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Full-Stack Backend Python with
AI & ML Roadmap

Turning Data into Decisions - Python & AI/ML Training from Basics to Deployment

Course Schedule

Duration Modules Covered Hours per day
3 Months
(360 hours approx.)		 All 17 Modules 4 Hours

Modules

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  • Python introduction & environment setup
  • Setup AI IDEs (Cursor, Anti-gravity, Stitch)
  • Variables, keywords, data types
  • AI-assisted code writing & debugging
  • Prompt-driven Python basics
  • Conditional statements
  • Loops and iterations
  • AI-assisted problem solving
  • Pattern and number problems
  • Logic building with AI suggestions
  • User-defined functions
  • Arguments and return values
  • Lambda functions
  • AI-based code refactoring
  • Reusable Python modules
  • Classes and objects
  • Constructors and methods
  • Inheritance & polymorphism
  • OOPS in real-world AI projects
  • AI-assisted architecture design
  • File read/write operations
  • CSV and text file handling
  • Exception handling
  • AI debugging for runtime errors
  • NumPy fundamentals
  • Pandas for data analysis
  • Matplotlib for visualization
  • AI-assisted data cleaning workflows
  • PostgreSQL with Python
  • CRUD operations
  • Python database connectors
  • AI-assisted query optimization
  • Django setup & architecture
  • Models, views, templates
  • Forms & authentication
  • AI-assisted web app development
  • Django REST Framework
  • Serializers & API views
  • Authentication & permissions
  • AI-assisted API performance optimization
  • FastAPI introduction
  • Async APIs & routing
  • JWT authentication
  • AI-assisted deployment practices
  • AI vs ML vs Deep Learning
  • Real-world AI use cases
  • AI-assisted coding workflows
  • Supervised vs Unsupervised learning
  • Regression & classification
  • Model training & validation
  • Scikit-learn introduction
  • Regression & classification models
  • AI-accelerated ML implementation
  • Data normalization
  • Model evaluation metrics
  • AI-assisted performance tuning
  • Student performance prediction
  • Spam detection system
  • Sales forecasting model
  • Integrating ML with Django
  • Deploying via FastAPI
  • API-based prediction systems
  • Industry-relevant live project
  • End-to-end AI solution building
  • Portfolio creation for interviews
  • Certificate completion
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Enroll in AI-Driven MERN or Python/ML Training and
start building real-world projects using AI IDEs.

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