8 Sections
47 Lessons
12 Weeks
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Orientation
Welcome
3
1.1
Program overview and learning roadmap
1.2
Tools setup: Python, VS Code, Git, cloud accounts
1.3
Meet your mentors and cohort members
Fundamentals of Programming using Python
Python syntax, variables, data types & operators
5
2.1
Control flow: loops, conditionals, functions
60 Minutes
2.2
OOP: classes, inheritance, polymorphism
60 Minutes
2.3
File handling, error handling & modules
2.4
Advanced: decorators, generators, comprehensions
2.5
Projects: mini automation scripts
Introduction to DBMS -SQL/NO SQL
6
3.1
Relational DB concepts: tables, keys, normalization
3.2
SQL: SELECT, JOIN, GROUP BY, subqueries, indexing
3.3
MySQL & PostgreSQL hands-on practice
3.4
NoSQL fundamentals: document, key-value, graph
3.5
MongoDB: CRUD, aggregation pipeline, indexing
3.6
Connecting databases with Python (SQLAlchemy, PyMongo)
Web Design with HTML ,CSS ,Java Script ,Boot Strap, Tailwind
6
4.1
HTML5 semantics, forms, accessibility
4.2
CSS3: Flexbox, Grid, animations, responsive design
4.3
JavaScript: DOM, events, fetch API, ES6+
4.4
Bootstrap: components, grid system, utilities
4.5
Tailwind CSS: utility-first design, custom themes
4.6
Project: responsive multi-page website
Djago-Python Web Framework , REST API , Fast Cloud
6
5.1
Django MVT architecture, models, views, templates
5.2
Django ORM, authentication, admin panel
5.3
Django REST Framework: serializers, viewsets
5.4
FastAPI: async endpoints, Pydantic schemas, docs
5.5
JWT authentication & API security
5.6
Cloud deployment: AWS / GCP / Azure, Docker basics
Statistics, Data Science & ML
7
6.1
Statistics: descriptive, probability, hypothesis testing
6.2
NumPy & Pandas: data wrangling and analysis
6.3
Data visualization: Matplotlib, Seaborn, Plotly
6.4
ML algorithms: regression, classification, clustering
6.5
Scikit-learn: model building, evaluation, pipelines
6.6
Feature engineering, cross-validation, hyperparameter tuning
6.7
Projects: EDA, predictive modeling, recommendation system
Deep Learning & GEN AI -LLMs, Agentic AI
9
7.1
Neural networks: architecture, backpropagation, activation
7.2
CNNs for image classification & object detection
7.3
RNNs, LSTMs & sequence modeling
7.4
TensorFlow & PyTorch hands-on training
7.5
Transformers, BERT, GPT architecture deep-dive
7.6
LLMs: OpenAI API, prompt engineering, fine-tuning
7.7
LangChain, Hugging Face, RAG systems
7.8
Agentic AI: autonomous agents, tool use, multi-agent systems
7.9
Projects: chatbot, image classifier, AI content generator
Final Project
5
8.1
Choose a real-world problem spanning web + AI domains
8.2
Full product development lifecycle: ideation to deployment
8.3
Mentor-guided weekly reviews and feedback
8.4
Build and present your portfolio project
8.5
Demo day presentation to industry panel
Python Full Stack with Gen AI & Agentic AI
Curriculum
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