This hands on course is designed for Excel users who want to extend their skills using Python directly inside Excel. You will learn foundational Python concepts€”data types, structures, functions€”and progress into working with Python in Excel using Pandas DataFrames, enabling powerful automation and analysis workflows.  The course blends ACE's practical teaching approach with real-world exercises, ensuring you gain confidence applying Python to everyday Excel tasks.

This course is ideal for: 

• Excel users who want to expand into Python for analysis and automation 
• Business analysts, administrators, and reporting professionals 
• Anyone beginning their Python journey with a focus on practical, Excelbased outcomes

To get the most from this course, learners should: 

• Be comfortable using Microsoft Excel 
• Have basic analytical or data-handling experience 

No prior programming knowledge is required.

By the end of this course, you will be able to:

• Understand core Python concepts and how they integrate with Excel
• Write and execute Python code inside Excel cells and formulas
• Manipulate data using Python lists, tuples, sets, and dictionaries
• Build repeatable workflows using Python functions
• Use Pandas DataFrames for high€‘powered analysis in Excel
• Automate logical workflows using if, for, and while statements

1. Introduction to Python in Excel

• What is Python and why use it in Excel?
• Understanding Python integration in Excel
• Running your first Python cell
• Safe environments and supported libraries

• Strings, integers, floats, booleans
• Converting between data types
• Inputs, outputs, and quick transformations

• Creating and manipulating lists
• Indexing and slicing
• List methods (append, extend, sort, remove, etc.)
• Using lists with Excel data ranges

• Immutable tuples and when to use them
• Sets for uniqueness and membership testing
• Dictionaries for key€“value storage
• Practical examples with Excel€‘sourced data

• Writing and calling reusable functions
• Function arguments and return values
• Using functions to automate Excel workflows
• Practical examples: cleaning data, calculations, formatting outputs

• Introduction to the Pandas library
• Creating DataFrames from Excel tables
• Cleaning, reshaping, and analysing data
• Filtering, sorting, grouping, merging
• Exporting results back into Excel

• Conditional logic with if
• Looping with for and while
• Real€‘world automation patterns
• Error handling and best practices