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AI-Powered Django – Basic Course

The core of this course is to train learners to build secure, scalable web applications using Django and AI-assisted development tools. All enrolled candidates can learn backend architecture, API integration, and intelligent coding practices that improve the development cycles.

Why Choose Cronus Consultants to Learn the AI-integrated Django Course?

At Cronus Consultants, mentors guide candidates in building robust backend systems using Django, integrated with AI-assisted development. Learners are trained in hands-on coding, receive architecture guidance, and participate in real-world projects to build technical confidence and achieve their professional development goals.

Curriculum Overview

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Python Programming Fundamentals: Covers core Python concepts, data structures, and object-oriented programming (OOP).
Web Fundamentals: Introduction to HTML, CSS, JavaScript, and HTTP protocols.
Version Control: Basic use of Git and GitHub for project management.

Project and App Structure: Setting up the development environment, virtual environments, and understanding Django's architecture (MVC/MTV).
Models, Databases, and ORM: Creating models, performing database migrations, and interacting with data using Django's Object-Relational Mapper (ORM) and SQLite/PostgreSQL.
Views and URLs: Defining application logic in views and mapping them to specific URLs.
Templates and Static Files: Rendering HTML using Django templates, managing static CSS/JS files, and using template inheritance.
Admin Interface: Customizing and utilizing the built-in Django admin panel for managing data.
Forms and User Authentication: Handling user input with Django forms and implementing authentication systems (login/logout, user roles).

AI-Powered Development Tools: Using AI assistants like GitHub Copilot or Claude AI for code generation, debugging, and explaining errors.
Integrating AI Functionality: Learning how to integrate external AI APIs (e.g., OpenAI APIs) into a Django application.
Building AI Features: Topics might include basic implementations of AI features like search functionality or data analysis with libraries such as NumPy and Pandas.