Become a Back-End Development Expert with SNQTECH

Are you ready to embark on a journey to master back-end development? Our comprehensive Back-End Development program is designed to equip you with the skills and knowledge needed to excel in the dynamic IT industry.

  • Experienced Mentors
  • Dedicated to Success
  • Certificate of completion
  • Accessible & Supportive
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Why Choose Our Python Full Stack Program?

Hands-on Experience:

Engage in real-world projects that simulate a full development lifecycle, providing you with essential skills and insights.

Expert Mentorship:

Learn directly from industry experts who will guide and support you throughout your journey.

Career Assistance:

Receive guidance on job searches, resume building, and interview preparation to help you secure your desired role.

What You'll Learn

  • Back-End Technologies: Core and advanced Python, Django, Flask, SQL and NoSQL databases, deployment using Git and Docker.
  • Server-Side Programming: Master the essential principles, methodologies, and technical intricacies of back-end development.
  • Project-Based Learning: Participate in mini-projects covering key phases like requirement analysis, system design, server-side programming, database management, integration, and deployment.
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Who are Eligible

  • Individuals with a degree in B. Tech / M.Tech / MCA / M.Sc / M.A / MBA / BCA / B.Sc (any specialization).
  • No prior experience in back-end development required.
  • Passion for technology and a desire to innovate.

Duration

90 Sessions

Validity

Life Time

Mode

Virtuak

Eligibility

Everyone

What we are going to learn in this course?

●      What is Python, Introduction and Importance of Python.

●      Python Local Environment Setup

●      Installing a Specific Python Version

●      Implementing IDE, Different Types of IDES and their uses

Working with Identifiers in Python.
  • What an identifier(variable)
  • Rules for an identifier (variable)
  • Integer DataType
  • Floating DataType
  • String DataType and Its Methods
    • Join() len() replace() split() strip() estrip() Istrip() upper() lower() and etc
  • Boolean DataType
  • Complex DataType
  • Bytes DataType
  • List DataType and its properties
  • Tuple DataType and its properties
  • Set DataType and its properties
  • Dictionary DataType and its properties
  • Difference between Array, List, Set, Tuple and Dictionary DataTypes.
  • ByteArray DataType and its properties
  • Frozenset DataType and its properties
  • Range DataType and its properties
  • None DataType and its properties
  • Arithmetic operators
  • Assignment operators
  • Logical operators
    • Logical AND operator
    • Logical OR operator
    • Logical NOT operator
  • Equality operators
  • Comparison operators
  • Chaining operators
  • Ternary operators
  • Special type of operators.
  • Bitwise operators
  • Working with end attribute
  • Formatted string
  • Replacement operators
  • if
  • nested if
  • if else
  • if elif else
  • for loop
  • nested for loop
  • while loop
  • nested while loop
  • pass statement
  • break statement
  • continue statement
  • List comprehension
  • Tuple comprehension
  • Set comprehension
  • Dictionary comprehension
  1. What is function and Types of functions in Python
  • How to create a function and its uses in real time applications
  • Working with “main” function
  • Formal and Actual parameters
  • Arguments and Parameters in functions
  • Difference between **ob1j** & **obj2**
  • Working with lambda keyword

2.  Working with High order functions:

  • filter()
  • map()
  • reduce()
  • Nested() and etc

3.  Packages in Python

  • What is a module
  • What is a package
  • How to Import & export data from one to another module
  • Working with reload () functions
  • Working with math module
  • Working with random module

4. Concepts of Data Structures and Algorithms

  • Stack
  • Queue
  • singleLinked list
  • DoubleLinked list

OOPS in Python

  1. How to create a object, class, functions, variables and constructor

    Class

    Inner classes

    Nested Class

    Concrete class

    Types of functions

    Instance method (Non static method)

    What is class method

    What is static method

    Types of Variables

    What is Instance variable

    Static Variable

    Non static Variables

    Working with GC(Garbage Collection) module

    Inheritance concept and Types of Inheritance

    Polymorphism

    Operator overloading Method overloading

    Method overloading with default and variable length argument

    Constructor overloading and Constructor overloading with default argument

    Constructor overloading with variable length argument

    Method overriding

    Constructor overriding

    Encapsulation

    Abstraction

    Interface in python

    Handling the Files in Python

    Handling various files such as CSV, Excel, txt and etc

    Why file and file fiddling

    Reading and writing lines in a file

    Working with with statement Working with pickling & unpickling

    Working with Zipping and Unzipping, object deserialization and deserialization

    Error, Exceptions, Types of Exceptions and Exception Handling

    What are and Uses of Decorators in Python

    What are Generators in python

    Multithreading and types of MultiThreading Concepts in python

    Assertions and types of Assertions in Python:

    What is REGEX (Regular Expression) and It’s methods

Web Development

  1. Django

    Get Started with Django

    What is Django, Introduction and Importance of Django

    Installation and setup

    Creating a new project and app

    Django project structure

    Models of Django

    Views in Django

    Function-based views vs. class-based views

    Handling requests and responses

    URL routing and path converters

    Template and Various Templates in DJango

    Forms, Types of Forms and error handling with Django

    Admin Interface, Customization, Registering and Admin Actions in Django

    Serving static files (CSS, JavaScript) and Handling media uploads

    Authentication and Authorization

    Understanding middleware, its use cases and Creating the  custom middleware

    Writing Unit tests and functional tests, Testing views, models in Django

    Building RESTful APIs with Django REST Framework, Serialization, viewsets and Authentication for APIs (JWT, OAuth) in Django

    Deployment of Django project into various servers

    Using Django with async views and Understanding Channels for WebSockets

    Database optimization techniques

    Flask

    Understanding and implementation of Flask framework

    Installation, setting up the flask environment and Creating a basic Flask app

    Flask Project structure and best practices

    URL routing and dynamic routes Using URL converters and Handling HTTP methods (GET, POST, etc.) using FLASK

    Templates in FLASK

    Forms in FLASK

    DataBase Integration Techniques with Flask

    Authentication and Authorization with FLASK

    BluePrints in FLASK

    Error Handling with FLASK

    FastAPI

    What is FASTAPI and Understanding FastAPI and It’s uses.

    Using parameters in URLs and queries.

    Handling JSON request bodies with Pydantic models.

    Returning structured responses using Pydantic in FastAPI.

    Dependency Injection and Managing dependencies in the endpoints.

    Adding custom middleware for request/response processing.

    Error Handling and Customizing error responses and status codes.

    Implementing authentication and authorization (OAuth2, JWT).

    Database Integration and Connecting to databases with SQLAlchemy or other ORMs.

    Writing tests for your FastAPI application.

    CORS i.e, Configuring Cross-Origin Resource Sharing settings in Fast API

    Asynchronous Support Using async and await for non-blocking code.

    Deployment of Fast API Applications into various servers

  1. Pandas

    What is Pandas, Understanding, Uses and Implementation

    Installing Pandas and setting up your environment.

    Data Structures in Pandas and Understanding Series and DataFrames.

    Implementation Data Import Techniques to extract data from CSV, Excel, and other formats.

    Data Exploration Using Pandas methods like head(), info(), and describe().

    Indexing and Selecting Data, Accessing data using labels, positions, and boolean indexing.

    Data Cleaning, Handling missing values, duplicates, and data types.

    Transforming Data in Pandas by applying functions and using apply(), map(), and applymap().

    Techniques to Filter and Sorting in Pandas

    Grouping, aggregation and summarizing the data using Pandas.

    Working with datetime data and time series functions in Pandas.

    Creating pivot tables and other GUI Reports using Pandas Techniques.

    Implementation of Visualization Techniques for basic plotting with Pandas and integration with Matplotlib.

    Learning other Advanced Features Using MultiIndex, categorical data, and window functions and etc.

    NumPy

    Understanding, Installing NumPy and setting up your environment.

    Creating and manipulating NumPy arrays.

    Array Operations By Performing element-wise operations and broadcasting in NumPy

    Indexing and Slicing in NumPy

    Implementation of Mathematical Functions using built-in functions for calculations (mean, sum, etc.).

    Learning how to load and save the arrays from files and to files using NumPy

    Working with Masked arrays that have missing or invalid entries.

    Working on Advanced Indexing concepts in NumPy

    TensorFlow

    Installation, and TensorFlow SetUp

    Understanding the basic data structure of TensorFlow.

    Building neural network models using the Sequential API in TensorFlow.

    Training the models by Compiling, fitting, and evaluations.

    Implementation of Data Pipeline in TensorFlow

    Implementing TensorBoard.

    Training models on multiple GPUs or machines.

    Deploying models for inference in production environments.

    PyTorch

    Understanding and creating PyTorch tensors.

    Performing mathematical operations on tensors.

    Learning Optimization Techniques using various optimizers like SGD and Adam.

    Utilizing CUDA for accelerated computing and GPU Support.

    Cloning pre-trained models for new tasks.

    Implementing dropout and weight decay for Regularization.

    Exporting models for production using TorchScript or ONNX etc.

SciPy

What is SciPy, Introduction and Importance of SciPy

Installing SciPy and setting up the SciPy environment.

Understanding the relationship between SciPy and NumPy.

Learning Scientific Computing using SciPy for mathematical functions and operations.

Techniques for Solving optimization problems, Performing Numerical Integration, Interpolating data points  with SciPy Methods.

Learning Linear Algebra using SciPy functions for matrix operations with .

Working on Signal Processing, Analyzing and filtering signals with SciPy Techniques

Learning Fourier Transforms for frequency analysis.

Basic image manipulation and processing in SciPy.

Implementing clustering algorithms with scipy.cluster.

Learning Delaunay Triangulation for geometric operations.

Matplotlib

Introduction to Matplotlib, and setting up the environment locally.

How to create simple line plots using Matplotlib

Editing the figure and axes objects.

Introducing different types of plots like scatter, bar, histogram etc.

Learning how to modify the plot appearances like titles, labels, legends etc.

Creating multiple plots and subplots in a single figure using matplotlib

Introduction and implementation of annotations

Learning Styling functions and techniques

Implementation of 3D plotting

Customizing grid lines and tick marks on axes using matplotlib

Integrating Matplotlib with Pandas for data visualization

Future Career Opportunities

The Back-End Development industry is rapidly growing, with numerous career opportunities such as:

  • Back-End Developer
  • Technical Lead
  • Solutions Architect
  • Senior Developer

Ready to Transform Your Career?

Enroll today and be your own master in the IT industry with SNQTECH!