This course is designed for developers and traders who are interested in creating a customized trading terminal from scratch using Python. Participants will leverage modern technologies like Python Flask, Tailwind CSS, AlpineJS, Daisy UI, SQLite, Brokers REST API, Websockets, ChatGPT, and Claude Sonnet 3.5. We will cover the entire process of building, deploying, and scaling a trading terminal on platforms like Amazon AWS and Digital Ocean.
By the end of the course, participants will be proficient in building real-time watchlists, placing various types of orders, and integrating broker APIs. They will also implement complex features like trailing stop loss orders, MTM-based square-offs, voice, and keyboard-based orders.
When : starting from 7th Oct 2024 , 7p.m – 9p.m (Weekdays)
Total Training Sessions: 18 Sessions
Total Training Hours : 36+ hours
Customer Support: +91 9535133445
Components Used:
- Backend: Python Flask
- Frontend: Tailwind CSS, AlpineJS, Daisy UI
- Database: SQLite DB
- Broker Integration: REST API & Websockets (Indian Brokers)
- AI Integration: ChatGPT & Claude Sonnet 3.5
- Hosting: Amazon AWS/Digital Ocean
Key Learning Outcomes:
- Prompting Techniques for AI-Powered Trading Terminal
- Mastering Web Technologies: REST API, WebSockets, and Webhook integration
- Modular Coding Solutions: Organizing the terminal into reusable and maintainable components
- Troubleshooting Complex Systems
- Building Real-Time Features:
- Watchlists
- Regular, Bracket, Cover Orders
- Split Orders
- Voice & Keyboard-Based Scalping Orders
- Building Advanced Trading Features:
- AutoStopLoss Orders
- OrderBook, TradeBook, PositionBook, and Holdings from scratch
- Broker Authorization and Time-Based AutoSquareoff
- Implementing Trailing Stoploss Orders & Positional MTM Square off
- Visualizing Real-Time MTM with Charts
What Traders Will Get at the End of the Course:
- Fully Functional Trading Terminal:
- Traders will walk away with a fully functional trading terminal that they can customize and extend according to their needs.
- The terminal will include real-time watchlists, the ability to place different types of orders (Regular, Bracket, Cover, etc.), and advanced order management features like Trailing Stop Loss and AutoSquareoff.
- Source Code and Templates:
- Participants will receive all the source code for the trading terminal, organized into modular and reusable components.
- Prebuilt templates for key terminal features like watchlists, order placement, and chart visualization will be provided for customization.
- AI-Powered Enhancements:
- Integration of ChatGPT and Claude Sonnet 3.5 for AI-powered trading terminal enhancements, including voice and keyboard-based trading commands.
- Trading API Implementation:
- Working examples of broker authorization, secure login, and the complete integration of REST API and WebSockets with real broker accounts.
- Deployment and Hosting:
- Step-by-step guidance on how to deploy the trading terminal on cloud platforms like Amazon AWS and Digital Ocean, including best practices for scaling and maintaining the application in a production environment.
- Comprehensive Documentation:
- Each participant will receive a comprehensive set of documentation covering every part of the development process, from setting up the development environment to deploying the final product.
- Support Materials:
- Cheat sheets for working with key technologies such as Flask, Tailwind CSS, Websockets, and SQLite.
- Code snippets for handling real-time data, API requests, and troubleshooting common issues.
- 1 Year Recorded Access to Course Materials:
- Participants will retain 1 Year of Recorded access to course videos, project source code, and supporting materials for future reference.
Course Flow:
- Week 1: Introduction to the tech stack and setting up the environment. Build the front and backend skeleton of the trading terminal.
- Week 2: Focus on building real-time features like watchlists and placing various types of orders. Explore AI-powered voice and keyboard commands for order placement.
- Week 3: Advanced features like Trailing StopLoss, MTM-based SquareOff, and AutoSquareoff. Create visual representations using MTM charts.
- Week 4: Learn to deploy the terminal on cloud platforms like AWS and DigitalOcean, troubleshoot real-world issues, and finalize the terminal.
Prerequisites:
- Familiarity with Python
- Basic knowledge of HTML, CSS, and JavaScript will be an added advantage
- Understanding of trading and basic market orders
