Designing a Stock Market App using Python is a hands-on course that guides you through the development of a functional stock market application. Over four engaging sessions, you’ll learn to fetch and display stock data, create dynamic visualizations, and implement advanced features such as user authentication and notifications. By the end of the course, you’ll be equipped with the skills to build and deploy your own stock market app, gaining a comprehensive understanding of both Python programming and web development.
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Session 1: Introduction and Setting Up
- Overview of stock market data: types and sources
- Introduction to essential tools and libraries: pandas, yfinance, Flask, SQLite
- Setting up the development environment: installing Python, libraries, and creating a virtual environment
- Introduction to GPT-4 for enhancing app functionalities
Session 2: Fetching and Displaying Stock Market Data
- Fetching stock market data using yfinance and requests
- Building a Flask application: creating routes and rendering templates
- Storing stock data in an SQLite database
- Displaying stock data in a web application using Jinja2 templates
Session 3: Data Visualization and Analysis
- Introduction to data visualization with Matplotlib and Plotly
- Creating visualizations of stock data , creating custom indicators
- Basic stock data analysis: calculating and displaying technical indicators.
- Storing and retrieving stock market data in SQLite
- Using GPT-4 for enhanced data insights and analysis suggestions
Session 4: Building Advanced Features and Deployment
- Implementing user authentication with Flask-Login
- Storing user data and preferences in SQLite
- Adding features for tracking favorite stocks and setting up email notifications
- Using GPT-4 to provide personalized insights and notifications to users
- Deploying the Flask app to a cloud platform (Amazon Beanstalk, Vercel, Digital Ocean etc) and setting up a custom domain.
This course provides a comprehensive guide to developing a stock market app from scratch, integrating SQLite for data storage, and leveraging GPT-4 for advanced functionalities, covering everything from fetching and displaying data to advanced features and deployment.
