Real Estate
How the real-estate business works, and the finance, marketing, data and AI that run it.
Real estate is where finance meets physical space: valued on income and yield, financed with leverage, and sensitive to rates and location. This vertical gives you the big picture, then finance, marketing, data and AI applied inside it.
Key terms
Why specialize in Real Estate?
Cross-cutting skills are not enough in the Real Estate sector. It plays by its own rules: a distinct value chain, specific players and balance of power, dense regulation, and key figures you won't find anywhere else. This vertical gives you that sector fluency — first the big picture, then finance, marketing, data and AI applied concretely to Real Estate, with the calculations, benchmarks and checklists you actually need on the ground.
What you'll be able to do
- Understand how the Real Estate sector works: value chain, key players and balance of power
- Know the major regulations and laws, the sector's acronyms and vocabulary
- Run the key calculations and read the benchmarks specific to Real Estate (US and Europe markets)
- Apply finance, marketing, data and AI to the realities of Real Estate
- Gauge your level with 5 sector assessments and a competency radar
70 lessons across 16 modules and 5 blocks, with a test per lens and a sector competency radar. Free to read — no account required.
Curriculum
Real Estate: how the sector works
Generalhow real estate works: the asset classes (residential, commercial, industrial), the value chain from development to operation, and why location and cycles dominate.
4 Modules · 18 Lessons
Finance in real estate
Financereal-estate finance: valuation by cap rate and NOI, leverage and debt structures, cash flow and the impact of interest rates, and development risk.
3 Modules · 13 Lessons
Marketing in real estate
Marketingreal-estate marketing: listing and leasing, tenant and buyer acquisition, brand for developers and brokers, and place-making.
3 Modules · 13 Lessons
Data in real estate
Datareal-estate data: property and market data, valuation models, occupancy and building-performance data, and portfolio analytics.
3 Modules · 13 Lessons
AI in real estate
AIAI in real estate: automated valuation, demand and pricing, building operations and energy, and deal sourcing.
3 Modules · 13 Lessons