Working in a browser-based notebook
Work in a hosted JupyterHub environment without installing software locally. Learn how notebooks work, run cells, read outputs and recover from common errors.
Python for Finance
Build practical Python confidence using real spreadsheet work.
A hands-on course for finance, accounting, compliance, reporting, and regulated teams who are comfortable with spreadsheets but new to Python. Build from Python foundations to practical data handling, reconciliation checks and repeatable workflows.
Outcomes
What participants will be able to do.
Open a notebook, run code, read simple errors, and make small changes without feeling lost.
Understand the Python basics needed to follow and adapt analysis examples.
Use pandas to load, inspect, filter, clean, summarise, and combine spreadsheet-style data.
Produce clear outputs that can be checked, reviewed, and taken back into normal reporting work.
Curriculum
A beginner-friendly practical syllabus.
Python basics for spreadsheet users
Work with values, names, text, numbers, dates, lists, dictionaries, comparisons, conditions, loops, and small reusable steps, using examples that map back to familiar spreadsheet tasks.
Loading spreadsheet-style data with pandas
Load Excel and CSV exports, inspect rows and columns, check column names and data types, preserve identifiers such as account numbers, and understand the first checks to run before trusting a dataset.
Cleaning and preparing data
Select useful columns, rename unclear headings, filter records, sort outputs, handle blanks, standardise simple text values, and create calculated columns for common finance and reporting checks.
Analysing and summarising data
Use pandas to count records, total values, group by categories, compare subsets, check control totals, and answer practical questions from spreadsheet-style finance or operations data.
Combining and checking datasets
Join data from multiple files, spot unmatched records, investigate differences, and produce clean outputs that support review, correction, and follow-up analysis.
Taking the work back to the team
Finish with a practical analysis workflow that participants can read from top to bottom, explain to someone else, and adapt after the course without needing to understand Python or pandas internals.
Format
Designed for complete beginners.
For spreadsheet-confident beginners
Suitable for people who work with Excel, exported reports, reconciliations, controls, or management information, but have little or no programming experience.
A format shaped around your needs
Enquire about introductory and applied formats. We will agree the syllabus, duration and delivery arrangements for your group, including the scope of reconciliation and automation exercises.
Discuss The Course
Interested in Python for Finance?
Send a short note about the audience, current skill level, and the spreadsheet workflows you want the course to support.