Python Data Course: Python for Data Analysis & Visualization

Learn how to use Python powerful libraries to manipulate and process data to do data analysis & data visualization.

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Last Updated: 2023-07-12 05:07:43 English Course Type: Self Learning

What is Python libraries or modules & how to use its methods?
How to use Numpy + pandas in data Analysis And data Science.
How to use Python to manipulate & process data.
Data analysis & data visualization using Python.

The most important part of data science is understanding the data that is available to data scientists. You will only be able to achieve the best outcomes if you have the correct knowledge of data and the appropriate data for the task at hand. The analysis, Visualization, and manipulation of data are all very important in Data Science.

Everything about data analysis and data science is made exceedingly simple with Python. We may easily achieve any desired action by utilizing some of the top libraries available in Python. Pandas is one such package that allows us to examine and manipulate data in order to reduce the complexity and speed up the problem-solving process.

One of the best features available in Python for data analysis operations is the Python libraries for data processing and manipulation. You are capable of doing a wide range of jobs with ease. In this course, we'll look at the various sorts of operations that every data scientist must employ in order to complete a project with the least amount of resources while reaching the maximum level of efficiency.

What you will learn in this course ?

Learn Python by doing Examples step by step.
In this course you will learn how to Install Python 3.
In this course you will learn how to use python IDLE.
In this course you will learn how to choose Python IDE to learn coding.
In this course you will learn how to Install Anaconda for Python coding.
In this course you will learn how to use Online Jupyter for Python Programming.
In this course you will learn how to use Python IDLE.
In this course you will learn how What the difference between Variables & Operators in Python.
In this course you will learn Operators Types in Python.
In this course you will learn Python Data Types.
In this course you will learn String Functions & entries in Python.
In this course you will learn how to use Input String Function in Python.
In this course you will learn Python Data Structures.
In this course you will learn how to create Lists & lists operations in Python.
In this course you will learn how to create Dictionaries & Dictionaries operations in Python .
In this course you will learn how to create Tuples & Tuples operations in Python.
In this course you will learn and when to use For Loop in Python. to create Sets & Sets operations in Python.
In this course you will learn how and when to use Control Flow and Loops in Python.
In this course you will learn IF Statement and control flow in Python.
In this course you will learn how and when to use For Loop in Python.
In this course you will learn how and when to use While Loop in Python.
In this course you will learn how to Handle Errors in your Python programs.
In this course you will learn how and when to use Python Functions.
In this course you will learn how and when to create functions in Python.
In this course you will learn how and when to use Lambda Expression in Python.
In this course you will learn how to create and use to Python Modules.
Lear how to use Python to open files.
Learn Data Analysis Process step by step.
Learn coding in Python Numpy Library Methods in this course.
Learn how to use Numpy Library Methods & Functions to manipulate data in this course.
Learn how to use Numpy Library Methods & Functions to process images.
Learn coding in Python Pandas Library Methods in this course.
Learn coding in Python Pandas Library Data Analysis in this course.
Learn coding in Python Pandas Library Data Visualization in this course.

Computer and internet.
No primer programming experience needed for this course.

Are you want to learn more about Python data libraries Methods & Functions?
Are you want to learn more about Data Analysis using Python libraries?
Are you want to learn more about Pandas + Numpy?

Section 1 : Python Environment Preparing. 4 Lectures 00:31:11
Lecture 1 :
Introduction Preview
Lecture 2 :
Environment Preparing for Python
Lecture 3 :
Python2 VS Python3
Lecture 4 :
Understanding Data Types in Python
Section 2 : Python Refresher 7 Lectures 01:39:37
Lecture 1 :
Variables, Operators and Data Types in Python.
Lecture 2 :
String Functions in Python.
Lecture 3 :
Data Structures in Python.
Lecture 4 :
Control Flow VS Loops.
Lecture 5 :
Error Handling in Python.
Lecture 6 :
Functions in Python.
Lecture 7 :
Files and Modules in Python.
Section 3 : Object Oriented Programming (OOP) In Python. 9 Lectures 01:01:32
Lecture 1 :
Creating Simple Class.
Lecture 2 :
Overviewing Constructor.
Lecture 3 :
Learning How to creating Dunder Methods?
Lecture 4 :
Learning about Inheritance.
Lecture 5 :
Knowing What is the Encapsulation?
Lecture 6 :
Learning also about Multiple Inheritance.
Lecture 7 :
Knowing What is the Overriding?
Lecture 8 :
Learning about Decorators.
Lecture 9 :
Learning How to use Build-in Decorators?
Section 4 : Refresher Project 1 3 Lectures 00:16:32
Lecture 1 :
Project 1 Walk through
Lecture 2 :
Project 1 Helpful Notes
Lecture 3 :
Project 1 Solution
Section 5 : Refresher Project 2 4 Lectures 00:22:31
Lecture 1 :
Project 2 Walk through
Lecture 2 :
Project 2 Helful Notes
Lecture 3 :
Project Solution Part 1
Lecture 4 :
Project Solution Part 2
Section 6 : Refresher Project 3. 3 Lectures 00:17:09
Lecture 1 :
Project 3 Walk Through.
Lecture 2 :
Project 3 Helpful Notes.
Lecture 3 :
Project 3 Solution.
Section 7 : Data Analysis Process. 1 Lectures 00:03:06
Lecture 1 :
Data Analysis Process Overview.
Section 8 : Python Numpy 9 Lectures 01:00:52
Lecture 1 :
1. Numpy Intro.
Lecture 2 :
2. Numpy.shape & Numpy.size
Lecture 3 :
3. Creating Numpy nd arrays using Numpy functions.
Lecture 4 :
4. Numpy.unique( ) & Array slicing.
Lecture 5 :
5. Numpy Calculations and Operators.
Lecture 6 :
6. Numpy Aggregations.
Lecture 7 :
7. Numpy Reshape and Transposing.
Lecture 8 :
8. Numpy Comparing.
Lecture 9 :
9. Numpy Images Processing.
Section 9 : Python Pandas Data Analysis & Visualization 11 Lectures 00:55:42
Lecture 1 :
Installing Jupyter Lab & Pandas.
Lecture 2 :
SQL PostgreSQL Down and install
Lecture 3 :
Database Creation
Lecture 4 :
Database Restore
Lecture 5 :
Using Python Pandas Package to load PostgreSQL the Data Output file
Lecture 6 :
Fetchmany and Fetchall
Lecture 7 :
Querying Using Python Panadas
Lecture 8 :
Pandas methods and functions
Lecture 9 :
Visualizing Data
Lecture 10 :
Pandas Data Analysis
Lecture 11 :
Sampling Error
Section 10 : Web Scraping & Data Analysis Using Python & SQL. 4 Lectures 00:31:39
Lecture 1 :
How to Scrape a website in Python?
Lecture 2 :
Scrape a Table inside a Webpage using Pandas and LXML Python Modules!
Lecture 3 :
Data Visualization of the Scraped Data.
Lecture 4 :
Save The Scraped Data to a Database.
Section 11 : Final Project: Using Pandas + Automation to Manage a Business Email List. 3 Lectures 00:41:15
Lecture 1 :
Part 1
Lecture 2 :
Part 2
Lecture 3 :
Part 3

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Yes absolutely & thats one of the advantage of self-paced courses. You can anytime pause or resume the course & come back & forth from one lecture to another lecture, play the videos mulitple times & so on.
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Most of these courses have general questions & answers already covered within the course lectures. However, if you need any further help from the instructor, you can use the inbuilt Chat with Instructor option to send a message to an instructor & they will reply you within 24 hours. You can ask as many questions as you want.
Do i need a pc to access the course or can i do it on mobile & tablet as well?
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