Online Training PHP with Mysql with Live Project
Online Training with Certificate Live Project Development Training
Days Portions to cover
PHP
Day 1 PHP Introduction
Day 2 Variables, Constants, Datatypes
Day 3 Operators and Control Structures
Day 4 Looping Statements
Day 5 Arrays and Foreach Loop
Day 6 PHP Functions
Day 7 HTML Forms with PHP
Day 8 File Handling
MYSQL
Day 9 Introduction to MySQL
Day 10 Datatypes, Constraints
Day 11 Select, Orderby, Limit
Day 12 Functions - Number, Date, Character, Control Flow
Day 13 Joins, Groupby, Having, Subquery, Indexing
PHP
Day 14 PHP With MySQL
Day 15 Cookies in PHP
Day 16 Sessions in PHP
Day 17 Blog Project Demo, PhpMyAdmin
Day 18-20 Project
Day 21 Oops with PHP - Basics
Day 22 Oops with PHP - Advanced
Day 23 Javascript- Introduction, Functions, Events, Validation
Day 24 CSS
Day 25 CSS Practice
Day 26-27 Ajax
Day 28-29 Jquery
Day 30-31 Smarty
Day 32-33 CakePHP/Codeigniter
Day 34 Interview Questions
Day 35-38 Project
Day 39 CSS Template Integration
Day 40 Project Hosting in Internet
Day 40-45 Paypal Payment Gateway Integration
Day 45-50 Facebook API Integration
Day 51-54 Responsive Web Design using Bootstrap framework
Day 55-60 Project Advanced Features, SMS Gateway Integration
Days Portions to cover
PHP
Day 1 PHP Introduction
Day 2 Variables, Constants, Datatypes
Day 3 Operators and Control Structures
Day 4 Looping Statements
Day 5 Arrays and Foreach Loop
Day 6 PHP Functions
Day 7 HTML Forms with PHP
Day 8 File Handling
MYSQL
Day 9 Introduction to MySQL
Day 10 Datatypes, Constraints
Day 11 Select, Orderby, Limit
Day 12 Functions - Number, Date, Character, Control Flow
Day 13 Joins, Groupby, Having, Subquery, Indexing
PHP
Day 14 PHP With MySQL
Day 15 Cookies in PHP
Day 16 Sessions in PHP
Day 17 Blog Project Demo, PhpMyAdmin
Day 18-20 Project
Day 21 Oops with PHP - Basics
Day 22 Oops with PHP - Advanced
Day 23 Javascript- Introduction, Functions, Events, Validation
Day 24 CSS
Day 25 CSS Practice
Day 26-27 Ajax
Day 28-29 Jquery
Day 30-31 Smarty
Day 32-33 CakePHP/Codeigniter
Day 34 Interview Questions
Day 35-38 Project
Day 39 CSS Template Integration
Day 40 Project Hosting in Internet
Day 40-45 Paypal Payment Gateway Integration
Day 45-50 Facebook API Integration
Day 51-54 Responsive Web Design using Bootstrap framework
Day 55-60 Project Advanced Features, SMS Gateway Integration
Trainer
K.BoopathiKumar
919698548633
Training cost: 6000 Rs
www.trainingtrains.in
K.BoopathiKumar
919698548633
Training cost: 6000 Rs
www.trainingtrains.in
Online Software Testing Training with Live Projects
Online Software Testing Course Syllabus and Training Plan
Week 1
Brief introduction to software systems and SDLC
Week 1
Brief introduction to software systems and SDLC
Basic concepts
Basic Testing Vocabulary
Quality Assurance versus Quality Control
The Cost of Quality
Software Quality Factors
How Quality is Defined
Why Do We Test Software?
What is a Defect?
The Multiple Roles of the Software Tester(People Relationships)
Scope of Testing
When Should Testing Occur?
Testing Constraints
Life Cycle Testing
Independent Testing
What is a QA Process?
Levels of Testing
The “V” Concept of Testing
Week 2:
Testing Techniques
Quality Assurance versus Quality Control
The Cost of Quality
Software Quality Factors
How Quality is Defined
Why Do We Test Software?
What is a Defect?
The Multiple Roles of the Software Tester(People Relationships)
Scope of Testing
When Should Testing Occur?
Testing Constraints
Life Cycle Testing
Independent Testing
What is a QA Process?
Levels of Testing
The “V” Concept of Testing
Week 2:
Testing Techniques
Structural versus Functional Technique Categories
Verification versus Validation
Static versus Dynamic Testing
Examples of Specific Testing Techniques
Test Administration
Verification versus Validation
Static versus Dynamic Testing
Examples of Specific Testing Techniques
Test Administration
Test Planning
Customization of the Test Process
Budgeting
Scheduling
Create the Test Plan
Customization of the Test Process
Budgeting
Scheduling
Create the Test Plan
Prerequisites to test planning
Understand the Characteristics of the Software Being Developed
Build the Test Plan
Write the Test Plan
Week 3:
Test Cases:
Test case Design
Building test cases
Test data mining
Test execution
Test Reporting
Defect Management
Test Coverage – Traceability matrix
Test Metrics – Guidelines and usage
Test reporting:
Guidelines for writing test reports
Week 4:
Test Tools used to Build Test Reports
Week 4:
Test Tools used to Build Test Reports
Managing Change
Software Configuration Management
Change Management
Risks – Risk Analysis and Management with examples
User Acceptance testing – in detail explanation with details
Case Study: How to test web, stand alone and database applications – with examples.
Help with resume and testing interview skills.
Change Management
Risks – Risk Analysis and Management with examples
User Acceptance testing – in detail explanation with details
Case Study: How to test web, stand alone and database applications – with examples.
Help with resume and testing interview skills.
Software Testing Training Course Week 5:
Automation Testing Basics
Automation Testing Basics
Basics of automation testing – why, when and how to perform automation testing
Factors for choosing a particular tool
An overview for the major functional testing tools
Overview of Test management and bug tracking tools
Factors for choosing a particular tool
An overview for the major functional testing tools
Overview of Test management and bug tracking tools
Contact
K.Boopathikumar
919698548633
K.Boopathikumar
919698548633
www.trainingtrains.in
Online PHP Training #training trains
PHP Training
Introduction of Web & PHP
What is PHP?
The history of PHP
Why choose PHP?
Installation overview
First Steps
Embedding PHP code on a page
Outputting dynamic text
The operational trail
Inserting code comments
Exploring Data Types
Variables
Strings
String functions
Numbers part one: Integers
Numbers part two: Floating points
Arrays
Associative arrays
Array functions
Booleans
NULL and empty
Type juggling and casting
Constants
Control Structures: Logical Expressions
If statements
Else and elseif statements
Logical operators
Switch statements
Control Structures: Loops
While loops
For loops
Foreach loops
Continue
Break
Understanding array pointers
User-Defined Functions
Defining functions
Function arguments
Returning values from a function
Multiple return values
Scope and global variables
Setting default argument values
Debugging
Common problems
Warnings and errors
Debugging and troubleshooting
Building Web Pages with PHP
Links and URLs
Using GET values
Encoding GET values
Encoding for HTML
Including and requiring files
Modifying headers
Page redirection
Output buffering
Working with Forms and Form Data
Building forms
Detecting form submissions
Single-page form processing
Validating form values
Problems with validation logic
Displaying validation errors
Custom validation functions
Single-page form with validations
Working with Cookies and Sessions
Working with cookies
Setting cookie values
Reading cookie values
Unsetting cookie values
Working with sessions
MySQL Basics
MySQL introduction
Creating a database
Creating a database table
CRUD in MySQL
Populating a MySQL database
Relational database tables
Populating the relational table
Using PHP to Access MySQL
Database APIs in PHP
Connecting to MySQL with PHP
Retrieving data from MySQL
Working with retrieved data
Creating records with PHP
Updating and deleting records with PHP
SQL injection
Escaping strings for MySQL
Introducing prepared statements
Building a Content Management System (CMS)
Blueprinting the application
Building the CMS database
Establishing your work area
Creating and styling the first page
Making page assets reusable
Connecting the application to the database
Using Site Navigation to Choose Content
Adding pages to the navigation subjects
Refactoring the navigation
Selecting pages from the navigation
Highlighting the current page
Moving the navigation to a function
Application CRUD
Finding a subject in the database
Refactoring the page selection
Creating a new subject form
Processing form values and adding subjects
Passing data in the session
Validating form values
Creating an edit subject form
Using single-page submission
Deleting a subject
Cleaning up
Assignment: Pages CRUD
Assignment results: Pages CRUD
Building the Public Area
The public appearance
Using a context for conditional code
Adding a default subject behaviour
The public content area
Protecting page visibility
Regulating Page Access
User authentication overview
Admin CRUD
Encrypting passwords
Salting passwords
Adding password encryption to CMS
New PHP password functions
Creating a login system
Checking for authorization
Creating a logout page
Advanced PHP Techniques
Using variable variables
Applying more array functions
Building dates and times: Epoch/Unix
Formatting dates and times: Strings and SQL
Setting server and request variables
Establishing global and static variable scope
Making a reference assignment
Using references as function arguments
Using references as function return values
Introduction to Object-Oriented Programming (OOP)
Introducing the concept and basics of OOP
Defining classes
Defining class methods
Instantiating a class
Referencing an instance
Defining class properties
OOP in Practice
Understanding class inheritance
Setting access modifiers
Using setters and getters
Working with the static modifier
Reviewing the scope resolution operator
Referencing the Parent class
Using constructors and destructors
Cloning objects
Comparing objects
Working with Files and Directories
File system basics
Understanding file permissions
Setting file permissions
PHP permissions
Accessing files
Writing to files
Deleting files
Moving the file pointer
Reading files
Examining file details
Working with directories
Viewing directory content
Sending Emails
Configuring PHP for email
Sending email with mail()
Using headers
Reviewing SMTP
Using PHPMailer
Data Science training course in Erode with Python
Learn to use Python as your Data Science tool of choice This course teaches you Python as a tool for data science, and specifically for implementing an advanced Machine Learning algorithm with Python
I. Introduction and Setting Up Your Integrated Analysis Environment
Setting Up Your Integrated Analysis Environment & Tools Overview
IPython Shell
Custom environment settings
Jupyter Notebooks
Script editor
Packages: NumPy, SciPy, scikit-learn, Pandas, Matplotlib, Seaborn, etc.
Once you complete this module, you will understand some of the unique benefits of using Python for data science / what features make Python particularly well-suited for data science, you will be able to set up a fully functioning Python-based analysis environment, and you will know what each tool is used for in the data science workflow.
II. Using Python to Control and Document Your Data Science Processes
Python Essentials
Data types and objects
Loading packages, namespaces
Reading and writing data
Simple plotting
Control flow
Debugging
Code profiling
Once you complete this module, you will be able to use the Python standard library plus Canopy tools to write, run, debug, and profile programs that control your data science processes (which draw on the scientific packages).
III. Accessing and Preparing Data
Data, Data, Everywhere...
Acquiring Data with Python
Loading from CSV files
Accessing SQL databases
Cleansing Data with Python
Stripping out extraneous information
Normalizing data
Formatting data
Once you complete this module, you will know how to load data from common types of data sources, including structured text files and SQL databases. and you will know some of the common tools used in Python to cleanse and prepare your data for analysis.
IV. Numerical Analysis, Data Exploration, and Data Visualization with NumPy Arrays,
Matplotlib, and Seaborn
Matplotlib, and Seaborn
NumPy Essentials
The NumPy array
N-dimensional array operations and manipulations
Memory mapped files
Data Visualization
2D plotting with Matplotlib
Advanced data visualization with Seaborn
Once you complete this module, you will understand how to use NumPy arrays for efficient numerical processing and how to use NumPy methods such as slicing to write code that is both compact and easy to read and understand. You will know how to use Matplotlib, Seaborn, and NumPy together to explore and visualize your data.
V. Exploring Data with Pandas
Searching for Gold in a Pile of Pyrite
Data manipulation with Pandas
Statistical analysis with Pandas
Time series analysis with Pandas
At the end of this module, you will know how to access some of the core tools used for statistical analysis and data exploration in Python.
VI. Machine Learning with scikit-learn
Predicting the Future Can Be Good for Business
Input: 2D, samples, and features
Estimator, predictor, transformer interfaces
Pre-processing data
Regression
Classification
Model selection
At the end of this module you will have a working understanding of what machine learning tools are available in scikit-learn and how to use them.
Trainer
K.BoopathiKumar
919698548633