Learn Core Python, Numpy and Pandas

Learn all the importance concepts about Core Python, Numpy and Pandas
Rating: 4.3 out of 5 (709 ratings)
23,535 students
Learn Core Python, Numpy and Pandas
Rating: 4.3 out of 5 (709 ratings)
23,535 students
Python
Numpy
Pandas

Requirements

  • Basic programming

Description

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 not a 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

Who this course is for:

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

Course content

4 sections • 64 lectures • 2h 50m total length
  • Setting up free jupyter notebook on Google
    02:07
  • How to use Jupyter notebook
    01:46
  • Variables in Python
    02:43
  • Python Integer Data Type
    04:10
  • Python String Data Type
    03:42
  • Taking Input
    00:55
  • Python Boolean Data Type
    01:59
  • Python Blocks
    01:37
  • if else statement
    01:19
  • if elif else
    01:19
  • Boolean Logic
    03:18
  • While Loop
    03:55
  • Python Lists
    03:49
  • Python List Operations - Append, Index, Max. Min
    04:16
  • Python Range
    01:09
  • Python Functions
    07:54
  • Passing variable arguments to functions
    01:33
  • Python Modules
    03:05
  • Python Exceptions
    08:20
  • Python File Handling
    03:23
  • None Data Type
    00:46
  • Python Dictionaries
    05:28
  • Tuples
    01:59
  • List Slices
    04:01
  • List Comprehensions
    01:10
  • Python String Functions
    03:26
  • Python List Functons - Any
    04:28
  • Python List All - Function
    02:22
  • Object Oriented Programming
    02:13
  • Object Oriented Programming - Methods and Class Level Attributes
    03:07
  • Object Oriented Programming - Inheritance
    03:51
  • Magic Methods
    01:27
  • Python Object Lifecycle
    01:14
  • Python Garbage Collection
    02:49
  • Object Data Hiding- Weak Method, Private Method
    02:28
  • Object - Class and static methods
    02:10

Instructor

Demystifying Machine Learning
Vishal Kumar Singh
  • 4.3 Instructor Rating
  • 822 Reviews
  • 28,009 Students
  • 2 Courses

Vishal Singh has 20+ years of IT experience. He has seen software from the FoxPro and Clipper days. He has hands on experience in designing ML systems. Has worked extensively on machine learning NLP problems in bio science for gene extraction from text. The course design is based on his personal experiences of mastering machine learning