This course develops the core skills required for valuation and investment analysis in corporate finance and capital markets. You will learn how to value businesses, projects, and financial assets using both intrinsic valuation and relative valuation approaches. The course begins with the time value of money, discounted cash flow (DCF) modeling, and the estimation of free cash flow, WACC, and terminal value. It then examines market-based methods, including EV/EBITDA, P/E ratios, comparables analysis, and precedent transactions.

Valuation and Investment Analysis

Recommended experience
What you'll learn
Apply time value of money and discounted cash flow techniques to value projects and companies.
Use relative valuation methods such as market multiples and comparables analysis.
Interpret valuation results in the context of investment decisions and market expectations.
Skills you'll gain
- Responsible AI
- Cash Flows
- Risk Analysis
- Simulation and Simulation Software
- Investment Management
- Data-Driven Decision-Making
- Capital Budgeting
- Financial Forecasting
- Business Valuation
- Excel Formulas
- Financial Systems
- Cash Flow Forecasting
- Financial Analysis
- Corporate Finance
- Accounting
- Financial Modeling
- AI Enablement
Tools you'll learn
Details to know

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3 assignments
March 2026
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There are 3 modules in this course
This module lays the groundwork for all valuation techniques by focusing on the time value of money. Learners will explore present value, future value, annuities, and discounting methods. The goal is to develop comfort with applying basic financial math to solve real-world problems involving cash flows, rates of return, and opportunity cost.
What's included
11 videos2 readings1 assignment1 peer review1 discussion prompt
This module introduces the most commonly used valuation models: the Discounted Cash Flow (DCF) model and relative valuation using multiples. Students will learn how to construct a DCF model using forecasted free cash flows and terminal value, and how to derive firm value using comparables like EV/EBITDA and P/E ratios. Emphasis is placed on understanding each method’s assumptions and limitations, and when to use each in real-world scenarios.
What's included
10 videos1 reading1 assignment1 peer review1 discussion prompt
This module explores how artificial intelligence is transforming financial modeling, from automating data gathering and cleaning to generating forecasts and stress-test scenarios. Learners will gain a practical understanding of AI tools available to finance professionals, learn how to apply them in model building, and understand the governance, validation, and risk considerations necessary for reliable results. By the end of this module, participants will be equipped to integrate AI into their workflows effectively while avoiding common pitfalls.
What's included
11 videos1 reading1 assignment2 peer reviews1 discussion prompt
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