This section provides an overview of stock market analytics, emphasizing its role in investment decision-making. Topics include the types of analysis (fundamental, technical, quantitative), key metrics, and the importance of data-driven strategies.

Participants learn about data sources in the stock market, including historical price data, financial statements, and market indicators. Techniques for cleaning, preprocessing, and organizing data for analysis are covered, ensuring accuracy and reliability.

Statistical tools and techniques for analyzing stock market data are discussed, including measures of central tendency, volatility, and correlation. Participants explore predictive modeling methods such as time series analysis and machine learning for forecasting stock prices and trends.

This section focuses on technical analysis techniques, including chart patterns, indicators, and trend analysis. Participants learn how to develop and backtest trading strategies based on technical signals and market patterns.

Risk management principles for investing in the stock market are introduced, covering concepts such as diversification, asset allocation, and risk-adjusted returns. Portfolio optimization techniques, including modern portfolio theory and risk parity, are discussed to help participants build balanced and efficient investment portfolios.