Claude AI in Excel for Business Professionals Course

Lesson 1 • Setting Up Your Work Environment

Walks through accessing Claude via browser and API, and configuring Excel for AI-assisted work. Ensures every student has a functional environment before practicing prompts.

Lesson 2 • Understanding Claude AI Capabilities

Covers what Claude AI is, how it processes language, and what it can do in a business context. Establishes the mental model needed for all subsequent Excel integration work.

Lesson 3 • Writing Your First Effective Prompts

Introduces prompt structure: role, context, task, and format. Students practice generating simple Excel instructions from natural language requests.

Lesson 1 • Core Prompt Design Principles

Covers specificity, constraint-setting, and output shaping as the three pillars of effective Excel prompts. Directly reduces trial-and-error in later applied chapters.

Lesson 2 • Evaluating and Validating AI Outputs

Establishes a validation checklist: logic review, edge-case testing, and manual spot-checks. Prevents errors from propagating into business-critical spreadsheets.

Lesson 3 • Iterative Prompting and Refinement

Introduces follow-up prompting, correction requests, and constraint additions to refine outputs. Students practice multi-turn conversations to reach production-ready results.

Lesson 4 • Prompt Templates for Common Tasks

Builds a reusable library of prompt templates for formulas, data cleaning, and reporting. Templates accelerate daily work and enforce consistency across a team.

Lesson 1 • Generating Basic Formulas

Covers prompting Claude for SUM, AVERAGE, COUNT, and IF formulas with correct cell references. Builds confidence in translating business questions into working formulas.

Lesson 2 • Debugging Broken Formulas with Claude

Teaches pasting error messages and broken formulas into Claude for diagnosis and repair. Students practice a structured debug workflow that resolves errors in minutes.

Lesson 3 • Lookup and Reference Formulas

Teaches prompting for VLOOKUP, XLOOKUP, INDEX-MATCH, and dynamic array lookups. Students learn to describe lookup logic so Claude returns the right function choice.

Lesson 4 • Text and Date Manipulation Formulas

Covers prompting for text-parsing, concatenation, date arithmetic, and formatting formulas. Directly supports data-cleaning and reporting tasks introduced in later chapters.

Lesson 1 • Handling Duplicates and Missing Values

Covers Claude-assisted strategies for flagging, removing, or imputing duplicates and blanks. Students choose the right approach based on data context and business rules.

Lesson 2 • Diagnosing Data Quality Issues

Covers prompting Claude to identify inconsistencies, blanks, duplicates, and format mismatches in a dataset description. Accurate diagnosis drives efficient cleaning strategies.

Lesson 3 • Standardizing Text and Categories

Teaches using Claude-generated formulas and Power Query M code to normalize text case, trim spaces, and unify category labels. Consistent categories enable reliable analysis.

Lesson 4 • Automating Repeatable Cleaning Workflows

Teaches building reusable Power Query queries and macro-ready cleaning steps with Claude's help. Automation reduces manual effort when new data arrives each reporting cycle.

Lesson 1 • Calculated Fields and Items

Teaches prompting Claude to write calculated field formulas and explain their scope within pivot tables. Students avoid common calculation errors unique to pivot contexts.

Lesson 2 • Designing Pivot Table Structures

Covers prompting Claude to recommend row, column, value, and filter field arrangements for specific business questions. Good structure decisions prevent rework later.

Lesson 3 • Building Automated Summary Reports

Teaches assembling Claude-generated formulas and pivot outputs into a structured, auto-refreshing summary report. Students deliver a complete reporting artifact by chapter end.

Lesson 4 • Statistical and What-If Analysis

Covers prompting Claude for descriptive statistics, correlation, and scenario-based what-if models. Connects raw data to decision-support outputs expected by business stakeholders.

Lesson 1 • Formatting and Polishing for Stakeholders

Teaches using Claude to generate conditional formatting rules, consistent typography, and print-ready layouts. Professional presentation increases stakeholder trust in the data.

Lesson 2 • Interactive Controls and Slicers

Covers adding drop-downs, slicers, and form controls to dashboards with Claude-guided setup instructions. Interactivity lets users explore data without editing the workbook.

Lesson 3 • Planning a Dashboard with Claude

Covers prompting Claude to recommend layout, chart types, and KPI selection based on audience and business goal. Planning before building prevents costly redesigns.

Lesson 4 • Choosing and Configuring Charts

Teaches prompting Claude to recommend the right chart type for each data story and configure axis, label, and color settings. Correct chart choice prevents misinterpretation.

Lesson 1 • VBA Fundamentals via Claude Explanations

Covers prompting Claude to explain the VBA editor, module structure, Sub procedures, and variable types. Conceptual grounding prevents blind copy-paste errors in later tasks.

Lesson 2 • Looping and Conditional Logic in VBA

Addresses prompting Claude for For-Next, Do-While loops, and If-Then-Else blocks applied to real data scenarios. Loops unlock batch processing across large datasets.

Lesson 3 • Generating Macros for Repetitive Tasks

Teaches describing repetitive workflows to Claude and receiving complete, commented VBA code. Students automate formatting, copying, and file-saving tasks immediately.

Lesson 4 • Debugging VBA Code with Claude

Covers pasting runtime errors and broken code into Claude for diagnosis and corrected rewrites. Students apply a structured debug process that mirrors professional development practice.

Lesson 1 • Measuring Productivity Gains

Covers tracking time saved, error rates, and output quality before and after AI integration. Measurement justifies continued investment and guides further workflow improvements.

Lesson 2 • Mapping AI to Business Processes

Covers identifying high-value, repetitive Excel tasks across finance, operations, and sales for AI augmentation. Process mapping ensures AI effort targets maximum business impact.

Lesson 3 • Governance, Accuracy, and Risk Management

Addresses data privacy rules, output validation gates, and escalation protocols for AI-generated Excel content. Governance protects the organization from costly AI-driven errors.

Lesson 4 • Scaling AI Adoption Across the Organization

Teaches building a rollout plan, training peers, and iterating based on feedback to expand AI-assisted Excel use. Structured scaling sustains gains beyond the initial pilot.