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Using AI and Copilot in Excel for Data Analysis
Your Excel analysis can benefit from AI when data and requests are well structured. Explore Copilot to prepare data processing and reporting, then check the results. Become more independent without losing control of the figures used to make decisions.
- Duration
- 3 days 21 hours
- Code
- IA025FR Code
Presentation
As data becomes a strategic asset, knowing how to use AI in Excel provides a tangible advantage. This focused 3-day course teaches you to use Copilot and AI integrated into Excel to automate repetitive tasks, identify hidden trends and accelerate decision-making without coding.
Designed for non-technical professionals, it takes you from basic Excel use to AI-enhanced data analysis. Through practical cases drawn from your work in HR, logistics, production, finance and other functions, you will test, explore and iterate.
At the end of the programme, you will design an interactive dashboard using your own data and leave with an operational project ready to use. The focus is on tools you can apply the next day, not abstract theory.
Objectives
By the end of this Excel and Copilot course, you will be able to:
- automate repetitive tasks and create interactive dashboards with Excel and AI;
- use Copilot to accelerate data analysis and enrich business insights;
- identify and implement practical AI use cases across business functions such as HR, production, logistics and customer relations;
- assess service quality and customer satisfaction using real data;
- work more independently and efficiently when manipulating and interpreting complex data.
Program
Module 1: demystifying AI in Excel
- Methods for integrating AI into Excel.
- Analysing the 3 levels of AI assistance:
- automatic suggestions;
- predictive analytics;
- intelligent automation.
Practical exercises
- Activate Copilot and test initial suggestions.
Module 2: mastering Copilot for data analysis
- Essential prompt use for interacting with AI.
- Using 5 key prompt types: analysis, visualisation, prediction, comparison and recommendation.
Case study
- Analyse KPIs using a sector-specific dataset, choosing finance, HR, operations or customer relations.
Module 3: improving operational performance with AI
- Monitoring performance in production, quality, sales, logistics and other areas.
- Detecting anomalies and generating intelligent alerts.
- Automatically identifying correlations, such as market conditions and sales results.
- Automatically generating intelligent reports.
Module 4: customer analytics and business intelligence
- Turning customer data into actionable insights.
- Monitoring business KPIs: revenue, satisfaction, churn and conversion.
- Anticipating customer, employee and user behaviour through predictive analytics.
- Automatically segmenting and targeting actions.
Practical exercises
- Design an action plan based on real data, such as reducing churn or improving productivity.
Module 5: automating advanced tasks
- Creating intelligent, self-updating dashboards.
- Using advanced AI functions for forecasting and trend detection.
- Automating repetitive tasks with AI-assisted macros.
- Setting up automatic alerts for critical indicators.
Practical exercises
- Create a tailored dashboard suited to your work.
Module 6: collaborating on a complex project
- Apply all the skills you have acquired to a complex real case, such as a product launch, logistics optimisation or budget management.
- Working in a multidisciplinary team.
- Creating a deliverable covering feasibility analysis, prioritisation and projections.
- Presenting final recommendations.
Audience
This course is intended for anyone who needs to manipulate and analyse data, including:
- department managers in HR, marketing, finance, logistics and other functions;
- data analysts and management controllers;
- project managers and executives seeking greater efficiency;
- anyone who wants to work more independently with complex data.
Prerequisites
This course requires the following prerequisites:
- Professional experience: familiarity with data analysis or experience handling data in HR, marketing, finance or another field is recommended.
- Technical requirements: a PC or Mac with at least Microsoft 365 E3 and access to Copilot for Microsoft 365 activated.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
- Case study
Course highlights
- Practical, concrete approach: work with 5 realistic simulated datasets, applying concepts immediately to practical situations.
- Copilot-focused expertise: the course centres on Copilot and its features, helping you master its finer points and integrate it naturally into your workflows.
- Tangible resources: leave with a library of over 50 prompts for different business contexts, plus a digital guide and quick-reference sheet to support independent use after the course.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
Microsoft®, Microsoft Excel® and Copilot™ are registered trademarks or trademarks of Microsoft Corporation in the United States and other countries.