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Python for data science

What you will learn

Learn Python from scratch to advance

Python OOPS concept

All the Python concepts for data science

Python tutorial with detailed hands-on

Description

This course will help you learn python from scratch to advance with detailed hands-on on Anaconda Jupiter notebook.

All the topics needed for data science and machine learning will be covered in this course.

The following topics are covered in this course:

  1. Python Basics – Variables, print functions
  2. Basic Data Types in python
  3. String operations in python
  4. Data Types like List, Tuple, Set & Dictionary
  5. Python Conditional Statements: If-Else
  6. Looping statements: For loop, while loop, For-Else, etc
  7. List, Tuple, Set & Dictionary Comprehensions
  8. Python Functions
  9. Lambda Functions
  10. Iterable, Iterator, and Generator in python
  11. File Handling in python
  12. Exception Handling in Python
  13. Logging in Python
  14. Packages and Modules
  15. Python OOPS (Object Oriented Programming) – Class & Object
  16. Inheritance, Abstraction, Polymorphism & Encapsulation in python
  17. Python connectivity to MySQL
  18. Python connectivity to MongoDB
  19. Python connectivity to SQLite
  20. Map, Reduce, Filter & Zip functions in python
  21. Python connectivity to Cassandra
  22. Numpy
  23. Pandas basics
  24. Pandas Advanced
  25. Visualization

and many more…

This course is all about practical use and hands-on python. It will focus on the implementation of python programming and will deliver theory concepts on a need basis. At the end of this course, you will become a confident Python developer.

This course is a prerequisite for my upcoming Machine LearningΒ  & Data Science course.

More about Python:


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Python is a dynamic modern object-oriented programming language that is easy to learn and can be used to do a lot of things both big and small. Python is what is referred to as a high-level language. That means it is a language that is closer to humans than computers. It is also known as a general-purpose programming language due to its flexibility.

Python is object-oriented means it regards everything as an object. An object in the real world could be a person or a car.

Python is an interpreted language that does not need to be complied with for example java programming language.

It is interpreted and run on the fly at the same time.

Python has been used in a lot of places like in creating games, for statistical data and visualization, speech and face recognition.

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 a 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. that does not need to be complied with for example java programming language.
English
language

Content

Introduction

Python #1: Basics (Variables, Print, Basic Data Types, Math Operations)
Python #2: Type Casting in Python
Python #3: Plus (+) operation on all basic data types
Python #4: How to take input from the user
Python #5: STRING – indexing, slicing & transversing operations