Python Tutorial | Beginner Python Programming Free Course


Python Tutorial | Beginner Python Programming Free Course

Python is a programming language that lets you work quickly and integrate systems more effectively. Best way to learn python is gets your hands dirty with coding in python. These Python Tutorial will provide you the best learning experience for beginners who wants to learn python programming by follow along with these python tutorial.

Programming with Python: Hands-On Introduction for Beginners:

In These course, you will eliminate roadblocks to learn programming and you will able to start your own programs in Python 3 from scratch. It has over 38K students enrolled with 4.5 rating along with 3.5 Hours of video contents. You will learn how to obtain a strong understanding on the fundamentals of programming. How to write your own independent programs in python and you will understand the basics of Python language.

Course Outline:

  1. Introduction and Course Structure
  2. Installation for Windows
  3. Installation for Mac
  4. Installation for Linux
  5. What is variable and how to define one?
  6. Rules to define a variable
  7. Data Types in Python
  8. What are numbers and different types of Numbers in Python
  9. What is an operator?
  10. Different types of operators
  11. What is a string and how to define one?
  12. String operations
  13. What is a list and how to create one?
  14. List operations
  15. What is tuple and how to create one?
  16. What is dictionary and how to create one?
  17. Dictionary operations
  18. What are conditionals statements?
  19. Different types of conditional statements
  20. Using logical operators in conditional statements
  21. Program to check if a number is multiple of 3 and 7
  22. What are looping statements and implementation of For loop in Python
  23. While loop implementation in Python
  24. Nested loop implementation in Python
  25. Break, continue and else
  26. Program to check if a book exists in your collection of books
  27. What are functions and how to define one?
  28. Function with parameters and return values
  29. Program to find the greatest among two numbers
  30. What is exception handling and how to handle exception in python?
  31. Problem Statement of Project
  32. Project solution part 1
  33. Project solution part 2
  34. Conclusion


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The Four Pillars of OOP in Python 3 for Beginners

This course covers the Python OOP in a simplified way. You will learn Object oriented programming using python in a way that you really understand. You will also learn how to bundle attributes and methods within a class and instantiating them through an object. You will learn about the four pillars that hold together the object oriented programming and these are:


  • Abstraction
  • Encapsulation
  • Polymorphism
  • Inheritance


This course has over 27K students enrolled with 4.5 star ratings along with 2.5 hours of video contents for follow along.

Course Outlines:

  1. Introduction
  2. Installation for Windows,Mac and Linux
  3. Understanding Classes and Objects
  4. Implementation of Classes and Objects in Python
  5. Class Attributes and Instance Attributes
  6. Understanding the self parameter
  7. Static Methods and Instance Methods
  8. inti() method  – create a fully initialized object
  9. Abstraction and Encapsulation
  10. Performing Abstraction and Encapsulation in Python
  11. Understanding Inheritance and Performing a single inheritance in python
  12. Multiple Inheritance in Python
  13. Multilevel Inheritance in Python
  14. Public, Protected and Private – Naming Conventions in Python
  15. Overriding and the super() method
  16. The Diamond shape problem in multiple inheritance
  17. Overloading an Operator
  18. Implementing an Abstract Base Class
  19. Problem Statement of Final Project – SImulate a Banking System
  20. Project Solution part 1
  21. Project Solution part 2
  22. Conclusion


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Deep Learning Prerequisites: The Numpy Stack in Python:


In this course, you will learn about The Numpy, Scipy, Pandas and Matplotlib stack which is a preparation for deep learning, machine learning and artificial intelligence. This course is designed to show you how to do things in the Numpy stack that are frequently needed in deep learning and data science.


This course has over 81K students enrolled with 4.6 star ratings along with 3 hours of video contents so that you can follow along with the instructor.

Course Outlines:

  1. What’s this course about? How can you succeed? What should you know first?
  2. Where to get the code and how to install libraries
  3. Python 2 or Python 3?
  4. Lists vs Arrays
  5. Dot product 1: For loop vs cosine methods vs dot function
  6. Dot product 2: Speed comparison
  7. Vectors and Matrices
  8. Generating Matrices to Work With
  9. Matrix Products
  10. More Matrix Operations
  11. Solving a Linear System
  12. Word Problem
  13. Manual Data Loading
  14. DataFrames
  15. More about DataFrames: Selecting Rows and Columns
  16. Even More about DataFrames: Column Names
  17. The apply() Function
  18. Joins
  19. Line Chart
  20. Scatterplot
  21. Histogram
  22. Plotting Images
  23. Gaussian PDF and CDF
  24. Sampling from a Gaussian Distribution(1-D)
  25. Sampling from a Gaussian Distribution(Spherical and Axis-aligned Elliptical)
  26. Sampling from a General multivariate Normal
  27. Other Interesting Scipy Functions
  28. Conclusion


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Hope this free course will help you to develop your career as well as yourself. Also Checkout other Free Udemy Course and Let me know your opinion and share it with your friends. In future, i will provide review on more courses available out there. Stay connected with this blog and stay updated.

Nahidur Rahman Rifath

Passionate Software Engineer, Content Writer, Reader


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