Foundations of Markets and AI

This unit introduces core stock market concepts alongside foundational artificial intelligence principles, covering market mechanics, AI capabilities, typical AI processes, and emerging algorithms. Students will build the conceptual bridge necessary to evaluate and plan AI-driven approaches for investment analytics in later units.

Learning Objectives

• Analyze core stock market concepts (securities, market participants, order types, indices) and interpret basic price and volume charts to inform introductory investment decisions
• Demonstrate foundational understanding of artificial intelligence by describing its capabilities, common workflows (data collection, model training, validation), and distinctions from traditional rule-based systems
• Evaluate emerging AI algorithms and model types (e.g., supervised/unsupervised learning, reinforcement learning, deep learning, large language models) for their strengths, limitations, and data requirements in investment analytics contexts
• Apply foundational knowledge to design a simple AI-driven investment analysis plan that maps a market question to data sources, preprocessing steps, an appropriate algorithmic approach, and basic ethical/accuracy considerations