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Professionals using AI tools to analyse data, create charts and prepare business reports
Artificial Intelligence · Course #006

AI for Data Analysis and Reporting

AI for Data Analysis and Reporting is a practical course that shows participants how to use Artificial Intelligence responsibly across the data workflow. Learners practise data preparation, spreadsheet analysis, formula and query support, exploratory analysis, chart selection, insight generation and report writing. The course emphasises asking precise analytical questions, validating calculations, protecting sensitive information and communicating evidence without exaggeration. No advanced programming background is required.

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Overview

AI for Data Analysis and Reporting is a practical course that shows participants how to use Artificial Intelligence responsibly across the data workflow. Learners practise data preparation, spreadsheet analysis, formula and query support, exploratory analysis, chart selection, insight generation and report writing. The course emphasises asking precise analytical questions, validating calculations, protecting sensitive information and communicating evidence without exaggeration. No advanced programming background is required.

Course Highlights

AI-assisted data preparation

Spreadsheet and formula support

Exploratory data analysis

Charts and data visualisation

Insight generation and report writing

Data validation, privacy and responsible use

Modules & Curriculum

Introduction to AI-Assisted Data Analysis

Defining Analytical Questions and Preparing Data

Spreadsheet, Formula and Query Support

Exploring Trends, Patterns and Anomalies

Data Visualisation and Chart Selection

AI-Assisted Reporting and Executive Summaries

Validation, Privacy and Responsible Data Analysis

Learning Outcomes

  • Define clear analytical questions and select suitable AI-supported approaches.
  • Prepare, organise and clean structured data for analysis.
  • Use AI to support spreadsheet formulas, queries and exploratory analysis.
  • Identify patterns, trends, comparisons, anomalies and possible data-quality issues.
  • Select suitable charts and explain analytical findings clearly.
  • Draft concise reports, summaries and decision-focused recommendations.
  • Verify AI-supported calculations, interpretations and visualisations.
  • Apply confidentiality, privacy and responsible data-use principles.

Ready to Build Your Future-Ready Skills?

Turn raw data into clear insights, visualisations and professional reports with practical AI tools.

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