Generative AI for Full Stack Developers (Django + React.js + PostgreSQL)
This course is designed to help Full Stack Developers integrate Generative AI into web applications built with Django (Backend), React.js (Frontend), and PostgreSQL (Database).
- Course fee
- Contact us
- Duration
- 5 days
- Group rate
- Ask an advisor
Course overview
This course is designed to help Full Stack Developers integrate Generative AI into web applications built with Django (Backend), React.js (Frontend), and PostgreSQL (Database).
Participants will learn how to use AI-powered tools and models to:
Enhance frontend interactivity with AI-driven UI elements.
Automate backend tasks using AI APIs.
Implement AI-powered chatbots, search engines, and recommendation systems.
Optimize database queries and analytics with AI-driven insights.
By the end of this course, developers will be able to build intelligent, AI-powered full-stack applications that are scalable and efficient.
Training methodology
This course follows a hands-on, project-based approach, including:
Instructor-led sessions – Live coding, AI demos, and technical discussions.
Practical assignments & real-world case studies – Building AI-powered features.
Interactive coding labs – Implementing AI models in full-stack applications.
Capstone project – Developing and deploying an AI-powered full-stack web app.
Prerequisites
- Experience with Python & Django (Django REST Framework preferred).
- Familiarity with JavaScript, React.js, and state management (Redux/Zu-stand).
- Understanding of SQL databases (PostgreSQL) and API integration.
- Basic knowledge of Machine Learning & AI APIs (helpful but optional).
Target competencies
- By the end of the course, participants will:
- Integrate AI models into Django-based backend architectures.
- Use AI APIs in React.js for intelligent UI interactions.
- Enhance PostgreSQL queries and analytics using AI.
- Develop AI-powered features like chatbots, recommendation engines, and search tools.
- Deploy AI-enhanced applications on cloud platforms.
Course objectives
Upon completing the course, participants will:
- Build full-stack AI-powered applications using Django, React.js, and PostgreSQL.
- Implement AI-enhanced chatbots, search engines, and recommendation systems.
- Use AI for automated content generation and data processing.
- Integrate AI APIs and models into frontend and backend systems.
- Deploy AI-powered applications on AWS, Azure, or GCP
Course outline
- Overview of Generative AI and its role in web development.
- Introduction to LLMs (GPT-4, LLaMA), image models (Stable Diffusion, DALL·E), and AI APIs.
- Understanding AI-powered frontend, backend, and database integrations.
- Hands-on: Setting up a Django + React.js + PostgreSQL development environment for AI.
- AI-generated text, reports, and dynamic web content.
- Automating blog creation, email templates, and SEO-optimized articles.
- Using AI for personalized content recommendations.
- Hands-on: Integrating OpenAI’s GPT API for automated content generation in Django & React.js.
- Understanding Natural Language Processing (NLP) for chatbot development.
- Building AI-powered chatbots with Open-AI, Rasa, and Lang-Chain.
- Connecting chatbots with Django REST APIs & React.js UI.
- Hands-on: Developing a full-stack AI chatbot with Django and React.js.
- Implementing AI-based product and content recommendations.
- Using collaborative and content-based filtering with AI.
- Enhancing user engagement with AI-driven recommendations.
- Hands-on: Building a Django + PostgreSQL recommendation engine with AI.
- Implementing AI-enhanced search features using vector embeddings.
- AI-powered auto-suggestions and autocomplete for search bars.
- Using Elasticsearch and AI for semantic search.
- Hands-on: Developing an AI-powered intelligent search engine with PostgreSQL.
- Using AI for code generation, debugging, and optimization.
- AI-assisted unit testing, documentation, and refactoring.
- Automating Django & React development tasks with AI tools.
- Hands-on: Optimizing Django REST APIs and React.js components using AI.
- AI-powered UI personalization and dynamic UI generation.
- AI-driven image and video generation using Stable Diffusion.
- Implementing AI-based form validation and accessibility improvements.
- Hands-on: Building an AI-enhanced frontend with React.js.
- Using AI for predictive analytics and business intelligence.
- AI-powered real-time data analytics and visualization.
- Implementing AI-driven insights and decision-making models.
- Hands-on: Integrating AI-based data analysis in a Django + PostgreSQL app.
- Best practices for deploying AI-enhanced full-stack applications.
- Optimizing performance, security, and scalability of AI features.
- Deploying AI-powered web apps on AWS, Azure, or Google Cloud.
- Hands-on: Deploying a Django + React.js AI-powered app using Docker & CI/CD.
- Final project: Building and deploying an AI-enhanced full-stack web application.
- Peer review and evaluation of AI implementations.
- Course recap & final Q&A session.
- Certification and career guidance for AI-powered full-stack development.
Morning and evening classes are available. CompuBase Training Center, Abu Dhabi.
