Python in Excel for Data Analytics in Banking

Program Description

Microsoft recently integrated Python directly into Excel (via the =PY() function), allowing analysts, bankers, and business professionals to combine Excel’s familiar grid with Python’s powerful data analysis, visualization, and automation capabilities.

This course equips learners to bridge Excel’s accessibility with Python’s advanced analytics, enabling them to handle tasks like financial modeling, regulatory reporting, and data visualization more efficiently.

 LEARNING OBJECTIVES

·         Explain the integration of Python in Excel and its benefits for financial and regulatory tasks.

·         Use the =PY() function to run Python code inside Excel worksheets.

·         Apply Python libraries (Pandas, Matplotlib, Seaborn) for data cleaning, analysis, and visualization.

·         Automate repetitive Excel tasks using Python scripts.

·         Build simple financial and compliance dashboards combining Excel formulas and Python outputs.

·         Interpret and present results in a format aligned with Ghanaian banking and ISO reporting standards.

 PRE-REQUISITE

 ·         Basic Python and Excel courses

 COURSE CONTENTS

 Introduction to Python in Excel

·         What the integration is, why it matters for finance, compliance, and reporting.

Getting Started

·         Enabling Python in Excel, using the =PY() function, basic syntax.

Python Essentials Refresher

·         Quick review of variables, data types, loops, and importing libraries.

Data Handling with Pandas

·         Importing, cleaning, transforming, and summarizing datasets.

Visualization in Excel with Python

·         Creating charts and dashboards with Matplotlib and Seaborn.

Automating Reports

·         Building automated compliance and financial reporting workflows.

Integrating Excel & Python Workflows

·         Combining Excel formulas with Python for reproducible, auditable outputs.

Capstone Project

·         Learners design a mini-project (e.g., compliance dashboard, loan analysis, or faith-based dataset project).

Wrap-Up & Assessment

·         Review, knowledge check, project presentations, and feedback.

Python in Excel for Data Analytics in Banking

Duration: 5 days

Skill Level: Intermediate

Delivery Mode: In-person

Month: June