IBM Financial Planning and Analysis (FP&A) with AI Skills

By the end of this course, you will write structured AI prompts that clean and standardize messy financial data, use AI to draft and extend model logic, apply AI to anomaly detection and reconciliation, and build the governance habits — guardrails, output logging, and audit evidence — that make AI-assisted finance defensible. This is where AI stops being a buzzword and becomes practical leverage. You will reclaim the hours lost to manual data prep and model-building, while keeping human judgment and control firmly in place — the balance finance leaders, auditors, and regulators now expect. What sets this course apart is that governance is built in from the start, not bolted on at the end. Under one clear principle — AI surfaces, the analyst owns — you learn to tier AI uses by risk, verify every output, and document how AI was used. The skills are taught tool-agnostically and demonstrated on AI tools, so they transfer as the tools evolve. No coding background required.

By the end of this course, you'll be able to design, document, and defend a credible, business-aligned budget — one that earns sign-off from leadership and genuine buy-in from the departments that have to deliver it. Most analysts inherit a budget process they've never redesigned. This course changes that. You'll map the end-to-end budget cycle stage by stage, diagnose where and why it stalls, and learn the workflow-design principles — stage-gates, entry and exit criteria, clear role assignments — that make it run faster. You'll move from static, line-item budgeting to driver-based planning: identifying the volume, price, headcount, and productivity levers that actually move the numbers, building them into transparent formulas, and running sensitivity tests that show how assumption changes ripple through revenue, cost, and margin. You'll also develop the business-alignment skills that make budgets stick — mapping departmental goals to measurable drivers, facilitating cross-functional reviews, and capturing agreed changes through traceable budget logs. No prior FP&A or coding experience required. This is Course 2 of the IBM FP&A Analyst with AI Skills Professional Certificate.

By the end of this course, you will distill variances and forecasts into clear, prioritized executive headlines, build headline-proof-action narratives matched to the right charts, map FP&A controls and build a risk register, and rehearse the high-stakes Q&A where decisions are won or lost. This is the translation layer between sound analysis and executive action — the skill set that separates analysts who report numbers from those who shape decisions. You will learn to make your findings land in seconds with leadership, and to stand behind them when challenged. What makes this course distinctive is that it pairs storytelling with governance, because in finance an insight only carries weight if the numbers behind it are controlled and defensible. You will work on a real executive pack for the program's case company — revising it for clarity, selecting charts, building a risk register, and practicing the executive Q&A — producing both a portfolio-grade work sample and habits you can use in your next leadership review.

By the end of this course, you will structure financial models in Excel with clean, auditable architecture, calculate and decompose budget-to-actual variances into price, volume, and mix, build variance bridges that turn numbers into a performance story, and produce rolling forecasts you can validate with error metrics like MAE and MAPE. These are the operational skills that anchor an FP&A analyst's credibility — the work that shows up in every monthly and quarterly review. You will move from a raw budget gap no one can explain to a driver-level narrative leadership can act on, and from guesswork to a forecast you can defend. What makes this course distinctive is its build-it-by-hand approach: you learn the modeling and analysis manually first, so when AI automates this work in later courses, you can tell when its output is wrong. Every skill is taught concept-first, then demonstrated on a realistic enterprise insurer in Excel or IBM Planning Analytics — the same case company you carry through the program.

A multi-stage capstone simulating one full FP&A lifecycle for Acme Mutual, the PC's persistent proxy enterprise insurer. Learners move from raw business data to a boardroom-ready recommendation: selecting KPIs and drivers, building a driver-based financial model, running variances and AI-assisted forecasts, designing scenario and sensitivity views, and assembling an executive narrative pack with embedded governance evidence. The capstone is structured in eight modules that mirror the Assess → Build → Forecast → Communicate sequence, producing an integrated portfolio artifact learners can reference in interviews or performance reviews as concrete evidence of AI-augmented FP&A competency.

Financial planning and analysis (FP&A) is one of the fastest-growing finance specializations — and it starts with knowing what the function is, and what it is not. This first course in the IBM FP&A Analyst with AI Skills Professional Certificate builds the foundations every analyst needs before any modeling or forecasting makes sense. You will learn what FP&A teams own and how they differ from accounting; how budgeting, forecasting, and variance analysis structure the finance calendar; and how analysts partner with the business to turn numbers into decisions leadership can act on. You will read the three core financial statements as one connected system and see why a profitable business can still run short on cash. You will choose the KPIs that link daily operations to the outcomes leadership tracks, and connect financial planning to organizational strategy. No prior FP&A or coding experience is required — every concept is built from the ground up.