Course Content
This session offers the essential knowledge of what AI is and how it operates, tailored for real estate professionals eager to incorporate AI into their business practices. It is designed to be accessible to everyone, irrespective of technical background, providing a necessary foundation for all subsequent sessions and future independent work with AI. More specifically, the session covers:
- An accessible overview of artificial intelligence, with a particular focus on conversational AI and advanced language models like GPT-4.
- The distinction between AI and traditional software, highlighting AI's ability to derive rules from objectives, in contrast to the predefined rules in conventional software.
- The inner workings of neural networks, the AI learning process, and text understanding through techniques such as tokenization, embedding, and self-attention.
- Strategies for minimizing AI output errors, effective prompting techniques, and an overview of the top AI products.
The session follows an office market research project to explain and demonstrate key skills for leveraging AI in handling documents and reports such as:
- prompt engineering
- AI-powered searching
- critical thinking with AI
- insights and recommendations with AI
- limitations of AI in working with text
It delves into AI's capability in enhancing document analysis, underscoring the significance of context in communication and the development of effective AI prompting strategies.
The session highlights the crucial role of AI in synthesizing vast amounts of market data, drawing objective, context-aware conclusions. It stresses the importance for real estate professionals to not only understand but also effectively utilize these advanced tools for gaining competitive insights.
The session introduces using generative AI in business analysis, in the real estate sector.
It starts by covering the integration of qualitative information in analysis, outlining the benefits and challenges of using qualitative data and how generative AI can enhance precision and speed in this context.
Then, it delves into the creation of strategies with AI assistance, highlighting steps like setting context, defining problems, specifying tasks, and prompt generation for effective strategy formulation.
It considers two key case studies: using AI as a tool to execute strategy generation and using AI as a consultant to develop a complete strategy for a specific problem.
Next, the session explores the application of AI in mathematical operations, contrasting the capabilities of Excel and large language models (LLMs) in handling mathematical tasks.
Finally, it progresses to practical aspects of strategic real estate analysis, like simple valuation, sensitivity analysis, and Monte Carlo Analysis, demonstrating how these can be approached using gen AI. It concludes with a case study on forecasting and building custom models using AI.
This session presents AI capabilities to write and execute code from natural language prompts using the example of creating data visualizations relevant to real estate professionals. In particular, it covers:
- Basic data processing and analysis tasks using real data and how to turn it into an advanced analysis by entering the right prompts.
- Creation, customization, and analysis of diverse chart types, including bar charts, pie charts, and time series plots, all made accessible through natural language commands.
- How to effortlessly generate maps with your own data, regardless of technical skills or background.
- Animated visualizations of graphs and maps, adding an engaging dimension to data presentation.
- Development of interactive visualizations such as dynamic dashboards or even interactive maps.
Key takeaways include the ability to handle diverse data types, the use of AI to interpret code and generate visuals, and techniques for creating compelling, interactive data presentations.
The session consists of three diverse presentations that delve into advanced aspects of AI and its practical applications in real estate.
First, Monika offers a deeper insight into the philosophical and technical intricacies of AI, discussing future trends, ethical considerations, and the impact of AI on the workforce.
Second, Thomas provides a more hands-on approach, detailing how AI can be pragmatically implemented in business operations, with a focus on efficiency and innovation.
Third, Niko concentrates on the practical aspects of integrating AI into businesses, particularly emphasizing the skills required for successful adoption and the transformation of job roles in an AI-driven corporate landscape.
Together, these lectures provide a comprehensive understanding of AI's potential, challenges, and the evolving dynamics of its integration into various industries.
