Python in Excel training for finance teams

Help your finance, accounting, or operations team use Python inside the spreadsheets they already work with. In this private workshop with George Mount, participants practice preparing data, comparing results, and building analyses they can explain to colleagues.

Start with a business question: how should we compare run rates, apply a fiscal calendar, or explore uncertainty in a forecast? We use those questions to give Python a practical job, with time to understand the code and check the answer.

Microsoft Excel MVP · O'Reilly author · LinkedIn Learning instructor

What your team will practice

The goal is to make Python useful in a familiar workbook. Participants work through guided examples, adapt the methods, and discuss when an Excel formula or Power Query is still the better choice.

• Prepare data for analysis. Read workbook tables into Python, work with DataFrames, and check dates, data types, and missing values.
• Make reporting rules explicit. Group and summarize transactions, apply reporting periods, and compare results with the source data.
• Explore patterns visually. Build charts that help colleagues understand trends, relationships, and unusual values.
• Evaluate assumptions. Compare time-series methods or simulation scenarios and explain what the results do and do not tell you.
• Leave an understandable workbook. Keep inputs, analysis steps, and checks clear enough for another analyst to follow.

See the kind of work we can build on

My examples of comparing revenue run rates with Python in Excel and building a custom fiscal calendar show the approach: start with a reporting question, make the assumptions visible, and test the result. We can use examples like these to discuss the right level for your workshop.

Sample two-day agenda

This is a starting outline. We agree on the final agenda before booking so the pace and depth fit the group.

Day one: Build a dependable foundation

• Read Excel tables into Python and understand how Python cells and outputs fit into a workbook.
• Clean, summarize, and reshape a dataset with pandas.
• Create and interpret charts, with attention to the question each chart answers.
• Work with dates, reporting periods, and moving averages, then check the outputs against known results.

Day two: Apply the methods to financial analysis

• Explore distributions, relationships, and statistical questions in a business dataset.
• Use Monte Carlo simulation to compare scenarios and examine uncertainty.
• Compare forecasting approaches and evaluate their errors against historical data.
• Develop an applied analysis with documented assumptions and review steps. Regression, classification, or more advanced time-series methods can be included where the group is ready.

Materials for the two-day workshop

• Two full days of live instruction, with guided exercises and time for discussion.
• Detailed step-by-step course notes, practice datasets, slides, and handouts.
• Supplemental video content for continued practice and lifetime access to the slides, datasets, and handouts.
• A copy of Advancing into Analytics: From Excel to Python and R.

For a shorter session or a longer program, we agree on the materials and delivery arrangements during scoping.

Work directly with George Mount

George Mount is the founder of Stringfest Analytics, a Microsoft Excel MVP, an O'Reilly author, and a LinkedIn Learning instructor. His teaching includes modern Excel and analytics programs for financial services analysts and operations teams.

George designs and leads the training, from choosing the learning objectives to preparing the exercises and delivering the sessions. Read more about George and see participant feedback.

Software and preparation

Participants need access to Python in Excel through a qualifying Microsoft 365 subscription and a supported Excel environment. We confirm the available features, update channel, organizational settings, and practice-file setup before finalizing the agenda. Check the current Microsoft availability guidance; having Excel installed does not by itself confirm Python access.

Exercises can use sample data. If you want to include your own examples, we agree on suitable data and handling arrangements in advance. My training tech-check guide explains the preparation process.

Questions from training organizers

Can we tailor the workshop to our team?

Yes. Share the reporting or analysis work you want to improve, the current skill level, and one or two representative tasks. We can adjust the examples, pace, and depth, and discuss whether a focused workshop or a longer learning series fits best.

Do participants need to know Python?

No prior Python experience is required for the introductory workshop. Participants should already be comfortable with Excel tables, formulas, lookups, and PivotTables. We confirm those starting skills during scoping.

How much does private training cost?

The fee depends on the agreed scope, group size, delivery format, and customization. Share your timing and budget or planning stage when you inquire. The agenda, fee, materials, and delivery arrangements are agreed before booking; it is fine to start the conversation while seeking internal approval.

Is this the same as a general Python course?

This workshop uses Python inside Excel. For broader Python work in notebooks, explore Python Foundations for Finance. For a program combining Excel, Power Query, Copilot, and Python, compare the team training options.

Plan your team training

Use the form below to discuss a paid Python in Excel workshop for your organization. Tell me about the audience, approximate group size, reporting or analysis goals, preferred timing, and virtual or on-site delivery. Include your software access and budget or planning stage if known.

I will review your goals and follow up about scope, fit, and next steps. Prefer to talk it through? Book a training conversation.

Learning independently? Explore the Python in Excel learning guide for books, tutorials, and individual courses.