Python Full Stack with AI Training in Bangalore

About the Python Full Stack with AI Training in Bangalore

The Python Full Stack with AI course in Bangalore helps you learn all the stages of application development. You will learn to code in Python. You will learn Frontend Development using HTML, CSS, JavaScript, and React.js. Then you will learn backend development using Django and FastAPI. You will learn how to use SQL, MySQL, PostgreSQL, ORM, and data modelling. Then you will learn about Data Analysis using NumPy and Pandas. Then you will learn about Machine Learning using Scikit-learn. Then you will learn Generative AI, LLM APIs, LangChain, RAG Pipelines, and AI Chatbots. You will also learn how to test APIs, Debug, Version Control using Git, Docker. You will practice using these concepts.

What You Will Learn

• Write Python programs using functions, OOP, data structures, and exception handling.
• Build responsive interfaces with HTML, CSS, JavaScript, and React.js.
• Develop backend services using Django, FastAPI, REST APIs, and authentication.
• Manage application data with SQL, MySQL, PostgreSQL, and ORM.
• Explore Machine Learning, Generative AI, LLMs, RAG, and AI chatbot integration.
• Test, debug, version-control, and deploy applications using Git, GitHub, Docker, and cloud platforms.

Syllabus of Python Full Stack with AI Training in Bangalore

Module 1: Python Programming Fundamentals

• Python syntax, variables, data types, and operators
• Conditional statements, loops, and control flow
• Functions, lambda expressions, and built-in methods
• Lists, tuples, dictionaries, sets, and data structures
• Object-Oriented Programming (OOP), inheritance, and polymorphism
• Exception handling, file operations, modules, and packages
• Iterators, generators, decorators, and asynchronous programming
• Debugging techniques and unit testing basics

Module 2: Frontend Web Development

• HTML5 elements, forms, and semantic markup
• CSS3 styling, Flexbox, Grid, and responsive layouts
• JavaScript fundamentals, ES6+ features, and DOM manipulation
• Events, promises, async/await, and Fetch API
• React.js components, props, state, and hooks
• React Router and frontend navigation
• Context API or Redux for state management
• Connecting user interfaces with backend services

Module 3: Backend Development with Django

• Django installation, project setup, and application structure
• URL routing, views, templates, and request handling
• Models, Django ORM, and database operations
• CRUD functionality for web applications
• Forms, validation, and user authentication
• Roles, permissions, and session management
• Django REST Framework and API creation
• Application security and backend testing

Module 4: API Development with FastAPI

• FastAPI project configuration and endpoint creation
• HTTP methods, status codes, and request handling
• Request validation and response models using Pydantic
• Building and documenting REST APIs
• Async endpoints and background task processing
• API authentication and error handling
• WebSockets and real-time communication fundamentals
• Integrating Python APIs with frontend applications

Module 5: Database Design and Integration

• Relational database concepts and SQL commands
• MySQL and PostgreSQL database operations
• Tables, keys, constraints, and relationships
• Joins, subqueries, aggregate functions, and transactions
• Database normalization, indexing, and query optimization
• ORM concepts and database migrations
• Introduction to NoSQL databases and document storage
• Connecting databases with Django and FastAPI

Module 6: Machine Learning and Data Analysis

• Introduction to Artificial Intelligence and Machine Learning
• Data manipulation using NumPy and Pandas
• Data cleaning, preprocessing, and exploratory analysis
• Data visualization and feature preparation
• Supervised and unsupervised learning techniques
• Regression, classification, and clustering algorithms
• Model training, testing, and performance evaluation
• Implementing basic ML workflows using Scikit-learn

Module 7: Generative AI and Large Language Models

• Generative AI concepts and common application areas
• Understanding Large Language Models (LLMs)
• Prompt design and prompt engineering techniques
• Connecting Python applications with AI model APIs
• Managing conversation history and contextual responses
• Generating structured outputs from language models
• Building text summarization and question-answering features
• Developing AI-powered chatbot applications

Module 8: Retrieval-Augmented Generation (RAG)

• RAG architecture and its role in AI applications
• Loading and processing documents from different sources
• Text splitting, chunking, and metadata handling
• Embeddings and semantic similarity search
• Vector database concepts and integration
• Retrieving relevant information for LLM responses
• Building document-based question-answering systems
• Testing retrieval quality and improving response relevance

Module 9: AI Agents and Workflow Automation

• Introduction to AI agents and agent-based workflows
• Function calling and tool integration
• Connecting language models with external APIs
• Using application data and databases in AI workflows
• Managing conversation state and context
• Automating multi-step tasks with AI
• Introduction to multi-agent coordination
• Developing practical AI-assisted workflow applications

Module 10: Full Stack Application Integration

• Planning the architecture of a full stack application
• Connecting React.js interfaces with Python backends
• Integrating Django and FastAPI services where appropriate
• Linking application features with SQL databases
• Adding AI APIs and LLM-powered functionality
• Implementing authentication and access controls
• Handling validation, errors, and application logs
• Testing the complete frontend-to-backend workflow

Module 11: Version Control and Application Deployment

• Git fundamentals, branching, merging, and version history
• Managing source code through GitHub repositories
• Environment variables and configuration management
• Introduction to Docker and container-based deployment
• Preparing applications for production environments
• CI/CD concepts and automated build workflows
• Deploying applications on suitable cloud hosting platforms
• Basic application monitoring, logging, and maintenance

Module 12: Practical Projects and Portfolio Development

• Build a full stack task management application
• Develop an expense tracker with AI-assisted insights
• Create a document-based AI question-answering chatbot
• Build a meeting notes and summary application
• Integrate an AI assistant into a web application
• Test application functionality and resolve technical issues
• Document project architecture, features, and setup instructions
• Publish project code on GitHub and prepare for technical interviews

Upcoming Batch Schedule for Python Full Stack with AI Training in Bangalore

Besant Technologies provides flexible timings to all our students. Here are the Python Full Stack with AI Training in Bangalore Schedule in our branches. If this schedule doesn’t match please let us know. We will try to arrange appropriate timings based on your flexible timings.

• 09-11-2026 Mon (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 05-11-2026 Thu (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 07-11-2026 Sat (Sat - Sun)Weekend Batch 11:00 AM (IST) (Class 3Hrs) / Per Session Get Fees

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Python Full Stack with AI Course Trainer Profile

Aravind Prakash has more than 11 years of experience in software, backend, and application development. He has a good working knowledge of Python, Django, FastAPI, React.js, REST API, SQL, and developing applications in the cloud. He has experience using AI applications like Machine Learning, LLM APIs, prompting, LangChain, and RAG. This course will help you solve coding problems, understand application architecture, link databases, and build projects with web and AI. You will learn how to piece together all aspects of coding to create a complete application.

Python Full Stack with AI Certification Course in Bangalore- Besant Technologies

Besant Technologies Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.

Our certification at Besant Technologies is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s of the world. The certification is only provided after successful completion of our training and practical based projects.

After completing the Python Full Stack with AI training at Besant Technologies, learners can receive a course completion certificate subject to the institute’s requirements. Those who want to strengthen their professional credentials can also explore external certifications relevant to Python programming, cloud development, and AI technologies. Options may include Python Institute credentials, AWS Certified Developer – Associate, and suitable Microsoft Azure developer or AI certifications. Each external certification has its own examination requirements and is separate from the institute’s course completion certificate.

Key Features of Python Full Stack with AI Training in Bangalore

• Code from Scratch: Practise writing Python programs and learn to structure clean, maintainable code as part of the Python Full Stack with AI course in Bangalore with placements.
• Build Interactive Web Pages: Create responsive user interfaces and connect frontend components to backend services.
• Develop Database-Driven Applications: Learn how to store, retrieve, update, and manage application data using SQL databases.
• Create RESTful Services: Understand API routing, request validation, authentication, response handling, and error management.
• Connect AI to Web Applications: Explore ways to add LLM-powered chat, text summarisation, and document search features to applications.
• Work with Real Development Scenarios: Practise debugging, resolving application errors, handling user inputs, and testing individual features.
• Understand Application Security: Learn the basics of authentication, permissions, secure configuration, and API access management.
• Manage Code Changes: Use Git and GitHub to maintain project versions and collaborate on development tasks.
• Learn the Deployment Process: Explore environment setup, Docker fundamentals, cloud hosting, and application release workflows.
• Prepare a Technical Portfolio: Organise project code, document application features, and practise explaining development decisions in interviews.

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