Python Full Stack Engineering with Generative AI
Build data-driven web apps and AI agents with Python, FastAPI, Django, React, and LangChain.
Curriculum Preview & Board Review Status
This program is currently in preview status. Syllabus modules and delivery schedules are undergoing curriculum committee review. Submit your enquiry to express interest and receive preview materials.
Program Overview
A fast-paced, practical curriculum centered on modern Python engineering. You will master Python data structures, asynchronous FastAPI microservices, Django ORM, React frontend integration, and advanced Generative AI architectures including autonomous agents, LangChain, and vector embeddings.
Key Skills & Stack Practiced
Intended Audience
- Students seeking final-year engineering projects in AI, Machine Learning, and Full Stack Python
- Developers looking to modernize their stack with FastAPI, LangChain, and React
- Data and engineering aspirants wanting production web skills alongside AI models
Prerequisites
- Familiarity with basic programming fundamentals
- Laptop with minimum 8GB RAM
- Enthusiasm for building real-world AI applications
Structured Phase-by-Phase Syllabus
Each phase introduces core engineering abstractions with hands-on exercises and milestone deliverables.
Python 3.12 Mastery & Asynchronous Programming
Deep dive into Python syntax, data structures, generators, decorators, and modern asynchronous concurrency with asyncio.
Core Topics
- Python 3.12 features: Type Annotations, Pattern Matching, Exception Groups
- Advanced Python: Decorators, Context Managers, Generators, Metaclasses
- Asynchronous Programming with Asyncio, Coroutines, and Event Loops
- Testing with PyTest, Mocks, and Automated CI/CD Linting
Hands-on Exercises
- Build an asynchronous concurrent web crawler and price monitor with aiohttp
- Implement custom decorators for execution timing, caching, and rate limiting
Learning Outcomes
- Write clean, highly performant asynchronous Python code
- Master Python typing and modern package tooling
Basic logic and high-school mathematics
Deep dive into Python syntax, data structures, generators, decorators, and modern asynchronous concurrency with asyncio.
- •Python 3.12 features: Type Annotations, Pattern Matching, Exception Groups
- •Advanced Python: Decorators, Context Managers, Generators, Metaclasses
- •Asynchronous Programming with Asyncio, Coroutines, and Event Loops
- •Testing with PyTest, Mocks, and Automated CI/CD Linting
- •Build an asynchronous concurrent web crawler and price monitor with aiohttp
- •Implement custom decorators for execution timing, caching, and rate limiting
How You Build Your Capstone Project
Explore how the flagship project matures from system design to full stack deployment and Viva examination defense.
ResearchAssist: Multimodal Academic Paper Analysis with AI
A full-stack academic document intelligence portal featuring FastAPI, React, vector search, and automated citation verification.
Data Pipeline & Document Processing Engine
What Changes in this Phase
Builds asynchronous PDF parser, text chunker, and token counter in Python.
Features Implemented
- •PDF upload parser
- •Semantic chunking pipeline
- •Metadata extractor
Skills Practiced
Milestone Deliverables
- •Python Document Ingestion Package
- •Unit Test Suite
- Q1:Why is recursive character text chunking preferred over fixed-length slicing for academic papers?
- Q2:How do token limits impact LLM context window cost and latency?
Builds asynchronous PDF parser, text chunker, and token counter in Python.
Deploys FastAPI application with Pydantic validation, ChromaDB embeddings, and JWT auth.
Builds React user interface with PDF split-screen viewer and synchronized citation highlights.
Adds LangChain agent capable of web search verification, bibliography formatting, and export.
Try a Coding Concept
Test core programming mechanics right in your browser through safe client-side simulations.
Deterministic educational demonstration — safe client-side preview
public class Main {
public static void main(String[] args) {
String studentName = "Priya";
int semester = 8;
System.out.println("Welcome to CodeMyFYP Project Studio!");
System.out.println("Candidate: " + studentName + " | Final Semester: " + semester);
}
}Click "Run Demonstration" to inspect output.
Outputs are calculated deterministically for study.
What Support is Included
We focus on genuine learning, deep code comprehension, and academic rigor.
1-on-1 Code Reviews
Direct feedback on your Git pull requests. Line-by-line inspection of code quality, architecture patterns, and naming conventions.
Viva & Interview Defense
Mock technical interviews and Viva cross-examination sessions ensuring you can confidently explain every architectural choice.
IEEE Report Documentation
Complete documentation templates conforming to university standards, including UML diagrams, ER schemas, and testing logs.
Program Details & Queries
How does this Python track differ from basic data science courses?
Most data science courses stop at Jupyter notebooks. This program teaches full-stack software engineering: building real web APIs (FastAPI), managing databases (PostgreSQL), building user interfaces (React), and deploying production AI systems in Docker.
Can this program serve as my college Final Year Project?
Yes. The capstone project is specifically structured to exceed university final-year project requirements for B.Tech, B.E., and MCA degrees, complete with SRS, architecture diagrams, and Viva defense questions.
What hardware or cloud accounts do I need?
A modern laptop with at least 8GB RAM is required. For AI models, we teach both local models (Ollama) and cloud APIs (OpenAI) with strict cost-control practices.
Interested in Python Full Stack Engineering with Generative AI?
Submit your enquiry to receive syllabus updates, batch schedules, and preview materials as soon as they are approved.
Zero obligation • Direct technical conversation with engineers • NDA upon request