Build practical financial analysis and modeling skills used by analysts and finance professionals to evaluate business performance and support better decisions.
By Board Infinity · Offered on Coursera
Enrollment figure as published on the Coursera course page.
41 lessons that build models, not just explain them
Issued through Coursera, one click onto LinkedIn
17 assignments across the four modules
Four modules that move from reading the three statements, to diagnosing performance, to building models that answer a question someone actually asked.
Master Financial Analysis & Modeling Fundamentals walks you through financial statements, ratio analysis, forecasting and valuation, helping you convert raw numbers into clear insights. You learn how income statements, balance sheets and cash flow statements connect, and how to assess profitability, liquidity, efficiency and leverage.
From there you apply ratio analysis and DuPont decomposition to identify performance drivers and working capital efficiency. You build integrated financial models in Excel or Google Sheets, run scenario and sensitivity analysis, and apply valuation methods like DCF and comparables.
The last module covers forecasting and budgeting techniques - SMA, EMA, rolling forecasts and variance analysis - and uses Excel, Sheets and Python to automate the work. Throughout, the emphasis is on hands-on modeling and business interpretation, so you understand what the numbers mean.
Coursera positions this course for finance roles and students - and it stays accessible if you have never built a model before.
Build practical financial analysis and modeling skills used in analyst workflows, from statement analysis through to valuation.
Strengthen forecasting, budgeting, variance analysis and financial modeling capabilities you already use day to day.
Develop practical skills for interpreting financial statements, ratios, valuation and financial models alongside your coursework.
Build a structured foundation in financial analysis and modeling rather than assembling it from scattered sources.
Strengthen financial modeling and analytical skills, and put a repeatable structure behind work you are already doing.
Coursera lists this course as accessible to product managers, entrepreneurs and operations professionals who need to read financials well.
Each one is the foundation for the next: you cannot diagnose performance without reading the statements, and you cannot model without both.
Understand income statements, balance sheets and cash flow statements, how they link, and how to use them to evaluate financial health - including the red flags that show up in real reporting.
Apply profitability, liquidity, leverage and efficiency ratios, DuPont decomposition, working capital analysis and the cash conversion cycle - then explain the result to a decision-maker.
Link the three statements into one integrated model, design base, bull and bear scenarios, run sensitivity and tornado analysis, and apply DCF and comparable-company valuation.
Build budgets and rolling forecasts, apply SMA and EMA, evaluate accuracy with MAPE and RMSE, and automate the workflow using Excel, Google Sheets and Python (pandas).
These four build toward the specialization's stated outcomes: designing financial workflows that integrate analytics, ML and AI; evaluating company performance with analysis, forecasting and valuation frameworks; building predictive models; and creating automated dashboards and reports. This first course covers the financial analysis, modeling, forecasting and valuation foundation - the later courses take on the ML and dashboard work.
A dedicated Board Infinity coach who works in the field - someone who can look at the model you have stared at for an hour and tell you what it is actually saying.
Explore 1:1 coachingCoaching is a separate Board Infinity offering. It is not required to complete the course or earn the certificate.
The model that will not balance, explained by someone who has built one before.
Not just whether it calculates - whether the assumptions behind it hold up.
Cases set for you, then reviewed, so the frameworks turn into judgement.
Which finance path fits you - FP&A, corporate finance or analytics - and what to learn next.
Twenty-two hours end to end, fully self-paced. Every module lists its learning objectives, its full contents - every lesson, reading and assignment - and what you leave with.
Lesson titles, durations and counts are taken from the Coursera course page, which remains the authority if the course is updated.
This is a finance course, not a software course. The tools are the ones analysts actually model in - and only the ones this course covers.
Where the integrated models, scenario tables and valuations are built. Model architecture, statement linking and sensitivity analysis all happen here.
The same modeling work, collaboratively. Every core model in the course can be completed in Sheets instead of Excel.
For analysis that outgrows a spreadsheet. Module four introduces pandas for financial analysis and automating repetitive tasks. Coursera lists Python as optional.
The reporting your analysis reads from. The course works with statements and financial data as they are actually reported.
The twenty skills Coursera lists for this course, grouped the way the work actually splits - reading the numbers, modeling them, projecting them, and the tools underneath.
Reading what the statements are telling you.
Turning history into a model of the future.
Committing to a number, then checking it.
What the work is actually done in.
These are skill areas the course teaches, not separate software certifications. The single credential is the shareable certificate issued through Coursera.
Complete the graded assessments and you earn a shareable certificate, issued through Coursera - with a one-click path onto your LinkedIn profile.
The credential is provided through Coursera, where the course is hosted. Board Infinity does not issue a separate certificate for this course.
Coursera's one-click button files it under Licenses & Certifications.
A named credential against a syllabus anyone can read in full.
On social media, or in a performance review as evidence of what you covered.
Awarded on 17 assignments across the four modules - it certifies the work, not attendance.
These are the roles that build models, read statements and defend a forecast. The course teaches skills relevant to them - it does not guarantee a role, an offer or a salary.
Statement analysis, ratio diagnostics, integrated models and valuation are the day-to-day of the role.
Budgets, rolling forecasts, forecast accuracy and variance analysis - module four is built around exactly this work.
Reading business metrics and financial data well enough to say what a number means, not just what it is.
Working capital, the cash conversion cycle and cash flow analysis are the levers finance teams manage first.
DCF, WACC and comparable company analysis are the shared language of corporate finance decisions.
A structured foundation to build on, whether you are switching into finance or strengthening what you already do.
Every topic here exists free somewhere on the internet, and plenty of it is taught well. What a structured course adds is the order you meet it in, the checking that makes it stick, and something to show at the end. This is a comparison of formats, not a claim that other teachers are worse.
It is the first of three courses in the Master Financial Analysis: AI-Driven Modeling & Forecasting Specialization. Enrolling in this course enrols you in the specialization.
Financial statements, ratio analysis and DuPont, integrated models, scenario and sensitivity analysis, DCF and comparable valuation, forecasting, budgeting and automation.
View courseRegression, time series and clustering models for financial forecasting; engineered financial features; model validation with MAE, RMSE and MAPE; stock prediction, credit risk and portfolio analytics.
View courseInteractive dashboards in Power BI, Tableau and Streamlit; ML models inside dashboards and web apps; automated reporting pipelines; API-driven data ingestion.
View courseBoard Infinity runs 270+ courses and 57 specializations on Coursera - browse the full catalogue.
The questions Coursera answers on the course page, reproduced here.
This course is designed for aspiring financial analysts, business professionals, founders, and students who want to build strong financial modeling skills. No prior modeling experience is required, but basic spreadsheet familiarity is helpful.
Yes. Coursera currently lists it at beginner level, with the recommended experience being a foundational understanding of the subject. Module one starts with the structure of an income statement rather than assuming you already read one.
No. The course starts with fundamentals and gradually builds toward modeling and valuation. Key accounting concepts are explained clearly with practical examples.
Most learners finish in 4-6 weeks with 4-6 hours per week. You can move faster or slower depending on your schedule, as the course is fully self-paced. The course page header shows Coursera's other estimate of 2 weeks at 10 hours a week, and the specialization page lists this course as 22 hours.
Coursera lists four outcomes: design financial workflows integrating analytics, ML and AI to solve real-world finance problems; evaluate company performance using financial analysis, forecasting and valuation frameworks; build predictive models using regression, time series, clustering and generative AI; and create automated dashboards and reports to deliver real-time financial insights. This first course covers the financial analysis, modeling, forecasting and valuation foundation - the predictive modeling and dashboard work sits in courses two and three of the specialization.
Very practical. Each module includes hands-on modeling tasks, scenario analysis, and real-world interpretation exercises to reinforce concepts.
Yes. Exercises and models are based on practical business scenarios to help you connect theory with how financial analysis is used in real companies.
You'll have access to structured exercises, guided assignments, and discussion prompts to reinforce learning. You'll also receive feedback through quizzes and applied modeling tasks.
Yes. You'll create integrated financial models, scenario analyses, forecasts, and valuation frameworks that mirror real analyst workflows.
Yes. You'll learn the fundamentals of discounted cash flow (DCF) and comparable company analysis, along with guidance on interpreting valuation results in business contexts. Module 3 covers discount rate and WACC, multi-stage DCF modeling and comparable company valuation metrics.
Yes to both. Module 1 covers income statements, balance sheets and cash flow statements, including how they link and the red flags to watch for. Module 2 covers profitability, liquidity, solvency, leverage, coverage and efficiency ratios, DuPont decomposition, working capital and the cash conversion cycle.
Yes. Module 4 covers forecasting approaches, baseline budgets, rolling forecast models, simple and exponential moving averages, forecast accuracy metrics (MAPE and RMSE) and improving accuracy using variance analysis.
Yes. You'll receive structured templates and modeling frameworks that you can reuse for future projects, budgeting, and forecasting work.
You'll primarily use Excel or Google Sheets for modeling and forecasting, with optional Python exercises for learners interested in automation and data analysis.
No. Python is introduced as an optional tool for automation and data analysis. All core modeling can be completed using Excel or Google Sheets. Module 4 includes Python (pandas) for financial analysis and automating repetitive financial tasks.
Absolutely. The course focuses on practical understanding and interpretation, making it accessible to product managers, entrepreneurs, and operations professionals.
Absolutely. The tools and frameworks taught are equally useful for startups, growing businesses, and corporate environments.
Yes. The course builds core skills used in financial analyst, business analyst, consulting, and strategy roles, making it a strong foundation for career transitions. It teaches skills relevant to those roles; it does not guarantee employment.
Yes. Upon successful completion of all graded assessments, you'll earn a certificate that you can share on LinkedIn or include in your resume.
To access course materials, assignments, and earn a Certificate, you'll need to purchase the Certificate experience when you enroll in a course. Eligible learners may also have the option to start with a Free Trial. Some courses may also offer a Full Course, No Certificate option. This lets you access course materials, submit required assessments, and receive a final grade, but you won't be able to earn or purchase a Certificate.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can't afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you'll find a link to apply on the description page.
Board Infinity 1:1 coaching pairs you with a practitioner while you take the course.
Develop practical financial analysis, modeling, forecasting and valuation skills for modern finance workflows.
Enroll on Coursera4 modules · 41 lessons · 17 assignments · beginner level · shareable certificate
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