Python for Data Analysis Workshop
Join our upcoming workshop to learn, connect, and grow with industry experts.
.jpg)
Workshop Details
From: April 7, 2026 – To: June 25, 2026
Time: 7 PM-8:30 PM
Platform: Microsoft Teams
Amount: KES 25,000
About this Workshop
Python for Data Analysis Workshop
About the Workshop
Overview
This course is designed for anyone ready to take their data analysis to the next level.
As datasets grow larger and analysis becomes more complex, spreadsheets alone are no longer enough. Python allows you to work faster, handle larger datasets, automate analysis, and ask deeper questions of your data.
This 12-week, hands-on Python for Data Analysis program is built for people who want to move beyond basic tools and become more sophisticated in how they work with data. The focus is practical and end-to-end—working with real datasets, developing analytical thinking, and turning raw data into clear, meaningful insights through a final project
Objective
This workshop is designed to equip participants—regardless of technical background—with practical Python skills for data analysis in today’s data-driven world.
As data grows in size and complexity, organizations increasingly rely on Python to clean, analyze, and interpret information efficiently. From researchers and analysts to professionals working with large or complex datasets, Python enables deeper analysis and scalable workflows that go beyond spreadsheets.
By the end of this workshop, you’ll be able to work confidently with real-world datasets, perform meaningful analysis, visualize insights, and communicate data-driven findings clearly and effectively.
Course Outline
Meet Our Trainer
Mulei Mutava
Mulei Mutava is an applied economist with expertise in trade, capital markets, and regional integration. He holds a research fellowship at the New South Institute. His academic background includes undergraduate studies at Kenyatta University in Kenya and a master's degree from the University of Cape Town in South Africa. Mulei demonstrates a strong passion for data, having engaged extensively in data-intensive projects at the Capital Markets Authority of Kenya and COMESA. Recently, he has published research on migration trends in Africa with the New South Institute. His research interests encompass the role of finance in economic integration, and he is also committed to mentoring emerging data analysts, bridging the gap between academia and practical applications of data science.