Major Project Training

1. Concept of OOPs
2. Knowledge of HTML
3. Knowledge of PHP-MySQL

Module 1: Introduction of Laravel PHP Framework

• Installing Laravel
• Artisan CLI (command-line interface)
• Laravel Directory Structure
• Configuring a new Laravel project
• MVC Structure

Module 2: Setting up a sample project in Laravel

• Basic routing and Name routing
• Resource route
• Controller
• Call a controller method from a route
• Passing variables from controllers to views

Module 3: Laravel Blade Template Engine

• Master layout in HTML/Bootstrap template
• HTML Template inheritance
• Displaying Your Template Views
• Loading a view into another view/nested views
• Adding assets in view pages

Module 4: Laravel Authentication & Authorization Concept

• HTTP Basic Authentication
• Middleware Authentication
• LaravelGuard Authentication
• Hashing

Module 5: Laravel Forms Validation and show error message

• Creating Registration form
• Validating user input
• Creating a file uploader
• Validating a file uploader and email and password etc.
• Creating a custom error message using laravel default error method

Module 6: Advanced SQL Queries

• Using Operators
• Grouping Records, Having Clause
• Joining Tables
• Select Record
• Insert Record
• Deleting Record

Module 7: Laravel Migrations and Migrate Table

• Introduction
• Php Artisan migration command
• Migration structure
• How to create a table using a migration
• Laravel migration rollback
• Migrations for our project database
• Database seeding

Module 8: Creating a registration & user login form

• Create user register and login system Using Auth
• Adding Custom Fields to Registration Form

Module 9: Laravel Eloquent ORM

• Eloquent ORM Models
• Table name and primary keys
• Eloquent ORM INSERT, READ,UPDATE, DELETE
• Displaying data from models in views
• Relationship

Module 10: Creating and Using Third-Party Packages

• Introduction
• Downloading and installing packages

Module 11: Using Ajax and jQuery

• Introduction
• Multiple dropdown dependency

Module 12: Create Restful APIs

• Introduction
• Building a Restful API with routes
• Creating crud API

Module 13: Live Project

At the end of module, all students get the expertise to develop an industry standard Laravel application. So, at this stage, we assign live project works to the students.

• C Language
• C++ / Java (Optional)
• Foundation of Python (Optional)

Module 1: Software Requirement Specification

• Installing Anaconda Navigator IDE (Python 3.6).
• Setting up class path of Python.
• Text Editor: Visual Studio Code.

Module 2: Basic Programs Handling Data Type

• Running python.
• Python identifier, keywords, comments etc.
• Assigning values to variable.
• Different data types in python.
• Python numbers, strings.

Module 3: Operators and Decision making in python

• Operators in python.
• Decision making in python.
• If elif else statement.
• Break and continue loops.
• While loops with else.
• For loop.

Module 4: Functions in python

• Defining a function with ‘def’ keyword.
• Calling a function in python.
• Pass by value and pass by reference.
• Local vs global variable.
• Modules and packages in python.
• Default argument, keyword argument and arbitrary argument.
• Programs on function.

Module 5: Data Structure in python

• Lists and its different functions.
• List comprehension.
• Dictionary and tuples.
• Set and empty set.
• Pop and push on set.
• Using list as stack.

Module 6: Jupyter Overview

• Implementing Jupyter Notebook.
• Web Application embed Visualization.

Module 7: Machine learning packages in python

• Numpy package.
• Panda package.
• Matplotlib package.
• Sklearn package.

Module 8: Numerical and Computation using packages

• Creating Numpy array and manipulation.
• Indexing and slicing of Numpy array.
• Numpy operations.

Module 9: Python for Data Analysis – panda

• Series, Data frames, Group by, Merging Joining.
• Programs using python data frames.
• Data Manipulation with Panda.

Module 10: Python for Data visualization – Matplotlib

• Data visualization with Matplotlib.
• Scatter Plot, Straight Line Plot.
• Plotting of images.

Module 11: Introduction to Machine Learning using UCI Machine Learning Repository

• What are Features?
• What are Labels?
• Pre-processing of Data (mean max normalization).
• Over fitting and Under fitting of Model.

Module 12: Regression problem

• Linear regression.
• Logistic regression.
• Polynomial regression.

Module 13: Classification Problems

• KNN.
• Naïve Bayes.
• Decision Tree.
• Support Vector Machine.

Module 14: Clustering Problems

• Introduction to Un-Supervised Learning.
• K-Means Clustering.

Module 15: NLP

• Working with Text Data.

Module 16: Project

Networking, Basic Computer fundamentals, System Knowledge, OS Knowledge, basic knowledge on any preferred language.

Module 1:

Concepts and Theory

• Cyber Ethics and Law & Introduction
• Networking Concepts
• Google Hacking Database
• Information Gathering1
• Footprinting using Google
• Website footprinting
• Email Tracking and Footprinting
• Checking Traffic of Website

Module 2:

LAB SETUP

• VIRTUAL LAB CREATION
• Installation of VMWARE
• Installation of Kali Linux OS and Configuration
• FOOTPRINTING AND RECONNAISSANCE
• Information Gathering2
• Network Scanning and FOOTPRINTING1
• Network Scanning and FOOTPRINTING2
• NETWORK SCANNING USING N MAP

Module 3:

Pentesting on Router

• ROUTER PENTESTING
• Theory and Lab Setup
• Practical Scanning, Enumeration, and Exploiting Router in Multiple Ways

Module 4:

Network Pentesting

• NETWORK PENTESTING
• Lab setup with Windows
• Windows EndPointsPentesting
• Theory and Practical
• BufferOverflow (Theory and Exploitation)

Module 5:

Network Pentesting

• Software Misconfiguration
• RDP Service Exploitation
• Social Engineering Begins(Theory and Practical)
• ATTACK WEAKEST LINK HUMAN
• Introduction to Metasploit
• How Firewall works?
• Exploit it

Module 6:

Network Pentesting& Cyber Security

• Challenge: Level 1: Bypass The Firewall of Windows
• Level 2: Increase The Security
• (BLOCK PORT) and Prevent Hacking
• Break the Updated and Advance above Blocked PORT Security Also.

Module 7:

Social Engineering & Challenges

• Level 3:Increase the Security (BLOCK RANGE OF PORTS) this is advance level security
• Break the LEVEL 3 challenge also
• Level 4: Most advanced security (Block All Ports)
• Break It
• Cyber Crime Study
• Analyse the Attacks
• How NASA was hacked?
• Gary Mckinnon NASA Hack Case Study
• Challenge: Do the same attack in your own virtual lab
• System Hacking Using Social Engineering

Module 8:

METASPOILT-FRAMEWORK

Challenge Continues

• Do the same attack in your own virtual lab
• Celebration of Passing All Challenge
• How Antivirus Works?
• Bypass TOP BRANDED Antiviruses
• INFORMATION GATHERING
• BASIC EXPLOITATION
• Antivirus
• Bypass Antivirus
• Beat Antivirus using Python
• Escalate Privilege
• Post Exploitation with UAC Bypass
• Dump Hashes &Mimikatz
• Remote Network Monitoring
• Windows Sessions, Stations and Desktops
• Keyboard, Mouse Hacking
• Impersonation
• Temper the PAC
• Block Websites using PAC

TEAMVIEWER IS DANGEROUS

GOOGLE CHROME CAN LEAD TO HACK THE SYSTEM

• ANDROID HACKING

Module 9:

Miscellaneous

• Hijack Session Between CtrlC & Ctrl V
• Man In The Middle Attack in Multiple Ways
• CCTV Hacking
• Webcam Hacking And Live Streaming
• HACK Microphone
• DOS ATTACK LIKE PRO AND Network Monitor

Module 10:

WEBAPP PENTESTING

• HACK Social Media Accounts using Phising Attacks
• SQL Injection
• XSS Attack
• JS AND HTML FUN FOR PENTESTERS
• SERVER HACKING

Module 11: REAL LIFE HACKING

 PROJECTS & HACKING TOOLS

Networking.

Module 1: Basics of Cloud computing

• Basic Idea of Computing and Cloud Computing
• Problems without Cloud Computing
• Advantages and Disadvantage of Cloud Computing
• Business Drivers in Cloud
• Overview of Security Issues
• Types of Cloud Computing
• Cloud Delivery Models

Module 2: Introduction to AWS

• AWS Fundamentals
• AWS Cloud Computing Platform
• Accessing AWS Platform
• Creating AWS Account
• Introduction to AWS Service Modules

Module 3: AWS Compute Services

• AWS EC2
• Launch Linux Instance in AWS
• Launch Windows Instance in AWS
• Installing Webserver in Linux and Windows
• AWS EBS
• Attaching New volume with instances
• Backup and Restore Of volumes
• Creating Own AWS Machine Image

Module 4: AWS Storage Services

• AWS Simple Storage Services
• S3 Accidental Deletion Protection
• Static Website Hosting using Storage Service
• AWS storage Classes
• Lifecycle Policies

Module 5: AWS Database Services

• Introduction to AWS databases
• Creating AWS RDS
• Backup and Restore RDS
• Security of RDS
• Accessibility to RDS
• AWS Dynamo DB

Module 6: AWS Networking Services

• AWS VPC
• VPC Components
• Subnet
• IP Addressing
• Route Table
• Internet Gateway
• Security Groups

Module 7: AWS Identity Management

• Create individual users.
• Manage permissions with groups.
• Grant least privilege.
• Configure a strong password policy.
• Enable MFA for privileged users.
• Use IAM roles for Amazon EC2 instances.
• Use IAM roles to share access.

Module 8: Elastic Load Balancing and Auto Scaling

• Achieve better fault tolerance for your applications
• Automatically load balance containerized applications
• Automatically scale applications
• Using Elastic Load Balancing in your Amazon Virtual Private Cloud (Amazon VPC)
• Invoking Lambda functions over HTTP(S)

Module 9: Introduction to Google Cloud, Digital Ocean & other cloud providers

• DIGITAL OCEAN
• GCP
• OTHER CLOUD PROVIDERS

Module 10: Project

• REAL-TIME PROJECT

Basic Knowledge of Python.

Module 1: Machine Learning (A talk with Machines)

• Introduction
• Understanding the theory and concepts of Machine Learning
• Machine Learning Methods
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
• Top 8 programming Languages for Machine Learning & Data Science

Module 2: Python (A tour to Python Programming)

• Installation of Anaconda
• Tokens in Python
• Keywords
• Identifiers
• Literals
• Operators
• Strings
• String Methods
• Strings Indexing and Slicing Loop
• List, Tuple, Dictionary, Set Map, Function, Lambda
• Class Programs and Assignments

Module 3: Matrix Manipulation using Numpy

• NumPy Arrays
• Indexing and Selection
• Slicing
• Numpy Operations
• Class Programs and Assignments

Module 4: Data Analysis With Pandas

• Make (Read & Write) CSV Dataset files
• Series & Data Frames
• Missing Data Group by Merging, Joining Concatenating
• Class Programs and Assignments

Module 5: Data-Visualization with-Matplotlib&Seaborn

• What is data visualization?
• Importance of data visualization
• Plotting, Plot, Sub-plot & Special Plot Distribution
• Plots using Seaborn Categorical
• Plots using Seaborn Matrix
• Plots using Seaborn
• Style and Colour using Seaborn
• Class Programs and Assignments

Module 6: Data Processing Using Titanic Dataset

• Reading Data
• Handling Missing Data
• Categorical Data
• Imputation
• Sampling
• Transform data
• Standard Scaler
• Decomposition
• Aggregation
• Splitting Data in Training & Testing Set

Module 7: Basic Statistics and Probability

• Mean, median, mode, variance
• Bayes theorem
• Joint probability distribution
• Basics of Vectors
• Class Programs and Assignments
• Introduction to features selections
• Univariate features selections
• Recursive features selections
• Class program of sklearn Features
• Selection

Module 8: Different types of Learning

• Difference between supervised learning, unsupervised learning, and reinforcement learning
• Famous Algorithms for Data Science and Machine Learning
• Understanding of these Algorithms

Module 9: Algorithm

• Statistics of linear regression
• Linear regression
• Logistic-regression
• k nearest neighbors
• k mean algorithm for clustering
• Statistics of k mean

Module 10: Decision Trees and Ensemble Learning

• Concept of decision trees and random forests
• Decision trees and random forest Bagging, boosting, voting classifier Implementation of bagging, boosting, voting classifier using scikit learn
• Understanding of count vectorizer and Naive Bayes
• Support Vector Machine(SVM)
• SVM using scikit learn
• bias variance trade off errors due to variance
• Understanding the theory of Perceptron and Gradient Descent algorithm along with practical demonstration

Module 11: Deep Learning&Recommendation Engine

• Neural Network
• Convolutional Neural Network
• Back Propagation
• Building recommendation engine using python
• Perceptron and Gradient Descent algorithm

Module 12: Image Processing with OpenCV

• Template Matching
• Corner Detection
• Edge Detection
• Feature Matching
• Project: Face Detection in Image
• Project: Face Detection in Real time

Module 13: NLP &ReinforcementLearning

• Introduction to token and corpus(Practical with demo project)
• Introduction to Reinforcement Learning
• Understanding the concepts of Reinforcement Learning
• Implementation of Reinforcement Learning

Module 14: Artificial Intelligence

• PROJECTS

• Basic Photoshop (Optional)

Module 1: Use of Photoshop Tools

• Use of tools
• Layers
• Filter and Concept about web page size
• Design
• Layout

Module 2: Introduction to HTML & HTML 5

• Html tags
• Table/div
• Forms
• Input
• Events
• Iframe
• Attributes
• Fundamental concepts of html,
• Introduction to adobe dreamweaver / komodo
• Audio/video element implementation
• Create dropdown web menu
• Pixel perfect design

Module 3: Introduction to CSS / CSS2/ CSS3

• Fundamental concepts of CSS
• CSS Properties
• CSS Value
• CSS Syntax
• CSS Comments
• Keyframe Animation
• CSS Parallax

Module 4: XHTML rules, W3C validation & browser compatibility

• Fundamental concepts of XHTML
• XHTML rules
• Validation through W3C live site
• Cross browser compatibility

Module 5:  Basics of JavaScript

• Implementing JavaScript
• Events and Objects
• Form Validation using JavaScript

Module 6:  Implementing JQuery

• JQurey into website
• Basic JQuery
• JQurey Slider
• JQurey CSS
• JQurey Accordian
• JQurey Tabs
• JQurey Parallax

Module 7: Webpage Implementation

• Responsive Technology
• Bootstrap Framework
• PSD to Responsive HTML Creation
• CMS page creation and modification

Module 8: Project

• Not required

C Programming

Module 1: Basic Structure of C Programming

• Keywords in C
• Identifiers in C
• Format Specifiers
• Format Specifiers Examples
• Data Types in C Language

Module 2: Introduction to Data Types in C

• Int Data Type in C
• Float Data Type in C
• Double Data Type in C
• Char Data Type in C

Module 3: Variable in C Language

• Variable Introduction in C
• Variable Declaration and Initialization
• Variable types and Scope in C
• Local Variable in C
• Static Variable in C
• Global variables in C
• Storage Class in C
• Constant in C Language
• Constants in C

Module 4: Operators and Enums in C Language

• Introduction to Operator
• Operator Precedance

Module 5: Decision Making of C Language

• If Statement
• If-else Statement
• Nested if Statement
• If else if Ladder
• Switch case

Module 6: Loop control in C Language

• Loop Introduction in C
• While loop in C
• Do while Loop In C
• For Loop in C
• Control Flow in C Programming
• Break Statement in C
• Continue Statement in C
• GotoStatement in C

Module 7: Array in C Language

• Single Dimensional Array
• Multi-Dimensional Array in C

Module 8: Function in C Language

• Function in C
• Function Calling in C
• Return type in Function
• Call by Value in C
• User Define Function
• Predefined Functions

Module 9: String functions in C

• strcat() function
• strncat() function
• strcpy() function
• strncpy() function
• strlen() function
• strcmp() function
• strcmpi() function

Module 10: Recursion in c

• Introduction to Recursion
• Direct and Indirect Recursion

Module 11: Pointer in C Language

• Pointer in C
• Pointer Expressions and Arithmetic
• Pointer and Array
• Strings as pointers
• Pointer to Function
• Call by Reference in C

Module 12: Structure in C Language

• Structure in C
• Nested Structure in C
• Array of Structures in C
• Pointer to Structure
• Structure to Function in C
• Typedefin C

Module 13: Introduction to File

• File Operation in c
• Dynamic Memory Allocation
• Introduction to DMA
• Calloc() and free() function
• Realloc() and free() function

Module 14: C Pre-processor

• Introduction about Pre-processor
• Command Line Arguments

C++ Programming 

Module 1: Classes in C++

• Defining Classes in C++
• Classes and Encapsulation
• Member Functions
• Instantiating and Using Classes
• Using Constructors
• Multiple Constructors and Initialization Lists
• Using Destructors to Destroy Instances
• Friendship

Module 2: Operator Overloading

• Operator Overloading
• Working with Overloaded Operator Methods

Module 3: Initialization and Assignment

• Initialization vs. Assignment
• The Copy Constructor
• Assigning Values
• Specialized Constructors and Methods
• Constant and Static Class Members

Module 4: Storage Management

• Memory Allocation
• Dynamic Allocation: new and delete

Module 5: Inheritance

• Overview of Inheritance
• Defining Base and Derived Classes
• Constructor and Destructor Calls

Module 6: Polymorphism

• Overview of Polymorphism

Module 7: Input and Output in C++ Programs

• Standard Streams
• Manipulators
• Unformatted Input and Output
• File Input and Output

Module 8: Exceptions

• Exceptions
• Inheritance and Exceptions
• Exception Hierarchies
• Inside an Exception Handler

Module 9: Templates

• Template Overview
• Customizing a Templated Method
• Standard Template Library Containers

Module 10:  Virtual and Pure Virtual Function

Module 11: Project

• C Language (Optional)
• C++ / Java (Optional)

Module 1: Installing Python and Setting up the Development Environment

• Downloading Python and Installing
• Downloading Eclipse and PyDev
• Introduction to different IDE and Editors for Python
• Installing Anaconda Navigator
• Hands on to Jupyter Notebook

Module 2: Basic programs handling Data type

• Running python
• Python identifier, keywords, comments etc
• Assigning values to variable
• Different data types in python
• Python numbers, strings

Module 3: Operators and Decision making in python

• Operators in python
• Decision making in python
• If elif statements
• Loops
• While loop and for loop
• Break and continue
• In, is keywords

Module 4: Functions in python-

• Defining a function with ‘def’ keyword
• Calling a function in python
• Pass by value and pass by reference
• Pass by object reference
• Local vs global variable
• Modules and packages in python
• Default argument, keyword argument and arbitrary argument
• Programs on function

Module 5: Dictionaries

• Introduction
• Accessing values in dictionaries
• Working with dictionaries
• Properties
• Functions

Module 6: Data structures in python

• Creating a list in python
• Different types of list operations
• Difference between list and tuple
• Understanding the concepts of sets
• Programs involving above data structures

Module 7: String in Python

• String Formatting Operator
• Built-in String Methods

Module 8: Object and Classes in python

• Introduction to the concepts of OOP
• Declaration of a class
• Basic properties, constructor
• Self, super keywords
• Creating object of a class
• Importing a custom class
• Programs involving classes
• Iterators
• Generators

Module 9: Regular expressions

• Match function
• Search function
• Matching VS Searching
• Modifiers
• Patterns

Module 10: Exceptions

• What is Exception?
• Handling an Exception
• The except Clause with No
• Exceptions
• The except Clause with Multiple
• Exceptions
• The try-finally Clause
• Argument of an Exception
• Raising an Exception
• User-Defined Exceptions

Module 11: File-Handling in python-

• Handling different types of file
• Opening a text file and a binary file
• Different modes of opening a file
• Reading and writing to a file
• Operations using file-handling

Module 12: Multithreading

• Thread
• Starting a thread
• Threading module
• Synchronizing threads
• Multithreaded Priority

Module 13: Building a Desktop based Application using Databases

• Introduction to sqlite3 or MySQL
• Database Connection
• Creating Database Table
• INSERT Operation
• SELECT Operation
• UPDATE Operation
• DELETE Operation
• Disconnecting Database
• Handling Errors

Module 14: Python Library

• NumPy: deal with the scientific task
• SciPy: deal with linear algebra, optimization, integration, and statistics
• Pandas: deal with Data Frame
• Matplotlib: deal with Graph Visualization

Module 15: Web Scraping

• Web Scraping using Beautiful Soup
• Data Manipulation using Get Requests

Module 16: Introduction to GUI Programming in python-

• Understanding the tkinter module.
• Structure of a tkinter program.
• Tkinter window, frame.
• Tkinter layout geometry.
• Pack, Grid, Place layout managers.
• Different types of widget classes in tkinter.
• Labels, Buttons, Entries in tkinter.
• Implementation of Listbox widget.

Module 17: Web PROGRAMMING

• Web Server Support and Configuration.
• Web page design using HTML and CSS.
• GET and POST Methods.
• Passing Information using GET method.

Module 18: Project (Specimen Topics)

Module 1: Installing Python and Setting up the Development Environment

• Downloading Python and Installing
• Downloading Eclipse and PyDev
• Introduction to different IDE and Editors for Python
• Installing Anaconda Navigator
• Hands on to Jupyter Notebook

Module 2: Basic programs handling Data type

• Running python
• Python identifier, keywords, comments etc
• Assigning values to variable
• Different data types in python
• Python numbers, strings

Module 3: Operators and Decision making in python

• Operators in python
• Decision making in python
• If elif statements
• Loops
• While loop and for loop
• Break and continue
• In, is keywords

Module 4: Functions in python-

• Defining a function with ‘def’ keyword
• Calling a function in python
• Pass by value and pass by reference
• Pass by object reference
• Local vs global variable
• Modules and packages in python
• Default argument, keyword argument and arbitrary argument
• Programs on function

Module 5: Dictionaries

• Introduction
• Accessing values in dictionaries
• Working with dictionaries
• Properties
• Functions

Module 6: Data structures in python

• Creating a list in python
• Different types of list operations
• Difference between list and tuple
• Understanding the concepts of sets
• Programs involving above data structures

Module 7: String in Python

• String Formatting Operator
• Built-in String Methods

Module 8: Object and Classes in python

• Introduction to the concepts of OOP
• Declaration of a class
• Basic properties, constructor
• Self, super keywords
• Creating object of a class
• Importing a custom class
• Programs involving classes
• Iterators
• Generators

Module 9: Regular expressions

• Match function
• Search function
• Matching VS Searching
• Modifiers
• Patterns

Module 10: Exceptions

• What is Exception?
• Handling an Exception
• The except Clause with No
• Exceptions
• The except Clause with Multiple
• Exceptions
• The try-finally Clause
• Argument of an Exception
• Raising an Exception
• User-Defined Exceptions

Module 11: File-Handling in python-

• Handling different types of file
• Opening a text file and a binary file
• Different modes of opening a file
• Reading and writing to a file
• Operations using file-handling

Module 12: Multithreading

• Thread
• Starting a thread
• Threading module
• Synchronizing threads
• Multithreaded Priority

Module 13: Building a Desktop based Application using Databases

• Introduction to sqlite3 or MySQL
• Database Connection
• Creating Database Table
• INSERT Operation
• SELECT Operation
• UPDATE Operation
• DELETE Operation
• Disconnecting Database
• Handling Errors

Module 14: Python Library

• NumPy: deal with the scientific task
• SciPy: deal with linear algebra, optimization, integration, and statistics
• Pandas: deal with Data Frame
• Matplotlib: deal with Graph Visualization

Module 15: Web Scraping

• Web Scraping using Beautiful Soup
• Data Manipulation using Get Requests

Module 16: Introduction to GUI Programming in python-

• Understanding the tkinter module.
• Structure of a tkinter program.
• Tkinter window, frame.
• Tkinter layout geometry.
• Pack, Grid, Place layout managers.
• Different types of widget classes in tkinter.
• Labels, Buttons, Entries in tkinter.
• Implementation of Listbox widget.

Module 17: Web PROGRAMMING

• Web Server Support and Configuration.
• Web page design using HTML and CSS.
• GET and POST Methods.
• Passing Information using GET method.

Module 18: Project (Specimen Topics)