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Python (Basic)

In the era of technology and digitalization we all needs to be be in touch and up to date with the programming languages to be on the top and to show up your talent. So, click on the link and get started with python programming language.


Python (Advanced)

In the era of technology and digitalization we all needs to be be in touch and up to date with the programming languages to be on the top and to show up your talent with the advanced features that you can add up to your application to make it more attractive and a product like. So, click on the link and get started with advanced python programming language.


Machine Learning

With the Advanced and the digital world we all want to be with a machine/robot that we can rely on. Step forward with the machine learning to get closed to the advanced robots that can mimic like we humans and also we can trust them. So, click on the link to get started with Machine learning.

Python Basics


Course Content


Module 1

  • Introduction to Python

-        Why is python so popular?

-        Future Technologies

-        Applications

-        Career in python

Module 2

  • Downloading and Installing Python IDE

-        Sources to download python

-        Installation of python on your system

-        Setting up the environment path

Module 3

  • Writing your first program

-        Introduction to python IDLE

-        Arithmetic operations in python

-        No declaration, No initialization

-        Different ways to print statements in python

Module 4

  • Python variables

-        Creating a variables in python with no declaration

-        Printing multiple mesaages with one line code

-        Arithmetic operation on variables of different datatypes

-        Arithmetic operation on string and int

Module 5

  • Operators in Python

-        Types of operators

-        Arithmetic operators

-        Comparison operators

-        Assignment operators

-        Logical operators

-        Bitwise operators

-        Membership operators

-        Identity operators

Module 6

  • if-else Statement (Part 1)

-        What is conditional statement?

-        Syntax of if-else-elif and nested if-else statements

-        Working of the conditional statements

-        Example to understand if-else-elif statements

-        Taking input from user

-        Real-life applications

Module 7

  • Loops in Python

-        What are loops?

-        Why do we need loops?

-        Types of loops

-        Syntax

-        Working of loops

-        Understanding loops(while and for) with example

-        Real-life applications

Module 8

  • Data structure in Python

-        What is data structure?

-        Types of data structure

-        Identifications of data structure

-        Understanding the uses of different types of data structure

-        Accessing, inserting, deleting, finding and sorting of data

-        Real-life applications

Module 9

  • Functions in Python

-        What are functions?

-        Syntax

-        Types of functions

-        Types of arguments

-        Understanding the creating of function with examples

-        What is NameError?

-        Difference between local and global variable

Module 10

  • Modules in Python

-        What is a module?

-        Creating a user-defined module

-        How to import a user-defined module

-        Using the in-built module

-        How to change the working directory in python?

-        Different ways to import a module

Module 11

  • File handling in Python

-        Introduction to file handling

-        Syntax of file handling

-        Different modes in file

-        Creating a file in different mode

-        How to use with statement with file handling?


·       Creating a Login/signup interface to send and receive messages

·       Creating a simple chatterbot to chat like a human.





Python Advance


Course Content



Object Oriented Programming

  • OOP Concepts

-        Introduction to OOPs

-        Overview of OOPs terminology

-        Creating a class

-        Documentation in classes

-        Creating a class variable

-        Using the magic method as constructor

-        Creating methods in python

-        Creating an object in python

-        Accessing the class variables and calling the methods using the objects

-        Deleting an object

-        Inheritance in classes

-        Calling the constructor method of one class onto the second class

-        Data hiding in classes

-        Real-life applications

Special Method

  • Magic Methods

-        Introduction to Dunders/Magic methods

-        Types of magic methods

-        Syntax

-        Magic methods in OOPs

-        Correct way to create a python script using magic methods

-        Understanding some magic methods with example

-        Real-life applications

CGI Programming

  • CGI Programming (Part-1)

-        What is CGI programming?

-        CGI Architecture

-        Creating your first program in cgi programming

-        Setting up the path to create a cgi script

-        Understanding how to check the output of a cgi script with example

  • CGI Programming (Part-2)

-        Creating a server based survey form using cgi programming

-        Using “cgi” module in python for creating a survey form

-        Adding different widgets to the server based survey form

-        Taking input from user to proceed


  • Generators & Iterators

-        What is iterator and generator?

-        Syntax

-        Iterators and generators in classes

-        Using the yield function in python

-        Understanding iterators and generators with examples

-        Real-life applications

MySQL Database Access

  • MySQL Database

-        What is MySQL?

-        Downloading and Installation of MySql

-        Downloading and Installation of WampServer

-        Installing the pymysql module

-        Getting started with the basics of MySQL commands to maintain records

-        Creating our first program to link mysql with python

-        Appending, updating and deleting the data to the existing table in the database

-        Understanding and troubleshooting the AttributeError

-        Real-life applications

Networking in Python

  • Socket Programming (Part-1)

-        What is socket programmimg?

-        Learning the use of “socket” module

-        Checking the ip address of any website

-        Creating our first program for socket programming

  • Socket Programming (Part-2)

-        Creating the separate server and client python script to send and receive data with an example.

-        Real-life applications

Sending Email

  • Sending email in python

-        What is SMTP?

-        Syntax

-        Creating our first program to send an email without anuy subject using gmail

-        Understanding the actual and valid way to login to gmail and to send email without getting any error

-        Troubleshooting the error

-        Creating a  program to send an email with subject using gmail

-        Real-life applications


GUI Programming

  • GUI in Python (Part-1)

-        What is GUI?

-        Modules used for GUI in python

-        Getting started with tkinter module to build up our first desktop application

-        Adding different widgets to our application

--  Label

-- Messagebox

-- Button

-- Canvas

-- Checkbutton

--  Entry

-- Listbox

  • GUI in Python (Part-2)

-        Adding different widgets to our application

-- Message

-- Radiobutton

-- Scale

-- Scrollbar

-- Spinbox

-- Labelframe

-- Text

-- Menu

-- TopLevel

-        Creating your own notepad with a proper menu options

-        Real-life applications of GUI


·       Creating a Login/signup application to send and receive messages

·       Creating an application for data sorting and analysis using MYSQL to maintain record and for data storing using excel in python


Machine Learning

Course Contents


  • Introduction to Machine Learning

-        What is machine learning?

-        Need for machine learning

-        Types of machine learning and its explanation

-        Mathematics required for machine learning

-        Real-life Applications

Python for data analysis
  • Numpy (Part-1)

-        Scalar, vector and matrix

-        Steps to machine learning

-        What is numpy?

-        Installation of numpy

  • Numpy (Part-2)

-        Different ways to import numpy

-        Creating, accessing, slicing and updating a multi-dimensional array

-        Understanding different ways to create your array in an easier and faster way

-        Scientific computation on an array

-        Random function in numpy

-        Calculating a dot product of different matrix

-         Applications

  • Pandas

-        Steps to machine learning

-        What is Pandas?

-        Installation of pandas

-        Creating a series in pandas

-        Types casting between series and array

-        Different ways to create dataframe in pandas

-        Accessing, updating values in dataframe

-        Saving and reading data in pandas

-        Real-life applications

Python for data visualization
  • Matplotlib (Part-1)         

-        Introduction to matplotlib

-        Installation to matplotlib

-        Getting started with matplotlib

-        Creating a plot using the plot function with 1D and 2D matrix

-        Setting up the labelling for the plot

-        Loading the data from an excel file and using that data to plot the graph

-        Making your plot more attracting

  • Matplotlib (Part-2)

-        Using the scatter function in matplotlib

-        Creating a 3D plot using the data in matplotlib with an example

-        Real-life applications  

K Nearest Neighbors
  • Introduction to Supervised Learning

-        Types of supervised learning

-        What is classification?

-        Types of classification

-        What is K-Nearest Neighbors?

-        Installation of Sklearn

  • K Nearest Neighbors

-        Creating our first algorithm for machine learning to predict the category of a flower

-        Understanding the data gathered and preprocessing/preparing of data it to use it with the classification model

-        Choosing and training the model using the preprocessed/prepared data

-        Predicting the category of a flower

-        Real-life applications

Linear Regression
  • Linear Regression (Part-1)

-        Introduction

-        Types of supervised learning

-        What is regression?

-        Types of regression

-        What is linear regression?

  • Linear Regression (Part-2)

-        Creating an algorithm to predict the price for the given lot size using the Housing data

-        Using the steps for machine learning the create the effective algorithm

-        Plotting a linear curve according to the predicted data using the testing data

-        Applications

Comparing different classification models
  • Comparing classification models (Part-1)

-        Introduction to supervised learning

-        Sources to gather/collect data and download the heart disease data to compare different algorithm

-        Understanding the data(attributes) to compare the models

  • Comparing classification models (Part-2)

-        Preprocessing/preparing of data the data and splitting it into training and testing data

-        Normalizing  the data

-        Understanding different classification and regression models to be compared

-        What is logistic regression?

-        Using logistic regression and calculating it’s accuracy

  • Comparing classification models (Part-3)

-        K-Nearest neighbour with multiple number of neighbours to find the max accuracy

-        Support vector machine

-        Naive Bayes

-        Decision Tree

-        Random forest

-        Comparing all the above models and creating a bar plot for all of it

-        Basic introduction and use of seaborn for visualization

-        Real-life applications

K means Clustering
  • K-means clustering

-        Introduction to Unsupervised Learning

-        Types of unsupervised learning

-        What is clustering?

-        Types of clustering

-        What is K-Means Clustering?

  • K-means clustering (Part-2)

-        Understanding the data to use with K-Means

-        Creating an algorithm to categorize the data according to customer behaviour

-        Data gathering and preparing data

-        Choosing K-Means clustering model

-        What are centroids?

-        Training and predicting data

-        Visualising the data as per the predicted category

-        Real-life applications

Unsupervised Learning
  • Apriori Algorithm (Part-1)

-        What is association?

-        Types of association rule learning

-        What is Apriori algorithm?

-        What is frequent itemset, support, confidence, lift?

-        Installation and Understanding of mlxtend

  • Apriori Algorithm (Part-2)

-        Creating a recommendation system using the grocery data

-        How to handle the string data with machine learning algorithm?

-        Transaction Encoder

-        Use of dataframes in the program

-        Using the apriori algorithm to get all the combinations above the support value

-        How to find what are the products that can be sell together?

-        Use of lambda function in machine learning

-        Real-life applications

  • Principal Component Analysis
  • Projects

--  E-Commerce profitability and recommendation system for supermarket

-- Face recognition software to unlock Login/Signup to send/receive messages



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