Overview of Stock Screener Using AI

Understand what a stock screener is, how traditional screeners work, and why AI is changing the way stocks are filtered, analysed, and shortlisted especially in fast-moving markets.

Learn the basics of stock market data such as price (OHLC), volume, indicators, and fundamentals, and how AI interprets this data differently from rule-based screeners.

Get introduced to AI and machine learning concepts relevant to investing, along with clear limitations, risks, and SEBI-aligned compliance reminders for responsible usage.

Master the art of writing clear, structured prompts for AI-based stock screening. Learn to combine prices, indicators, fundamentals, and constraints without vague or misleading queries.

Use global AI tools like ChatGPT, Gemini, and Copilot, along with India-focused platforms such as Screener.in and Tickertape, to generate actionable screening outputs.

Understand how AI can be used for sentiment analysis, news-based screening, and adaptive screening logic while recognising false positives and overfitting risks.

Explore how to backtest AI-generated ideas, optimise screening accuracy, and turn raw outputs into repeatable, usable screening frameworks.

See real Indian market case studies, including AI-based screening of Nifty stocks using rule-based constraints and practical lessons from failures and successes.

By the end of this course, you’ll be able to use AI as a structured screening assistant supporting your decisions with logic, clarity, and discipline, not shortcuts or hype.