Framework
  • `
  • Creating API Endpoints
  • Adding Image Field
  • Filtering
  • Search functionality
  • API Authentication

  • Python Web Crawler Part -1
  • Python Web Crawler Part -2
  • Python Web Crawler Part -3
  • Python Web Crawler Part -4
  • Python Web Crawler Part -5
  • Python Web Crawler Part -6
  • Python Web Crawler Part -7
  • Python Web Crawler Part -8
  • Python Web Crawler Part -9
  • Python Web Crawler Part -10
  • Python Web Crawler Part -11
  • Python Web Crawler Part -12
  • Python Web Crawler Part -13
  • Python Web Crawler Part -14
  • Python Web Crawler Part -15
  • Python Web Crawler Part -16
  • Python Web Crawler Part -17
  • Python Web Crawler Part -18
  • Python Web Crawler Part -19

  • Introduction to Selenium
  • Installing Selenium
  • Opening a URL
  • Automating Google Search
  • Find Elements By XPATH
  • Clicking Links
  • Refreshing a Webpage
  • Using Forward and Backward Navigation Buttons
  • Scrolling and Getting the Current URL

  • Building A Facebook Auto Poster

  • Writing Clean Python Code: Best Practices part 1
  • Writing Clean Python Code: Best Practices part 2
  • Writing Clean Python Code: Best Practices part 3
  • Writing Clean Python Code: Best Practices part 4
  • Writing Clean Python Code: Best Practices part 5

  • IP Address
  • Ports & Sockets
  • Creating A Client
  • Sending Messages
  • Using Buffer
  • Building The Messaging Functionality
  • Sending Messages To Client
  • Programming Send Functionality
  • Completing Our Chat App

  • Introduction To OpenCV
  • Installing OpenCV
  • Reading & Displaying Images
  • Capturing Video From Webcam
  • Drawing Shapes On Images
  • Mouse Callback Events
  • Manipulating Pixels
  • Color Spaces In OpenCV
  • Object Tracking In Images
  • Object Tracking In Videos
  • Simple Thresholding
  • Simple Thresholding Implementation
  • Adaptive Thresholding
  • Adaptive Thresholding Implementation
  • Geometric Transformation Of Images
  • Geometric Transformation Of Images Implementation
  • Image Blurring
  • Image Blurring Implementation
  • Averaging
  • Gaussian Filtering

  • Updating entries in Django with UpdateView
  • Bootstrap part 1: Introduction To Bootstrap
  • Bootstrap Part 2: Adding Bootstrap To Our Site
  • Bootstrap Part 3: Bootstrap Grid System
  • Bootstrap Part 4: Grid Classes Part 1
  • Bootstrap Part 5: Grid Classes Part 2
  • Bootstrap Part 6: Grid Column Offset
  • Bootstrap Part 7: Making Images Responsive
  • Bootstrap Part 8: Nesting of Rows & Columns

  • Introduction to Regular Expressions & Raw Strings
  • Search & Match Methods
  • Introduction To Meta Characters
  • Introduction To Plus Meta Character
  • Plus Meta Character Example
  • Introduction To Curly Braces
  • Curly Braces Example
  • Introduction To Wildcard
  • Wildcard Example
  • Optional Meta Character
  • Caret Meta Character
  • Character Classes Part 1
  • Character Classes Part 2

  • Conclusion

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Course Advantage

Complete Understanding of Python from Scratch

Python for Data Science and Machine Learning

Functions and Lambdas Expressions

Graphical User Interface (GUI) in Python

Data Analysis with Pandas

NumPy Array, NumPy Operations

Write your own Decorators and higher order functions

Build Games with Python

Write your own Custom Modules

CREATE your own Programs and Applications

If-else statement, For loop and While loop

Master Object Oriented Programming (OOP) in Python 3

Data Analysis with NumPy

Matplotlib for Data Visualization

DataFrames, Pandas Series, Pandas Matrix

Create your own Generators and other Iterators

Error and Exceptions Handling

About this Course

Read more

The Complete Python Course: Learn Python From Scratch

Here Is What You Get By Enrolling In This Course:

Word-By-Word Explanation: In the entire course, I explain each line of code, without skipping a single line of code.

Awesome Quality Content: Over 38+ hours of HD(1080p) Videos.

Well Structured & Easy To Learn: Course has been specially designed to make it easy for the students to learn Python, Django, Data Analysis, Flask, Tkinter, OpenCV, Desktop App development with PostgreSQL & Web Scraping.

Live Support: Your mentors will be available on whatsapp or chat box to always guide you in your journey of Python.

Here Is Everything You Will Learn In This Complete Course:

In this hands-on course, you will learn Python right starting from scratch to the level where you can build almost anything with it, be it a fully functional database oriented web application or an automation tool.

This course will teach you Python right from scratch from a very basic level and will gradually move you towards more advanced topics.

We not just cover all the Python basics but also the most popular Python libraries such as Django, Flask, Tkinter & Selenium.


The Complete Course is divided into 11 Major sections.

Here is a brief description of what you will learn in each section.


Section 1: Python.

This section covers all the basics of Python, starting right from installing the required tools to covering topics like mathematical operators, strings, accepting user input, string operations, variables, conditionals like if, elif, control structures such as while & for loop, functions, modules & packages, lists, file handling, OOP in Python, regular expressions. Almost every basic Python concept is covered in this section.


Section 2: Make GUI In Python Using Tkinter.

Once done with the basics, we know learn the Tkinter library which allows us to create desktop based applications with Python. We learn how to create GUI apps using Tkinter & Python and also build a fully functional Desktop app i.e a calculator.


Section 3: Making Database Oriented Desktop Apps With PostgreSQL.

Making a simple desktop app alone isn't sufficient, it needs a backend database to store some data. To do the same we learn how to connect our desktop apps to the backend. In this section we build a student management system software using Python, Tkinter to design the GUI & PostgreSQL database to store the data for our application in the backend.


Section 4: Data Analysis.

Python is being widely used in the data science domain and hence it is important to learn how to use Python to analyse data. Hence in this section we learn how to use the tools and techniques used to perform data analysis. We start off by learning the Pandas library which is used to perform data analysis and all the basic concepts like DataFrames, Reindexing, Indexing, Broadcasting and also learn how to perform data plotting and visualisation with the Matplotlib library.


Section 5: Python Web Framework Django.

This section will teach you how to build full-stack web applications with Python & Django. Django is one of the most popular web frameworks for Python and is used to program the back-end side of out web app. In this section we will learn Django right from basics and will build a simple book store web application. We will learn how to create models, how to route URL requests, how to create different views for our web app, how to integrate HTML templates and a lot more.


Section 6: Python Web Framework Flask.

Flask is a micro web framework for Python used to build simpler web apps. If you want to develop some simple and small websites, you can do so using Flask. In this section we cover flask basics suck as Routing, Dynamic URLs, Templates, passing data to the server & site cookies.


Section 7: REST APIs Using Django Rest Framework.

In this section we learn how to build our own REST APIs using the Django Rest Framework. If you already have a Django web app built, you can create API endpoints for it using the Django Rest Framework. In this section we will build a fully functional REST API with features such as search, filtering & authentication.


Section 8: Web Scraping in Python.

Python can also be used to crawl websites and gather data from it. In this section we learn the same, we build a web crawler which crawls up any website of our choice and gathers links from it. Web crawlers are used by many search engines to rank websites and in this section we learn how to build a smaller version of it using Python.


Section 9: Automation with Python & Selenium.

Python is widely used for automation as well, especially for testing. Selenium web driver is one such tool which has been built for automating tests but the same can be used for automating other browser based tasks as well. In this section we learn how to automate tasks using Selenium and will also build a Facebook Bot that automatically posts status for us.


Section 10: Best Practices: Writing Clean & Efficient Python Code.

To be a good Python engineer/ developer you need to know how to write clean, concise and efficient Python code. In this section we learn some of the best practice that you must follow while writing Python code so.


Section 11: Image Processing With Python & OpenCV.

Python can also be used to process and manipulate images and videos. In this section we learn how to use OpenCV library with Python to manipulate images. We learn some interesting things like capturing webcam video, tracking images from a live video, different image thresholding techniques, image blurring, averaging and Gaussain filtering.


So let's begin the journey of becoming an expert in Python.

Make sure to enrol in the course before the price changes.

Take yourself one step closer towards becoming a professional Python developer by clicking the "take this course button" now!

Join the journey.

Sincerely,

Krishanth M

Have Some Query ?

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You will have lifetime access to the courses and can watch the lectures anytime you want. So it is totally flexible and provides you the comfort of learning anytime anywhere. Also as the technologies progress we keep on updating our courses so you get the access to them too.

Your doubts will be solved on a live chat, as soon as you get a doubt just ping your mentor through the chat option and within 5-10 minutes you will be connected to him to solve your doubts.

Tutedude doesn't believe in the idea of teaching 100 students in 1 class where the student sometimes feels hesitant to ask some doubts and where the other student feels that this student is wasting his time by asking silly doubts. Moreover in this busy world it becomes difficult to attend the classes on a specific schedule. So we combined the benefits and provide you interactive video lectures and live one on one doubt solving to learn at your own pace and comfort.

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