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Coding Bytes is the Best Online Python Training, Course, Certification Institute in Delhi, Our Online Python Course leads the chart among the best Python Training Courses of Delhi NCR.
  • Duration : 4 months
  • Fees : ₹ 21999 | ₹ 17999/-
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Python (Online)

Course Highlights

  • Introduction to Python
  • Python Data Types
  • Python Functions, Modules And Packages
  • Python String, List And Dictionary Manipulations
  • Sequences and File Operations
  • Functions, OOPs, Modules, Errors and Exceptions
  • Python Regular Expression
  • Python Exception Handling
  • Python Database Interaction
  • Python Multithreading
  • Contacting User Through Emails Using Python
  • Python Requests
  • Web Scrapping
  • Python Tkinter GUI
  • NumPy Python
  • Python Pandas
  • Matplotlib

Python Course Details

1) Introduction to Python

  • Installation and Working with Python
  • Understanding Python variables
  • Python basic Operators
  • Understanding python blocks

2) Python Data Types

  • Declaring and using Numeric data types
  • Using string data type and string operations
  • Defining list and list slicing
  • Use of Tuple data type

3) Python Program Flow Control

  • Conditional blocks using if, else and elseif
  • Simple for loops in python
  • For loop using ranges, string, list and dictionaries
  • Use of while loops in python Loop

4) Python Functions, Modules And Packages 

  • Organizing python codes using functions
  • Organizing python projects into modules
  • Importing own module as well as external modules
  • Understanding Packages
  • Powerful Lamda function in python Programming using functions, modules and external packages
5) Python String, List And Dictionary Manipulations
  • Building blocks of python programs
  • Understanding string in build methods
  • List manipulation using in build methods
  • Dictionary manipulation
  • Programming using string, list and dictionary in build functions
6) Python File Operation
  • Reading config files in Python
  • Writing log files in Python
  • Understanding read functions, read(), readline() and readlines()
  • Understanding write functions, write() and writelines()
  • Manipulating file pointer using seek Programming using file operations
7) Python Object Oriented Programming – OOPS
  • Concept of class, object and instances
  • Constructor, class attributes and destructors
  • Real time use of class in live projects
  • Inheritance , overlapping and overloading operators
  • Adding and retrieving dynamic attributes of classes
  • Programming using Oops support
8) Python Regular Expression
  • Powerful pattern matching and searching
  • Power of pattern searching using regex in Python
  • Real time parsing of networking or system data using regex
  • Password, email, url validation using regular expression
  • Pattern finding programs using regular expression
9) Python Exception Handling
  • Avoiding code break using exception handling
  • Safe guarding file operation using exception handling
  • Handling and helping developer with error code
  • Programming using Exception handling
10) Python Database Interaction
  • SQL Database connection using Python
  • Creating and searching tables
  • Reading and storing config information on database
  • Programming using database connections
11) Python Multithreading
  • Understanding threads
  • Forking threads
  • Synchronizing the threads
  • Programming using multithreading
12) Contacting User Through Emails Using Python
  • Installing SMTP Python module
  • Sending email
  • Reading from file and sending emails to all users addressing them directly for marketing
13) Python Requests


Module 1: Introduction to HTTP and REST

Understanding HTTP: Learn the basics of the HTTP protocol and its role in web communication.
Introduction to REST: Explore REST architecture and its principles for building web services.

Module 2: Getting Started with Python Requests

Installing Requests Library: Learn how to install and set up the requests library in Python.
Making Simple Requests: Perform basic HTTP GET requests using the requests library.

Module 3: Working with HTTP Methods

GET Method: Understand how to use the GET method to retrieve data from a REST API.
POST Method: Learn how to send data to a server using the POST method.
PUT Method: Explore the PUT method for updating existing resources on a server.
DELETE Method: Discover how to use the DELETE method to remove resources from a server.

Module 4: Handling Advanced Requests

Query Parameters: Learn to pass query parameters in requests for filtering and sorting data.
Request Headers: Understand how to include headers in requests for authentication and content negotiation.
Cookies: Explore how to manage cookies in HTTP requests using the requests library.

Module 5: Error Handling and Retry Mechanisms

Timeouts: Learn how to handle timeout errors gracefully in HTTP requests.
Retry Mechanism: Implement retry logic to handle transient errors during requests.

Module 6: Practical Application

Building a Weather App: Create a simple weather application using the Open Weather Map API with Python and requests.

14) Web Scrapping

Module 1: Introduction to Web Scraping

Understanding Web Scraping: Explore the basics of web scraping, spiders, and crawling.
How Web Scraping Works: Learn the underlying principles of web scraping and data extraction.

Module 2: Getting Started with Scrapy

Installation: Install Scrapy using PyCharm or Terminal/Sublime Text.
Project Structure: Understand the structure of a Scrapy project.

Module 3: Web Scraping Best Practices

Robots.txt and Web Scraping Rules: Learn about web scraping etiquette and respecting robots.txt rules.

Module 4: Creating and Running Spiders

Creating Your First Spider: Build your first web crawler using Scrapy.
Running Your Spider: Execute and run your Scrapy spider to scrape websites.

Module 5: Data Extraction Techniques

Using CSS Selectors: Extract data from web pages using CSS selectors.
Using XPath: Learn to extract data using XPath expressions.

Module 6: Data Storage

Item Containers: Store scraped data using Scrapy’s item containers.
Storing Data in JSON, XML, and CSV: Save scraped data in different file formats.

Module 7: Advanced Data Pipelines

Understanding Pipelines: Implement pipelines to process and store scraped data.
Storing Data in SQLite3: Learn the basics of SQLite3 and store data in a local database.

Module 8: Database Integration

Storing Data in MySQL: Integrate Scrapy with MySQL to store scraped data in a relational database.
Storing Data in MongoDB: Explore storing scraped data in a NoSQL MongoDB database.

Module 9: Advanced Scraping Techniques

Web Crawling and Following Links: Build spiders that navigate through multiple pages and follow links.
Scraping Websites with Pagination: Implement pagination handling in Scrapy spiders.

Module 10: Handling Restrictions and Challenges

Logging in with FormRequest: Scrape websites that require authentication using Scrapy’s FormRequest.
Bypassing Restrictions with User-Agent and Proxies: Learn techniques to bypass anti-scraping measures.

15) Python Tkinter GUI

Module 1: Introduction to Tkinter

Why Tkinter?: Understand the importance and versatility of Tkinter for building graphical user interfaces (GUIs) in Python.
Our First Tkinter GUI: Create a simple Tkinter window and learn the basics of GUI development.

Module 2: Tkinter Widgets and Layout

Tkinter Widgets & Attributes: Explore different widgets (like labels, buttons, entry fields) and their attributes.
Frame in Tkinter: Learn how to use frames to organize and structure your GUI components.

Module 3: Building Interactive GUIs

Accepting User Input: Use entry widgets and checkbuttons to accept user input in forms.
Handling Events: Learn how to handle user events like button clicks and key presses.

Module 4: Advanced GUI Components

Canvas Widget: Understand how to use the canvas widget for drawing graphics and shapes.
Menus and Submenus: Create dropdown menus and submenus to enhance GUI navigation.

Module 5: Enhancing User Experience

Message Box: Implement message boxes for displaying alerts and notifications.
Sliders and Scrollbars: Integrate sliders and scrollbars to control values and navigate content.

Module 6: Data Presentation Widgets

Listbox: Create listboxes to display selectable lists of items.
Radio Buttons: Learn how to use radio buttons for selecting options in GUI forms.

Module 7: Advanced GUI Techniques

Status Bar: Implement a status bar to provide feedback and display application status.
Using Classes for GUIs: Organize GUI components using classes and objects for better code structure.

Module 8: Practical Projects

Building a Calculator: Develop a functional calculator application using Tkinter.

16) NumPy Python
  • NumPy – Home
  • NumPy – Introduction
  • NumPy – Environment
  • NumPy – Ndarray Object
  • NumPy – Data Types
  • NumPy – Array Attributes
  • NumPy – Array Creation Routines
  • NumPy – Array from Existing Data
  • Array From Numerical Ranges
  • NumPy – Indexing & Slicing
  • NumPy – Advanced Indexing
  • NumPy – Iterating Over Array
  • NumPy – Array Manipulation
  • NumPy – Binary Operators
  • NumPy – String Functions
  • NumPy – Mathematical Functions
  • NumPy – Arithmetic Operations
  • NumPy – Statistical Functions
  • Sort, Search & Counting Functions
17) Python Pandas
  • Python Pandas – Introduction
  • Python Pandas – Environment Setup
  • Introduction to Data Structures
  • Python Pandas – Series
  • Python Pandas – DataFrame
  • Python Pandas – Panel
  • Python Pandas – Basic Functionality
  • Descriptive Statistics
  • Function Application
  • Python Pandas – Reindexing
  • Python Pandas – Iteration
  • Python Pandas – Sorting
  • Working with Text Data
  • Options & Customization
  • Indexing & Selecting Data
18) Matplotlib

Module 1: Introduction to Matplotlib

Overview of Data Visualization: Understand the importance of data visualization and its role in data analysis.
Introduction to Matplotlib: Explore what Matplotlib is, why it’s used, and its key features.

Module 2: Getting Started with Matplotlib

Installation and Setup: Learn how to install Matplotlib and set up your environment (including Jupyter Notebook on Windows 10).
Basic Plotting: Dive into basic plotting functions like line plots and scatter plots.

Module 3: Essential Plot Types

Line Plots: Create simple and customized line plots to visualize trends and relationships.
Bar Plots: Understand how to plot categorical data using bar charts.
Scatter Plots: Learn to use scatter plots for visualizing relationships between variables.

Module 4: Advanced Plotting Techniques

Histograms: Visualize data distribution with histograms.
Pie Charts: Represent data proportions using pie charts.
Stem Plots: Explore how to use stem plots for discrete data.

Module 5: Specialized Plot Types

Box Plots: Understand how to create box plots for summarizing data distributions.
Area and Stack Plots: Learn to plot stacked area charts for displaying cumulative data.
Step Plots: Create step plots to represent data changes at distinct intervals.

Module 6: Customizing Plots

Subplots: Master the art of creating multiple plots in one figure using subplots.
Saving Plots: Learn to save your Matplotlib plots in various formats (e.g., PNG, PDF).
Axis Customization: Customize axes labels, ticks, and limits to enhance plot clarity.
Adding Text: Enhance plots by adding text annotations and labels.

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