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Learn to build a voice assistant using OpenAI's ChatGPT and Whisper APIs with Python and Gradio. Create an interactive system that converts speech to text, processes it, and responds audibly.
Learn prompt engineering techniques for financial NLP tasks using GPT-3, including data extraction, entity recognition, and sentiment analysis. Gain practical skills for structured output and text classification.
Master building an AI prediction market assistant using Python, integrating Kalshi API for market odds and Perplexity Sonar API for analysis, with a Streamlit interface for automated trading decisions.
Master Robinhood's official crypto API with Python, from setting up keys and retrieving account info to placing orders and analyzing trading history.
Master structured data extraction from various financial media using Google's Gemini 2.0 Flash and Python SDK 1.0. Extract insights from PDFs, podcasts, images, and videos through practical demonstrations.
Master the creation of AI trading agents using Browser Use to automate stock research, scanning, and trading through Interactive Brokers while integrating with financial tools and social platforms.
Explore a detailed comparison of OpenAI and Gemini's deep research capabilities through a practical analysis of private SaaS companies, revealing key differences in report quality, prediction accuracy, and analytical depth.
Explore how to use Gemini API to extract and analyze financial predictions from YouTube videos, using Python and Yahoo Finance data to evaluate their accuracy over time.
Explore the capabilities and security implications of OpenAI's Operator for SaaS automation, including practical demonstrations of automated tasks, potential risks, and future applications in business workflows.
Explore how to automate financial transcript retrieval using OpenAI Operator, from initial setup to successful file transfers, while understanding its capabilities and limitations in handling automated tasks.
Learn to analyze financial news using OpenAI and Llama Index. Build a system to fetch, index, and query news data, with a focus on practical implementation and code walkthrough.
Learn to use Kalshi's API for prediction markets in Python. Explore data collection, pandas integration, and real-time websocket functionality. Gain insights into market comparisons and semantic bet matching.
Learn to analyze prediction market data using Python and the Polymarket API, covering REST API for event and market data, as well as websockets for real-time streaming.
Explore OpenAI API's Structured Outputs feature for finance applications, including extracting company lists and using Pydantic models for efficient data handling.
Build a financial news app UI with Streamlit, integrating GPT-4 and Llama-Index for advanced analysis and user-friendly interaction. Learn to create a powerful tool for financial insights.
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