Program Overview

AIﾗExcel Business Analysis Course

Course Introduction

The AIﾗExcel Business Analysis Course is designed to equip participants with the skills to harness the power of modern Excel, combining database, algorithm, and intelligent analysis capabilities. This course will cover Power Query's ETL helper, Power Pivot's relational data model, and Dynamic Array's programmatic thinking, enabling participants to build sustainable data processing and analysis systems without IT support.

Course Objectives

• Equip participants with the skills to build a lightweight database and automated reports using Excel.
• Enable participants to use Power Query for data cleaning and integration, and Power Pivot for modeling and indicator design.
• Teach participants to use Dynamic Array functions to develop flexible and reusable analysis templates.
• Help participants understand data analysis logic and solve report problems from a data structure perspective.
• Enable participants to combine AI tools with Excel for intelligent collaboration.

Target Audience

• Business executives who need to master data analysis and AI collaboration skills to improve work efficiency.
• Managers and decision-makers who need to understand correct data analysis and AI collaboration concepts to define problems, allocate resources, and control quality.

Expected Outcomes

• Participants will be able to build a self-sustaining data analysis system using modern Excel.
• Participants will be able to use Power Query, Power Pivot, and Dynamic Array functions to analyze data and create reports.
• Participants will understand how to combine AI tools with Excel to generate formulas, interpret errors, and design analysis models.

Course Outline

Environment and Tools

• Business data analysis process
• Data analysis maturity model
• Excel transformation path
• Impact of generative AI

From "Making Reports" to "Drilling into Data"

• Pareto chart analysis logic and application scenario
• Review of basic tool capabilities
• "Range" vs. "Table"
• Using combination charts to tell stories
• Exploring pivot table analysis capabilities
• Viewing data distribution
• Scatter chart structure and hotspots
• Example: e-commerce key indicator cluster analysis

Dynamic Array Ecosystem

• Breaking old rules with "spill range"
• Dynamic update process combining "array" and "table"
• Basic dynamic array functions and features: UNIQUE(), #, FILTER()
• Programmatic "truth table" operation logic
• Connecting "array" and "cell" functions: TEXTJOIN()
• "Brute force" and "elegant" problem-solving postures
• Excel new function development trend based on dynamic array

Business Simulation: Building a Mini Data Warehouse with Excel

• Analyzing the entire process: data preprocessing (ETL) + data modeling + chart presentation
• Data extraction and cleaning - Power Query's ETL magic
• Excel data loading path
• Basic structure of "modeling": Fact Table and Dimension Table logic chain
• Establishing "data relationships"
• Using DAX to calculate derived indicators
• Building a date data table
• Pivot table analysis across data tables

Data Structure Transformation

• Wide data and long data
• Core logic and application scenario of "wide" to "long" conversion
• From static monthly reports to dynamic full-period tracking
• M Code advanced application - copying and modifying queries
• Data integration: appending reports to datasets
• Multi-perspective analysis: flexibly opening up new insights from long data

AI Collaboration Data Analysis

• Example: RFM analysis
• RFM analysis principle and application scenario
• Preparing RFM data with Power Query
• Performing RFM analysis using k-means
• Truly landing AI application: Vibe Coding completes data analysis tasks
• Oral writing Python program code to implement k-means operation

Course Schedule

• Two-day course (12 hours in total).
• Three batches:
  • First batch: 2026/01/03, 01/10 (Saturday) 9:30-16:30 (with a 1-hour lunch break).
  • Second batch: 2026/05/02, 05/09 (Saturday) 9:30-16:30 (with a 1-hour lunch break).
  • Third batch: 2026/09/05, 09/12 (Saturday) 9:30-16:30 (with a 1-hour lunch break).

Course Fee

• The course fee is NT$6,500 (student discount price: NT$5,500).
• Early bird discount (before 04/21): NT$500.

Refund Policy

• Full refund if requested 30 days before the course starts.
• 90% refund if requested between 29 days and 1 day before the course starts.
• 50% refund if requested after the course starts but before one-third of the course is completed.
• No refund if requested after one-third of the course is completed.
• Full refund if the course is cancelled due to insufficient enrollment.