Learn Core Python, Numpy and Pandas

Learn Core Python, Numpy and Pandas, available at Free, has an average rating of 4.45, with 64 lectures, based on 997 reviews, and has 34971 subscribers.

You will learn about Python Numpy Pandas This course is ideal for individuals who are Developers interested in learning Python or Developers interested in learning Numpy or Developers interested in learning Pandas It is particularly useful for Developers interested in learning Python or Developers interested in learning Numpy or Developers interested in learning Pandas.

Enroll now: Learn Core Python, Numpy and Pandas

Summary

Title: Learn Core Python, Numpy and Pandas

Price: Free

Average Rating: 4.45

Number of Lectures: 64

Number of Published Lectures: 64

Number of Curriculum Items: 64

Number of Published Curriculum Objects: 64

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Python
Numpy
Pandas

Who Should Attend

Developers interested in learning Python
Developers interested in learning Numpy
Developers interested in learning Pandas

Target Audiences

Developers interested in learning Python
Developers interested in learning Numpy
Developers interested in learning Pandas

The course covers Core Python, Numpy and Pandas. Numpy and Pandas are stumbling block for many people who venture in machine learning. This course will help students to understand machine learning code as Numpy, Pandas are the building blocks for machine learning. Please note this is nota machine learning course. Please note that I have covered only core concepts of Python and there is fare more to Python than what I have covered.

Google Python Notebook is used for code.

Following are the topics in Core Python.

Setting up Google Notebook
Variables in Python – String, Integer, Boolean
Python Blocks
If else statement
While Loop
List operations
Range
Functions
Modules
Exceptions
File Handling
Dictionaries
Tuples
List Slices
List Comprehensions
String functions
Any,All operations
Object Oriented Programming
Magic methods
Class and Static methods

Following are topics in Numpy and Pandas

What is Numpy
Numpy – Add, Subtract, Multiply
Numpy Dot Product
Numpy Slicing
Mixing Integer Indexing And Slice Indexing
Numpy Array Indexing
More Array Indexing
Boolean Array Indexing
Numpy Sum
Numpy Reshape
Numpy Tensors 1D, 2D,3D
Numpy Transposing
Numpy Broadcasting

Pandas

What is Pandas
Pandas Series
Pandas Series Index
Pandas Advantage Over Numpy
Pandas Loc and iLoc
Pandas example – Finding Max
Pandas Series Addition
Pandas Apply Function
Pandas DataFrames Introduction
Pandas DataFrame Index, Loc and ILoc
Pandas Sum Along Axis
Pandas DataFrame Addition
Pandas DataFrame ApplyMap
Pandas Reading A CSV File

Course Curriculum

Chapter 1: Core Python Programming

Lecture 1: Setting up free jupyter notebook on Google

Lecture 2: How to use Jupyter notebook

Lecture 3: Variables in Python

Lecture 4: Python Integer Data Type

Lecture 5: Python String Data Type

Lecture 6: Taking Input

Lecture 7: Python Boolean Data Type

Lecture 8: Python Blocks

Lecture 9: if else statement

Lecture 10: if elif else

Lecture 11: Boolean Logic

Lecture 12: While Loop

Lecture 13: Python Lists

Lecture 14: Python List Operations – Append, Index, Max. Min

Lecture 15: Python Range

Lecture 16: Python Functions

Lecture 17: Passing variable arguments to functions

Lecture 18: Python Modules

Lecture 19: Python Exceptions

Lecture 20: Python File Handling

Lecture 21: None Data Type

Lecture 22: Python Dictionaries

Lecture 23: Tuples

Lecture 24: List Slices

Lecture 25: List Comprehensions

Lecture 26: Python String Functions

Lecture 27: Python List Functons – Any

Lecture 28: Python List All – Function

Lecture 29: Object Oriented Programming

Lecture 30: Object Oriented Programming – Methods and Class Level Attributes

Lecture 31: Object Oriented Programming – Inheritance

Lecture 32: Magic Methods

Lecture 33: Python Object Lifecycle

Lecture 34: Python Garbage Collection

Lecture 35: Object Data Hiding- Weak Method, Private Method

Lecture 36: Object – Class and static methods

Chapter 2: Numpy

Lecture 1: What is Numpy

Lecture 2: Numpy – Add, Subtract, Multiply

Lecture 3: Numpy Dot Product

Lecture 4: Numpy Slicing

Lecture 5: Mixing Integer Indexing And Slice Indexing

Lecture 6: Numpy Array Indexing

Lecture 7: More Array Indexing

Lecture 8: Boolean Array Indexing

Lecture 9: Numpy Sum

Lecture 10: Numpy Reshape

Lecture 11: More Numpy Reshape

Lecture 12: Numpy Tensors 1D, 2D,3D

Lecture 13: Numpy Transposing

Lecture 14: Numpy Broadcasting

Chapter 3: Pandas

Lecture 1: Pandas Series

Lecture 2: Pandas Series Index

Lecture 3: Pandas Advantage Over Numpy

Lecture 4: Pandas Loc and iLoc

Lecture 5: Pandas example – Finding Max

Lecture 6: Pandas Series Addition

Lecture 7: Pandas Apply Function

Lecture 8: Pandas DataFrames Introduction

Lecture 9: Pandas DataFrame Index, Loc and ILoc

Lecture 10: Pandas Sum Along Axis

Lecture 11: Pandas DataFrame Addition

Lecture 12: Pandas DataFrame ApplyMap

Lecture 13: Pandas Reading A CSV File

Chapter 4: Machine Learning Course

Lecture 1: Bonus Machine Learning Course

Instructors

Vishal Kumar Singh
Demystifying Machine Learning

Rating Distribution

1 stars: 19 votes
2 stars: 47 votes
3 stars: 177 votes
4 stars: 367 votes
5 stars: 387 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!

Menu