Python Full Stack with GenAI

Get the best python full stack training and Genrative AI online or on-campus with BTES experts.

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Online

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On Campus

Starting Date: 05th Jan, 2026 | 28th Jan, 2026

Duration

Regular Training - NA
Industrial Training - 6 Months, 6 Months

Mode Of Delivery i

Quick Enquiry

B.Tech/B.E. in Computer Science, MCA, or related field. Basic knowledge of programming and web development will be an advantage.

For Online Courses Only

Course Description

This comprehensive Python full stack developer course is designed to equip students with the skills necessary to become proficient Python full stack developers with hands-on experience in AI concepts. The curriculum uses the Python programming language to cover the entire spectrum of web development, including frontend, backend, and data handling. Students will learn through hands-on practice and real-world projects, ensuring they are well-prepared for a career in full stack development

*Pre-requisite Qualification(s) Should Be

B.Tech/B.E. in Computer Science, MCA, or related field. Basic knowledge of programming and web development.

Python Full Stack with GenAI Course

Our USPs

Placement Backed Programs*
Industry Endorsed & AI-Enriched Curriculum
Get Trained in World Class Methodologies
Training in Hybrid Mode
In-House Training Through LMS Tool
Technology Expert & Dedicated Trainers
Personalized Attention & Flexible Schedule
Soft-Skill & PD Classes on Periodical Basis
Technology Sessions by bebo Experts
Adaptive Training
360-Degree Orientation Program

Course Content

Core Python Programming - Counting Topics..

Overview of Python
Setting up Python Environment
Memory Model of Python & Variables
Data Types & Basic Operators (Arithmetic, Comparison, Logical)
Conditional Statements & Control Statements
String Operations, String Methods
List, Tuple, Dictionary, Set
Functions, Function Arguments, and Return Values
Lambda Functions
Working with Modules
File Handling
OOPS Concepts
Exception Handling
Popular Libraries (math, datetime, random, request, etc.)

Frontend Development - Counting Topics..

HTML5 & CSS3
DOM Manipulation
Event Handling
ES6 Concepts
Object-oriented Concepts
Responsive Design with Bootstrap
Version Control Basics using GitHub/GitLab
Advanced Git Techniques (Branching, Merging, Rebase, etc.)
Introduction to React
Creating React Components, State, and Props
Handling Events
React Lifecycle Methods
Redux
Actions and Action Creators
Reducers

Backend Development - Counting Topics..

Overview of Flask and Django
Framework Architecture
URL Routing
Creating Views and Templates
Handling Forms & Validations
SQL Basics
ORM (SQLAlchemy for Flask, Django ORM)
CRUD Operations
Migrations
Password Hashing and Security
Session Management
Creating RESTful APIs
Consuming Third-party APIs

Advanced Python and Deployment - Counting Topics..

Asyncio Basics
Threads
Multiprocessing
Working with Asynchronous Libraries
Real-time Communication with WebSockets
Deployment Options (Heroku, AWS, DigitalOcean, etc.)
Setting Up a Production Server
Using Docker for Containerization
Unit Testing
Integration Testing
Using Frameworks like PyTest

Generative AI and LLM Essentials - Counting Topics..

Generative AI and its Landscape
Applications of Generative AI
Introduction to Large Language Models (LLMs)
Transformer Architecture
Exploring Open-source LLMs
Introduction to HuggingFace and Pre-trained LLM Models
Limitations of LLMs
Pros and Cons of Different LLM Architectures
Accessing and Using Open-source LLMs for Projects
Best Practices for Responsible AI Development

Prompting Techniques for Generative Models - Counting Topics..

Basic Principles of Prompt Engineering
What is Prompt Engineering?
Importance of Prompt Engineering in Generative AI Models
Common Tools for Prompt Engineering
Strategies for Designing Prompts
Different Types of Prompting
Writing Effective Prompts
Best Practices for Strong Prompts

Interacting with Data through Retrieval-augmented Generation (RAG) - Counting Topics..

Overview of RAG
RAG Architecture
Techniques for Retrieving Data
Keyword Matching Methods
Using Sentence Transformers
Combining LLMs with Prompts and Retrieved Data
Strategies for Data Augmentation

Natural Language Processing (NLP) - Counting Topics..

NLP Fundamentals
Text Data Preprocessing
LangChain for Building LLM Applications
LangChain Framework Overview
LangChain Components
Building a Simple LLM Application

LLMs for Word Embedding and Chunking - Counting Topics..

Introduction to Word Embedding
Techniques for Word Embedding
Understanding Word Relationships
Methods for Sentence Embedding
Overview of Vector Databases
Types of Vector Databases
Chunking a Document
Traditional and Advanced Chunking Methods
Semantic Chunking
Building a GenAI Chatbot

Machine Learning Fundamentals - Counting Topics..

Introduction to Machine Learning Concepts
NumPy for Numerical Computing
Pandas for Data Manipulation
Matplotlib and Seaborn for Data Visualization
Supervised Learning Algorithms

Benefits To Students - Counting Benefits..

On completing this course, the students will get various benefits like:

Proficiency in Python programming and object-oriented principles
Capability in both frontend and backend web development
Skilled in Flask, Django, React, and Redux frameworks
Experience in building and deploying RESTful web services and microservices
Knowledge of basic and advanced machine learning and AI techniques
Preparation for job interviews and roles requiring full stack development with AI and machine learning integration

Exit Profile Of The Student

Mastery in Python programming and OOP concepts
Full stack web development skills
Experience with modern web frameworks and libraries
Expertise in building and deploying RESTful APIs and microservices
Foundational knowledge in Generative AI and NLP applications

Course Description

This comprehensive Python full stack developer course is designed to equip students with the skills necessary to become proficient Python full stack developers with hands-on experience in AI concepts. The curriculum uses the Python programming language to cover the entire spectrum of web development, including frontend, backend, and data handling. Students will learn through hands-on practice and real-world projects, ensuring they are well-prepared for a career in full stack development

*Pre-requisite Qualification(s) Should Be

B.Tech/B.E. in Computer Science, MCA, or related field. Basic knowledge of programming and web development.

Course Content

Core Python Programming - Counting Topics..

Overview of Python
Setting up Python Environment
Memory Model of Python & Variables
Data Types & Basic Operators (Arithmetic, Comparison, Logical)
Conditional Statements & Control Statements
String Operations, String Methods
List, Tuple, Dictionary, Set
Functions, Function Arguments, and Return Values
Lambda Functions
Working with Modules
File Handling
OOPS Concepts
Exception Handling
Popular Libraries (math, datetime, random, request, etc.)

Frontend Development - Counting Topics..

HTML5 & CSS3
DOM Manipulation
Event Handling
ES6 Concepts
Object-oriented Concepts
Responsive Design with Bootstrap
Version Control Basics using GitHub/GitLab
Advanced Git Techniques (Branching, Merging, Rebase, etc.)
Introduction to React
Creating React Components, State, and Props
Handling Events
React Lifecycle Methods
Redux
Actions and Action Creators
Reducers

Backend Development - Counting Topics..

Overview of Flask and Django
Framework Architecture
URL Routing
Creating Views and Templates
Handling Forms & Validations
SQL Basics
ORM (SQLAlchemy for Flask, Django ORM)
CRUD Operations
Migrations
Password Hashing and Security
Session Management
Creating RESTful APIs
Consuming Third-party APIs

Advanced Python and Deployment - Counting Topics..

Asyncio Basics
Threads
Multiprocessing
Working with Asynchronous Libraries
Real-time Communication with WebSockets
Deployment Options (Heroku, AWS, DigitalOcean, etc.)
Setting Up a Production Server
Using Docker for Containerization
Unit Testing
Integration Testing
Using Frameworks like PyTest

Generative AI and LLM Essentials - Counting Topics..

Generative AI and its Landscape
Applications of Generative AI
Introduction to Large Language Models (LLMs)
Transformer Architecture
Exploring Open-source LLMs
Introduction to HuggingFace and Pre-trained LLM Models
Limitations of LLMs
Pros and Cons of Different LLM Architectures
Accessing and Using Open-source LLMs for Projects
Best Practices for Responsible AI Development

Prompting Techniques for Generative Models - Counting Topics..

Basic Principles of Prompt Engineering
What is Prompt Engineering?
Importance of Prompt Engineering in Generative AI Models
Common Tools for Prompt Engineering
Strategies for Designing Prompts
Different Types of Prompting
Writing Effective Prompts
Best Practices for Strong Prompts

Interacting with Data through Retrieval-augmented Generation (RAG) - Counting Topics..

Overview of RAG
RAG Architecture
Techniques for Retrieving Data
Keyword Matching Methods
Using Sentence Transformers
Combining LLMs with Prompts and Retrieved Data
Strategies for Data Augmentation

Natural Language Processing (NLP) - Counting Topics..

NLP Fundamentals
Text Data Preprocessing
LangChain for Building LLM Applications
LangChain Framework Overview
LangChain Components
Building a Simple LLM Application

LLMs for Word Embedding and Chunking - Counting Topics..

Introduction to Word Embedding
Techniques for Word Embedding
Understanding Word Relationships
Methods for Sentence Embedding
Overview of Vector Databases
Types of Vector Databases
Chunking a Document
Traditional and Advanced Chunking Methods
Semantic Chunking
Building a GenAI Chatbot

Machine Learning Fundamentals - Counting Topics..

Introduction to Machine Learning Concepts
NumPy for Numerical Computing
Pandas for Data Manipulation
Matplotlib and Seaborn for Data Visualization
Supervised Learning Algorithms

Benefits To Students - Counting Benefits..

On completing this course, the students will get various benefits like:

Proficiency in Python programming and object-oriented principles
Capability in both frontend and backend web development
Skilled in Flask, Django, React, and Redux frameworks
Experience in building and deploying RESTful web services and microservices
Knowledge of basic and advanced machine learning and AI techniques
Preparation for job interviews and roles requiring full stack development with AI and machine learning integration

Exit Profile Of The Student

Mastery in Python programming and OOP concepts
Full stack web development skills
Experience with modern web frameworks and libraries
Expertise in building and deploying RESTful APIs and microservices
Foundational knowledge in Generative AI and NLP applications

Refer to our online Course

Python Full Stack with GenAI Course

Our USPs

Placement Backed Programs*
Industry Endorsed & AI-Enriched Curriculum
Get Trained in World Class Methodologies
Training in Hybrid Mode
In-House Training Through LMS Tool
Technology Expert & Dedicated Trainers
Personalized Attention & Flexible Schedule
Soft-Skill & PD Classes on Periodical Basis
Technology Sessions by bebo Experts
Adaptive Training
360-Degree Orientation Program

FAQs

Have a question? Check from our list of frequently asked questions.

Why should I enroll for this course?

This course offers a comprehensive curriculum covering core Python programming, frontend and backend development, advanced Python concepts, and AI technologies, equipping you with a competitive edge in the tech job market

Is a strong programming background required for this course?

While a basic understanding of programming is beneficial, the course progresses from foundational knowledge to advanced skills, though prior experience in Python or any programming language is helpful

Do I need any prior experience in web development to join this course?

No prior experience is required, as the course covers the basics of HTML, CSS, and JavaScript before advancing to complex concepts

Can I clear job interviews after completing the course?

The course prepares you with the practical skills needed for full stack development and AI roles and includes interview preparation and mock interviews

Still Have a Query? Please Contact on +91-8427696621, +91-82838 23237 or Click Here

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