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Python in Excel: Foundations for Non-Coders
Python is now built into Excel and the analysts who learn to use it will pull ahead of those who don't.
No coding background required: this Masterclass combines the familiarity of Excel with the flexibility and speed of Python, so you can automate tasks, handle larger datasets, and create dynamic insights and visuals that go far beyond traditional spreadsheet limits.
Join industry expert Carolina Lago for this hands-on Masterclass, designed for intermediate to advanced Excel users. Cut through the complexity and focus on the practical, real-world applications of Python in Excel without becoming a programmer. This is your chance to stay ahead of the curve and transform the way you work with data.
What you'll learn?
- Master the essentials of Python in Excel - understand how it integrates with formulas and complements tools like Power Query and VBA.
- Automate and streamline your workflows - use Python to handle repetitive analysis, large datasets, and performance-heavy calculations effortlessly.
- Create richer insights and visuals - build advanced analyses, reports, and visualizations that go beyond Excel’s native capabilities.
- Leverage Python’s most powerful libraries - including NumPy, Pandas, Matplotlib, and Seaborn.
- Build a complete project from scratch - apply your new skills in a hands-on capstone exercise that brings together data cleaning, analysis, and visualization.
This training will take place on 5 & 6 Oct (5:00-8:00 pm BST) online via Zoom. It is available as a single Masterclass or as part of our Premium Online Global Excel Summit Blind ticket.
What's included
Who is it for
This Masterclass is designed for professionals who use Excel regularly and are confident with its formulas, functions, and data tools. It focuses on the practical application of Python in Excel to enhance analysis, reporting, and automation without requiring any prior coding experience. Building on participants’ existing Excel skills, the course demonstrates how to integrate Python seamlessly to create faster, more powerful, and more flexible workflows.
- Data analysts and business professionals looking to modernize their Excel skills
- Finance professionals who want to automate and enhance reporting
- Power users of Excel interested in exploring data science and AI tools
- Professionals working with large or complex datasets
- Advanced Excel learners seeking to future-proof their analytical capabilities
Download Course Brochure
Course contents
About your trainer
Carolina Lago
Carolina is the Managing Director at Tactic Financial, where she helps SMEs and finance professionals enhance their skills through corporate training and hands-on advisory services. With over 15 years of experience in Financial Planning & Analysis (FP&A) and a Master's degree in Accountancy specializing in Data Analytics, Carolina's expertise spans multiple industries and global locations. Recognizing a gap in the market for flexible yet robust financial models, she developed the TACTIC Financial Modeling Framework, designed to create versatile and adaptable models with solid calculations. Carolina's multi-industry experience and strong academic background make her a strategic planner capable of interpreting data to drive actionable insights and business success.
What people think of
Carolina Lago
Module 1 - Why Python in Excel Is a Game Changer
- What Python in Excel actually is
- How it complements Excel (not replaces VBA or Power Query)
- The difference between Excel’s “cell-by-cell” logic vs. Python’s “object-oriented” thinking
Module 2 - Python Data Structures for Excel Users
- Everything in Python is an object
- Discuss .index, .values, and .column
- What’s a list, a dictionary, and a DataFrame - and how they compare to Excel ranges/tables
Module 3 - Python Libraries
- What are libraries and why they matter
- Overview of pandas, numpy, matplotlib, seaborn, statsmodels
- Preloaded libraries
- Data importing (import pandas as pd)
- Finding help: documentation, examples, community
- How to use AI
Module 4 - Functions vs. Methods
- Overview of function / method
- Visual analogy: =SUM(A1:A10) vs. df["Sales"].sum()
- Syntax patterns and common mistakes
- Practical examples with DataFrames and Series
Module 5 - Applying It All
- Combining concepts: libraries + data structures + methods
- Mini workflow: clean data → summarize → visualize
- Practical examples, e.g. “Top 5 products by sales”
- Hands-on mini-project: Create a compact, end-to-end report with Python
Training requirements
Intermediate Excel skills and a basic understanding of data analysis concepts are recommended. No prior coding experience required.
Each delegate must bring their own laptop with their preferred version of Excel installed.
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Buy 365-Day Digital Masterpass
If you continue experiencing issues, you can send it to us via email to info@globalexcelsummit.com
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