Navigating the Stock Market: A Practical Guide for Buying, Selling, and AI Risk Management

  Stock Market Trading & AI Risk Management.
This practical course teaches you how to confidently buy and sell stocks while responsibly integrating AI-enabled tools to identify opportunities and manage risk. Use this crisp introduction as a meta description: “Stock Market Trading & AI Risk Management — practical strategies for buying, selling, and safely using AI in trading.”

Course Overview

“Navigating the Stock Market” is a hands-on course that blends core investing fundamentals with modern algorithmic and AI-aware risk controls.
Over multiple modules you’ll learn market structure, order types, technical & fundamental analysis, position sizing, trade management, and how to evaluate and safely apply AI models and signal systems without overfitting or taking excessive model risk.

Who Should Enroll?

• Beginner to intermediate traders who want a structured path from basics to live-trading readiness.
• Investors curious about algorithmic/AI tools and the practical limits of AI in trading.
• Finance professionals seeking better frameworks for risk management when using predictive models.

Learning Outcomes

1. Explain market mechanics, order types, and liquidity concepts required for safe trading.
2. Perform basic fundamental and technical analysis to locate high-probability trade ideas.
3. Design and implement position sizing and stop-loss strategies to protect capital.
4. Assess AI models: understand bias, overfitting, backtest pitfalls, and production risk controls.
5. Integrate AI signals with human oversight and build a reproducible, auditable trade process.

Course Modules & Syllabus (Detailed)

• Module 1 — Market Foundations: Exchanges, tickers, spreads, order types, reading level 1 & 2 market data.
• Module 2 — Fundamental Analysis: Financial statements, valuation basics, news impact and event-driven trading.
• Module 3 — Technical Analysis: Trend identification, support/resistance, indicators, chart patterns, and entry/exit rules.
• Module 4 — Trade & Risk Management: Position sizing, stop placement, portfolio construction, daily risk limits.
• Module 5 — Algorithmic Trading Basics: Backtesting best practices, slippage, transaction cost modelling.
• Module 6 — AI Risk Management: Understanding model risk, validation, monitoring, explainability, and safe deployment of signals.
• Module 7 — Live Simulation & Case Studies: Practical simulated trades, post-trade review, journaling, and improvement loops.

Teaching Methods & Resources

The course uses short lectures, guided hands-on labs, download