Python Training in Chennai with Certification

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Job Oriented Training

 

3RI Technologies provides comprehensive Python training in Chennai to assist you to understand the fundamentals as well as more advanced topics such as scripting, algorithms, file operations, CRUD operations, and Django/ Flask python frameworks. Our training session will benefit both Freshers and professionals who want to gain hands-on experience with practical applications. Our instructor-led training is up to industry standards and involves both hands-on instruction and real-world projects and activities. Our industry-experienced trainers give coursework and mock interview sessions to help them ace interviews and secure a successful job with a multinational firm.

Key Features

Course Duration : 8 Weeks

Live Projects : 1

Online Live Training

EMI Option Available

Certification & Job Assistance

24 x 7 Lifetime Support

Our Industry Expert Trainer

We are a team of 10+ Years of Industry Experienced Trainers, who conduct the training with real-time scenarios.
The Global Certified Trainers are Excellent in knowledge and highly professionals.
The Trainers follow the Project-Based Learning Method in the Interactive sessions.

Python Course in Chennai Overview

Skills Required

Certifications
0 +
24x7 Support and Access
24x
40 to 50 Hour Course Duration
40- 0
Extra Activities, Sessions
0 %

Python Course Syllabus

Best-in-class content by leading faculty and industry leaders in the form of videos, cases and projects, assignments and live sessions

Module 1: Python Programming(Compulsory)
  1. An Introduction to Python
    • Why Python, its Unique Feature and where to use it?
    • Python Environment Setup
    • Discuss about IDE’s like IDLE, Pycharm and Enthought Canopy
    • Start programming on an interactive shell.
    • Python Identifiers, Keywords
    • Discussion about installed module s and packages
    • Access Command line arguments within programs
  2. Conditional Statement, Loops, and File Handling
    • Python Data Types and Variable
    • Condition and Loops in Python
    • Decorators
    • Python Modules & Packages
    • Python Files and Directories manipulations
    • Use various files and directory functions for OS operations
  3. Python Core Objects and Functions
    • Built in modules (Library Functions)
    • Numeric and Math’s Module
    • String/List/Dictionaries/Tuple
    • Complex Data structures in Python
    • Arbitrary data types and their Data Structure
    • Python built-in function
    • Python user-defined functions
    • Python packages and functions
    • The anonymous Functions – Lambda Functions
  4. Object Oriented Python
    • OOPs Concepts
    • Object, Classes and Destroying Objects
    • Accessing attributes, Built-In Class Attributes
    • Inheritance and Polymorphism
    • Overriding Methods,
    • Abstraction and Encapsulation
  5. Regular Expression
    • Regular Expressions
    • What are regular expressions?
    • The match and search Function
    • Compile and matching
    • Matching vs searching
    • Search and Replace feature using RE
    • Extended Regular Expressions
    • Wildcard characters and work with them
  6. Multithreading
    • Multithreading with Python
    • What is multithreading?
    • Starting a New Thread
    • The Threading Module
    • Synchronizing Threads
  7. File Handling
    • Writing data to a file
    • Reading data from a file
    • Read and Write data from CSV file
    • OS module
    • Rename and Removing files, directories
  8. Exception Handling in Python
    • Exceptions Handling
    • Handling various exceptions using try….except…else
    • Try-finally clause
    • The argument of an Exception and create a self exception class
    • Python Standard Exceptions
    • Raising an exceptions, User-Defined Exceptions
  9. Debugging Python Programs
    • Debug Python programs using pdb debugger
    • Assert for debugging
    • Standard project setup in Python
  10. Modules & Packages
    • Modules
    • How to import a module?
    • Packages
    • How to create packages
  11. Database Handling
    • Create Database Connection
    • Creating and accessing SQLite database
    • Python with MySQL Database
    • Creating Database table
    • CRUD operation on a database
    • Performing Transactions
    • Handling Database Errors
    • Disconnecting Database
Module 2: Advanced Python Programming(Compulsory to Complete Python)
  1. Basics of Web Page Creation
    • Understanding of basic HTML /CSS
    • HTML Header, paragraph
    • Various tag for button, label and combo-box
    • Creation of forms in HTML
  2. Django Framework
    • Introduction to Django
    • MVT Architecture
    • How to create Django App
    • Url Mapping
    • Templates
    • Introduction to static file
    • Django Model Overview
    • Creating model
    • Model template view creation
    • Django forms and validation
    • Relative Url with Template
  3. Interacting with a Database: Models
    • Overview of Models
    • Creating Models
    • Configuring the Database
    • Your First App
    • Using Django with MySQL.
    • Models-Templates-Views Paradigm
    • Inserting and Updating Data
  4. The Django Administration Site
    • Activating the Admin Interface
    • Using the Admin Interface
    • Users, Groups, and Permissions
    • Selecting an Objects
    • Deleting an Objects
  5. Views and Templates
    • URL Template Inheritance
    • Template Inheritance Coding Example
    • Quick Note on Custom Template Filters
    • Template Filters and Custom Filters
    • Template Filters Coding Examples
    • Django Passwords
    • Deploying Django Framework
  6. Form Processing
    • Django Forms
    • Form Validation
    • Model Forms
    • Relative URLs with Templates 
    • Relative URLs Coding Examples 
  7. Project Work
    • Discussion on Overview and requirements of Project
    • Creation a Web-based Application
Module 3: Python for Data Science (Different Course, it is delivered Separately) Mathematical Statistics
  1. Fundamentals of Data Science and Machine Learning
    • Introduction to Data Science
    • The need for Data Science
    • BigData and Data Science’
    • Data Science and machine learning 
    • Data Science Life Cycle
    • Data Science Platform
    • Data Science Use Cases 
    • Skill Required for Data Science
  2. Mathematics For Data Science
    • Linear Algebra
      • Vectors
      • Matrices
    • Optimization
      • Theory Of optimization
      • Gradients Descent
  1. Introduction to Statistics
    • Descriptive vs. Inferential Statistics
    • Types of data
    • Measures of central tendency and dispersion
    • Hypothesis & inferences
    • Hypothesis Testing
    • Confidence Interval
    • Central Limit Theorem
  2. Probability and Probability Distributions
    • Probability Theory
    • Conditional Probability
    • Data Distribution
    • Binomial Distribution
    • Normal Distribution


Machine Learning

Python for ML along with Module1

  1. Introduction to NumPy
    • Array Operations
    • Arrays Functions
    • Array Mathematics
    • Array Manipulation
    • Array I/O
    • Importing Files with Numpy
  2. Data Manipulation with Pandas
    • Data Frames
    • I/O
    • Selection in DFs
    • Retrieving in DFs
    • Applying Functions
    • Reshaping the DFs – Pivot
    • Combining DFs
      • Merge
      • Join
    • Data Alignment
  3. SciPy
    • Matrices Operations
    • Create matrices
      • Inverse, Transpose, Trace, Norms , Rank etc
    • Matrices Decomposition
      • Eigen Values & vectors
      • SVDs
  1. MatPlotLib
    • Basics of Plotting
    • Plots Generation
    • Customization
    • Store Plots
  2. SciKit LearnBasics
    • Data Loading
    • Train/Test Data generation
    • Preprocessing
    • Generate Model
    • Evaluate Models


Machine Learning

  1. Exploratory Data Analysis
    • Data Exploration
    • Missing Value handling
    • Outliers Handling
    • Feature Engineering
  2. Feature Selection
    • Importance of Feature Selection in Machine Learning
    • Filter Methods
    • Wrapper Methods
    • Embedded Methods
  3. Machine Learning: Supervised Algorithms Classification
    • Introduction to Machine Learning
    • Logistic Regression
    • Naïve Bays Algorithm
    • K-Nearest Neighbor Algorithm
    • Decision Tress (SingleTree)
    • Support Vector Machines
    • Model Ensemble
      • Bagging
      • Random Forest
      • Boosting
      • Gradient Boosted Trees
    • Model Evaluation and performance
      • K-Fold Cross Validation
      • ROC, AUC etc…
  1. Machine Learning: Regression
    • Simple Linear Regression
    • Multiple Linear Regression
    • Decision Tree and Random Forest Regression
  2. Machine Learning: Unsupervised Learning Algorithms
    • Similarity Measures
    • Cluster Analysis and Similarity Measures
    • K-chical Clustering
    • Principal means Clustering
    • HierarComponents Analysis
    • Association Rules Mining & Market Basket Analysis
  3. Text Mining
    • Basics
    • Term Document Matrix
    • TF-IDF
    • Twitter Sentiment Analysis
  1. Project Work
  • Machine Learning end to end Project blueprint
  • Regression predictive modeling – House Price Prediction
  • Classification predictive modeling – Binary Classification
  • Widespread coverage for each Topic
  • Various Approaches to Solve Data Science Problem
  • Pros and Cons of Various Algorithms and approaches
Module 4: Python for Automation Testing (Different Course, it is delivered Separately) Basic Selenium
  1. Introduction to Selenium
    • Introduction to Automation Testing
    • Why Automation Testing
    • Introduction to Selenium components
    • History and various versions of selenium
    • What is Selenium 3.0
    • Advantages of using Selenium over other tools.
  2. Installation and setting up the environment
    • Installation of Python
    • Automation Setup for Selenium Web Driver
    • Install and Configure PyDev in Eclipse
  3. Selenium-IDE
    • Introduction
    • IDE Features
    • Building & Running Test Cases
    • Building and Running Test Suites
  4. Selenium Web Driver 2.0
    • Why Selenium Web Driver
    • What is a Driver
    • Download & configuring Web driver
    • Architecture of selenium web driver
    • Drivers for Firefox, IE, chrome
  5. Identification of Locators
    • Tools to identify elements/objects
    • Different methods of finding an element
      • By ID, By name, class
      • By Xpath, By Tag name
      • By Link text
      • By CSS
      • Using Effective X-path
  1. Selenium Commands
    • Various types of operation that can be
    • performed on any elements and how to use them.
    • Browser Commands, Navigation Commands
    • Working with a different browser
    • Handling Checkbox, RadioButton
    • Dropdown and Select Operations
    • Capturing Screenshots
    • Handling Keyboard Event and Mouse Event
    • Multiple Window Handling
    • Alert & Pop Up Handling.
  2. Wait Commands in Selenium
    • Implicit Wait
    • Explicit Waits, Expected Conditions

Advanced Selenium

  1. Framework Designing
    • What is Framework
    • Different Types of Framework.
    • How to Design a framework?
    • Data-Driven Framework using Excel
      • Reading and writing data from Excel
      • Executing Testcases from Excel
  1. PyTest Framework
    • Introduction to PyTest framework
    • Installing PyTest
    • PyTest Fixtures
    • Parametrized Test Functions
    • Running multiple tests using PyTest
    • Generating Test report
  2. Unit Test Framework PyUnit
    • Basic of pyunit
    • pyunit Installation
    • pyunit annotation
    • Test Case creation 
    • Test Case execution
    • Assertions/Reporting Errors
    • Suite execution
    • pyunit Reports
    • Using pyunit in Selenium
  3. POM Framework
    • Advantages of POM
    • How to implement
    • Using Page Object and Page Factory
  4. Continuous Build Integration tools- Jenkins
    • What is Jenkins and how to use it
    • Installation and configuration of Jenkins
Module 5: Python for Web Development (Different Course, it is delivered Separately) This course has mandatory sections i.e. Module 1 & 2

Front End Technologies

  1. HTML
    • Introduction and Basic Structure of HTML
    • Basics, Elements, Attributes
    • Paragraphs and Formatting
    • HTML Skeleton, Links, Images
    • HTML Tables, Blocks
    • HTML Lists, Quick List
    • HTML Blocks
    • HTML Layouts & Forms, IFrames
    • HTML Colors
  2. CSS
    • Introduction
    • Syntax
    • Id & Class
    • Backgrounds
    • Text and Fonts
    • Links and Lists
    • Box Model
    • Advanced Topics
    • Dimensions, Display
    • Positioning, Floating
    • Align
  3. JavaScript
    • Introduction
    • Statements & Comments
    • Variables
    • Operators and Comparisons
    • Conditional Statements and Loops
    • User Defined Functions
    • JS Objects
    • JS Validations
  4. Bootstrap
  • What is Bootstrap and its Setup
  • How to Create a Layout in Bootstrap
    • Grid Classes
  • Basic Tags in Bootstrap
    • Contextual colors and backgrounds
  • Table in Bootstrap
    • Bootstrap Basic Tables
    • Striped Rows, Hover Rows
    • Bordered Table, Condensed Table
    • Responsive Tables
  • Navigation bar in Bootstrap
    • Inverted Navigation Bar
    • Fixed Navigation Bar
    • Navigation Bar with Dropdown
    • Right-aligned Navigation Bar
    • Collapsing the Navigation Bar
  • Form & Buttons in Bootstrap
    • Vertical Form
    • Horizontal Form
    • Inline Form
    • Block Level Buttons
    • Active/Disabled Button


Database Handling with Python

  1. Python MySQL Database Access
    • Create Database Connection
    • DML and DDL Operations with Databases
    • Performing Transactions
    • Handling Database Errors
    • Disconnecting Database
  2. Database Handling with NoSQL DB
    • SQL vs NoSQL
    • MongoDB
    • PyMongo
    • Establishing a Connection
    • Accessing Database
    • DML and DDL Operations

Project Work

  • User Login and Registration site
  • Create an online Test evaluation system for Institute
  • Building an E-commerce site in Django

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Skills to Master

Web scraping

Django

Operators

Methods

Functions

Data Structures

Pandas

NumPy

Libraries

Matplotlib

Loops

Errors and exceptions

Tools to Master

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