Trending Stocks with Python, Reddit, Twitter, and ChatGPT
What you'll learn
- Learn how to use Python and PRAW to collect and analyze data from Reddit posts
- Explore the power of the Twitter API to gather real-time data on trending stocks
- Discover how to leverage the power of ChatGPT to summarize large volumes of comments and extract valuable insights on trending stocks.
- Develop practical skills in logging and debugging code, and learn how to store logs in AWS S3 to ensure smooth operation and ease of use
- Learn how to set up an automated email system with email templates in Python
- Some development experience, but it doesn't necessarily have to be Python experience.
- An OpenAI API Key
In this comprehensive hands-on course, you'll delve into the world of stock analysis using Python, PRAW, Twitter API, and ChatGPT. You'll focus on leveraging social media data to identify trending stocks and extract valuable insights. By combining the power of Python with the real-time information from Twitter and Reddit, you'll gain a competitive edge in analyzing market trends.
First, you'll dive into analyzing Reddit data using PRAW (Python Reddit API Wrapper). Learn to extract stock-related comments from popular subreddits, identify stock tickers mentioned, and capture key sentiment indicators from the discussions. You'll gain insights into market sentiment and community perceptions, uncovering trends that can influence investment decisions.
Next, you'll learn how to gather data from Twitter using the Twitter API. Discover techniques to retrieve tweets related to stocks, and filter for the tweets that you want. Uncover the valuable information hidden within the vast sea of social media posts.
To distill the vast amount of information, you'll employ ChatGPT, an advanced language model from OpenAI. You'll harness the power of natural language processing (NLP) to generate concise summaries of the stock-related comments collected from Twitter and Reddit. Discover how to fine-tune ChatGPT for better performance in summarizing financial discussions, enabling you to capture the essence of the conversations effectively.
With the summarized insights in hand, you'll create customizable email reports to deliver the most relevant and up-to-date information to yourself or your subscribers. Utilizing SMTP and MIME in Python, you'll automate the process of sending the reports with a professional touch. You'll explore techniques for template customization, email variable handling, and error handling to ensure smooth delivery of the reports.
Throughout the course, you'll gain practical skills that extend beyond stock analysis. You'll learn to work with APIs, handle data collection and preprocessing, implement NLP techniques, and develop automated systems. These skills can be applied to various real-world scenarios in finance, technology, and data analysis.
By the end of the course, you'll be well-equipped to analyze trending stocks by leveraging the power of Python, PRAW, Twitter API, and ChatGPT. You'll have the ability to gather and process data from Twitter and Reddit, extract valuable insights, generate summarized reports, and automate the delivery process. Prepare to make informed investment decisions and uncover hidden opportunities in the dynamic world of stock market analysis.
Who this course is for:
- Developers and programming enthusiasts who are interested in learning about Python programming, natural language processing, and API integration
- Traders, investors, and finance professionals who want to leverage AI-powered tools and social media data to gain valuable insights into trending stocks and make informed investment decisions.
- Data analysts and researchers who are interested in exploring the application of Python and AI techniques in the field of finance and stock market analysis.
Hey there, I'm Steve! I've been a Salesforce Developer for almost a decade now, and I've recently become fascinated with Python programming. I discovered my passion for the stock market and wanted to automate the collection and analysis of stock market data. That's how I came up with the idea for FinancialPython, an online resource for learning about Python and finance.