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Python Programming Course Syllabus: The Ultimate Guide

Python Programming Course

Table of Contents

Python Programming Course Syllabus: The Ultimate Guide

Python is a high-level programming language widely used in various industries such as web development, data science, and machine learning. If you’re interested in learning Python, there are several courses available to help you get started.

Python is a general-purpose, high-level, interpreted, interactive, object-oriented, open-source programming language ideal for software development. The Python Training Institute in Faridabad is the perfect place to acquire good programming skills. Its curriculum is extensive and covers areas such as the basics of the Python language, setting up the Python programming environment, and Python object-oriented programming. 

In this guide, we’ll look at a typical Python programming course syllabus, including topics covered, course objectives, and skills you might learn.

All about the 2023 Python Curriculum

  • Python covers a wide range of subjects. B. Introduction to Python and computer programming, data types, variables, basic operators, Boolean values, conditional execution, loops, lists, and more.
  • Python programming is an important part of learning Python. Topics covered include Python language overview, Python language syntax, Python keywords and identifiers, Python variables, data types, operators, and more.
  • Django is a high-level Python web framework used for the rapid development of secure and maintainable websites, covering Python scripting, Python file manipulation, databases, views, Python object-oriented programming, and more. Python for data science is a popular choice because it requires knowledge of Python programming.
  • Learn about Python course topics, Python full-stack developer courses, Python syllabuses for beginners, and more here.

Python Course Topics

Python’s complete syllabus is extensive. Topics include Python overview, Python control statements, lists, ranges and tuples, Python dictionaries and sets, and more. A list of Python course topics is shown in the table below.

  • Introduction to Python
  • Python built-in function
  • Python Dictionaries and Sets
  • Input and Output in Python
  • Control Statements
  • List, Ranges & Tuples in Python
  • Exceptions
  • Python Object Oriented
  • Python Regular Expressions
  • Regular Expression
  • Python Multithreaded Programming
  • Using Databases in Python
  • Graphical User Interface
  • Thread Essentials
  • Data Science Using Python
  • Django Web Framework in Python
  • Web Scraping in Python

Python Syllabus for Beginners

Python IDE/Editor Establishment, Python Factors, Number juggling Administrators, Comparison Administrators, Task Administrators, Enrollment Administrators, etc are a few of the points for tenderfoots in Python. The nitty gritty Python Syllabus for Tenderfoots. The point-by-point syllabus for Python for Tenderfoots is recorded in the table underneath.

  •  Python IDE/Editor Installation
  • Python Variables
  • If Else Statement
  • Break & Continue Statement
  • Membership Operator
  • Comparison Operator
  • Arithmetic Operators
  • Assignment Operator
  • Python Built-in Modules
  • Web Scrapping
  • Python Regular Expressions (RegEx)
  • Python Database Communication
  • GUI Programming-Tkinter

Core Python Syllabus

Center Python covers themes such as the Presentation of Python, Introducing Python IDES: Python Sit out of gear and Boa constrictor, Data-types in Python, Factors in Python, Pigeonholing in Python, etc. You’ll check out the list of topics within the Center Python Syllabus in the table underneath:

  • Core Python
  • Introduction of Python
  • Operators in Python: Assignment, Logical, Arithmetic
  • Python Collections: List, Tuple, Sets, and Dictionary
  • Introducing Python IDES – Python Sit still and Anaconda
  • Data-types in Python
  • Variables in Python: Declaration and Use
  • Object Oriented Programming in Python

Advanced Python Syllabus

A few of the themes for the Development Python Syllabus incorporate Iterators for Lexicons, keys() and values(), The ‘in’ Administrator, Building Records, List Comprehension Language structure, etc. You’ll be able to check out the list of nitty-gritty subjects for the progressed Python Syllabus underneath:

  • Iterators for Lexicons
  • keys() and values()
  • Mysterious Capacities
  • List Cutting Sentence structure
  • Building Records
  • The ‘in’ Administrator
  • Excluding Lists
  • List Cutting
  • Comprehending Comprehensions
  • Lambda Sentence structure

Django Syllabus

Django with Python

Django could be a high-level Python web system that’s utilized for fast advancement in arrange to secure and viable websites. The table underneath gives the records of subjects secured beneath the Django Syllabus:

  • Presentation to Python
  • Protest Arranged Programming in Python
  • Capacities, Sorting, Mistakes, Special case, Customary Expressions, and Bundles
  • Presentation to Django Web System
  • Parsing XML and JSON with Python
  • Models and Energetic Webpages
  • Investigating, Databases, and Venture Skeletons
  • Layouts and Shapes
  • Serialization
  • Arrangements and Record Operations

Python Full Stack Developer Course

Full Stack Development Course

Python full stack designer is an open-source programming dialect, which has various applications. The syllabus for Python for Full Stack Engineer is given in detail within the table underneath:

Presentation

  • Learning Programming
  • Python Community

Improvement Situations

  • Content Editors and IDEs
  • Environment setup
  • Source Control
  • Terminal multiplexers
  • Shells

Information

  • Social databases
  • Information investigation
  • Markup Dialects
  • NoSQL
  • Object-relational mappers
  • Information visualization

Web Development

  • Web Systems
  • CSS Systems
  • API integration
  • Task queues
  • Layout Motors
  • JavaScript
  • Web plan
  • Testing
  • Inactive location generators
  • Organizing
  • Web APIs
  • Web application security
  • API creation

Web App Deployment

  • Facilitating
  • Working frameworks
  • Arrangement administration
  • Persistent integration
  • Platform-as-a-Service
  • Serverless Structures
  • WSGI servers
  • Web servers
  • Holders
  • Virtual Private Servers (VPSs)

DevOps

  • Checking
  • Web App Performance

To present, you’ve got got an understanding of Python and its syllabus at all levels. Presently let’s have a piece of information on what points are secured in that syllabus.

Python Programming course syllabus: Topics Covered

Introduction to Python Programming

The primary module of a normal Python programming course covers the nuts and bolts of Python programming. This incorporates a diagram of the Python programming dialect, its language structure, and how it is used in different businesses. You’ll check the Python programming course syllabus in the event that you’re planning to begin your career with Python. Understudies will also learn almost the diverse information types in Python, counting integrability, coasts, strings, and Boolean values.

Topics secured in this module may incorporate:

  • Outline of Python Programming
  • Python sentence structure and information sorts
  • Establishment and setup of Python
  • Factors, expressions, and articulations
  • Conditional articulations and circles

Data Structures in Python

Once understudies have a strong understanding of the nuts and bolts of Python programming, the course will move on to cover information structures in Python. This incorporates information structures like records, tuples, and word references, which are utilized to store and control information in Python.

Example:Data Structure in Python

Topics Covered in this module may incorporate:

  • Presentation of information structures in Python
  • Records, tuples, and lexicons
  • Getting to and controlling information structures
  • Built-in capacities for data structures
  • Cutting and ordering information structures

Functions and Modules

In the following module of a Python programming course, understudies will learn almost capacities and modules in Python. This incorporates a presentation of capacities, how to define and call capacities, and how to form and utilize modules in Python.

Example:

Functions & modules in Python

Topics Covered in this module may incorporate:

  • Presentation of functions in Python
  • Characterizing and calling functions
  • Parameters and contentions in capacities
  • Return articulations in capacities
  • Presentation to modules in Python

Object-Oriented Programming in Python

The other module of a Python programming course covers object-oriented programming (OOP) in Python. This incorporates a presentation of classes and objects, how to form and utilize objects in Python, and how to execute legacy in Python.

Example:

OOPS in Python

 

Topics Covered in this module may incorporate:

  • Presentation to object-oriented programming in Python
  • Classes and objects in Python
  • Making and utilizing objects in Python
  • Legacy in Python
  • Polymorphism in Python

File Handling and Exception Handling

Within the other module of this course, understudies will learn almost record taking care of and special case taking care of in Python. This incorporates a presentation to record dealing with Python, how to peruse and compose records in Python, and how to handle special cases in Python.

Example:

File Handling in Python

Topics Covered in this module may incorporate:

  • Presentation to record taking care of in Python
  • Perusing and composing records in Python
  • A special case dealing with Python
  • Taking care of distinctive sorts of special cases in Python
  • Investigating in Python

Web Scraping and Data Analysis

The ultimate module of this course covers web scratching and information examination in Python. This incorporates an introduction to web scratching, how to extricate information from websites utilizing Python, and how to utilize Python for information examination.

Topics Covered in this module may incorporate:

  • Presentation to web scratching in Python
  • Extricating information from websites utilizing Python
  • Information investigation in Python utilizing Pandas
  • Information visualization in Python utilizing Matplotlib
  • Presentation to machine learning in Python

 

Additional Read: How to become a Python Programmer in 2023?

Conclusion

Python could be a capable programming dialect that can be utilized for a wide run of applications, including web improvement, information science, and machine learning. On the off chance that you’re fascinated by learning Python, there is an assortment of courses accessible that can assist you get begun. On the off chance that you’re considering of beginning your career in programming at that point python training institutes in Faridabad are the most excellent.

The Python Programming course syllabus is designed by industry experts. In this course, you’ll learn the essentials of this course, information structures, capacities and modules, object-oriented programming, record taking care of and exemption taking care of, and web scratching and information examination. With these aptitudes, you will be well-equipped to begin building your possess Python ventures and seeking a career in Python programming.

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AGGREGATE FUNCTIONS
  • MySQL count()
  • MySQL sum()
  • MySQL avg()
  • MySQL min()
  • MySQL max()
MYSQL JOIN

MySQL JOIN

DATA ANALYTICS

DATA PRE-PROCESSING/WRANGLING

NUMPY
  • Fundamentals of NumPy
  • Types of arrays in NumPy
        Ones
        Empty
        Zeros
        Create Random Array
  • Reshaping of the array
         1-D to 2-D array
         2-D to 3-D array
         3-D to 1-D array
  • Arithmetic operations on  Array
         Addition
         Subtraction
         Multiplication
         Exponential
  • Slicing of the array
        How to slice array
        Change in properties during slicing
  • Transpose of a matrix
        How to take transpose
        Rows and columns  while taking transpose
  • Dot product of the matrix
       How to take Dot product of the Matrix
PANDAS
  • Data Frame
         What is Pandas Dataframe
         Different ways to create a Dataframe
        Read data from different sources and convert them to the Dataframe.
  • Pandas Series
        What is panda Series
        How to create a Panda Series.
  • Data inspection
         Using Count, info, head, tail.
         Using Shape, describe, unique, value etc
  • Data Slicing
        Data Slicing loc and iloc
  • Dataframe operations
         How to create a column or row
        How to delete a column or row
    Operations on Rows and Columns
  • Arithmetic operations on rows and
    columns
  • Handle Duplicate value and Null value
  • Handle outlier data
  • Group by Operations
  • Data Reshaping
  • Merging, Joining ,concatenation and
    append
  • Time series
MATPLOTLIB
  • Matplotlib for 3-D visualization
  • Bar, Pie, line, histogram
  • Countplot, boxplot, heatmap
SCIKIT-LEARN
  • Scikit models
  • Preprocessing using Scikit learn
  • Classification using Scikit-learn
  • Clustering using Scikit-learn
  • Regression using Scikit-learn
STATISTICS
  • Scalar and vector
  • Introduction to linear algebra
  • Measure of central tendency mean
  • Measure of central tendency mode
  • Measure of central tendency mode
  • Variance
  • Standard deviation
    Measure of shape skewness
    Measure of shape kurtosis
    Covariance and correlation
PROBABILITY
  • Importance of probability
  • Discrete and continuous variable
  • Bayes Theorem
  • Central Limit theorem
  • Normal Distribution
  • Bernoulli distribution
  • Uniform Distribution
HYPOTHESIS TESTING
  • Hypothesis testing and mechanism
  • Confidence interval
  • Margin of Errors
  • Confidence levels
  • T test and P values using python
  • Z test and P values using python
  • Chi Squared Distribution using python
LINEAR REGRESSION
  • Types of variables
  • Types of Linear variables
  • Mathematics Behind it
  • Implementation of the model
  • Testing and Check
  • Performance of the model
  • Assumptions of the Linear Regression
POLYNOMIAL REGRESSION
  • Need of polynomial Regression
  • Types of Variables in the Polynomial regression
  • Mathematics behind it
  • Implementation of the model
  • Testing and check performance of the
    model
MULTIPLE REGRESSION
  • Need of multiple Regression
  • Mathematics behind it
  • Implementation of the model
  • Testing and check performance of the model
RANDOM FOREST ALGORITHM
  • Why to use random Forest
  • Assumptions in random Forest
  • Working and Implementation of the Model
  • Data Pre-processing in Random Forest
SUPPORT VECTOR MACHINES
  • Types of SVM
  • Implementation of the SVM
  • Creating confusion matrix
NAIVE BAYES CLASSIFIER ALGORITHM
  • Bayes Theoram
  • Implementation of Naïve Bayes
    Classifier
  • Type of Naïve Bayes Model

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JAVASCRIPT EVENTS

Event listeners and handlers
Mouse events
Keyboard events

DOCUMENT OBJECT MODEL (DOM)

Accessing and manipulating HTML elements
DOM navigation and manipulation
Creating and removing HTML elements

1. INTRODUCTION TO REACT.JS

What is React.js?
History and evolution of React.js
React.js components and their role in
building web applications
Setting up the development environment

JSX

Introduction to JSX
Basic syntax and rules of JSX
Embedding expressions in JSX
Conditional rendering in JSX
Working with lists in JSX

REACT COMPONENTS

Understanding components
Creating class components
Creating functional components
Props and state in React components
Lifecycle methods in React components

REACT EVENTS

Handling events in React
Binding event handlers in React
Passing data to event handlers in React
Conditional rendering based on events in
React

REACT FORMS

Creating forms in React
Handling form submission in React
Controlled and uncontrolled components
in React

REACT ROUTING

Introduction to React Router
Setting up routing in React
Creating routes in React

INTRODUCTION TO MONGODB

What is MongoDB?
Advantages of MongoDB over RDBMS
MongoDB data model and architecture
Setting up the development environment

CRUD OPERATIONS

Creating and inserting documents in
MongoDB
Reading documents from MongoDB
Updating documents in MongoDB
Deleting documents from MongoDB

QUERYING MONGODB

Querying MongoDB using find() method
Querying MongoDB using comparison and
logical operators
Querying MongoDB using regular
expressions
Querying MongoDB using aggregation
framework

INTRODUCTION TO NODE.JS

What is Node.js?
Advantages of Node.js over other serverside technologies
Node.js architecture and event-driven
programming model
Setting up the development environment

NODE.JS MODULES

Introduction to Node.js modules
Creating and using built-in modules
Creating and using custom modules
Working with NPM (Node Package
Manager)

NODE.JS HTTP

Creating HTTP server in Node.js
Understanding HTTP methods and status
codes
Handling HTTP requests and responses
Serving static files in Node.js

EXPRESS.JS FRAMEWORK

Introduction to Express.js framework
Creating and configuring Express.js
application
Handling HTTP requests and responses in
Express.js
Implementing middleware in Express.js

NODE.JS DATABASE CONNECTIVITY

Introduction to database connectivity in
Node.js
Connecting to MongoDB database in
Node.js
Performing CRUD operations in Node.js
using MongoDB
Using Mongoose ORM with MongoDB in
Node.js

NODE.JS SECURITY

Introduction to security in Node.js
Understanding and implementing
authentication and authorization in
Node.js
Implementing HTTPS in Node.js
Preventing common security vulnerabilities
in Node.js

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