Predictive Analytics with Python in Excel

Duration

60  Mins

Level

Intermediate

Webinar ID

IQW24H0852

  • Data Manipulation with Python
  • Building Predictive Models
  • Executing Python Scripts in Excel
  • Visualization of Results in Excel
  • Practical Examples and Case Studies
  • Best Practices and Troubleshooting

Overview of the webinar

This topic explores the integration of Python's advanced data analysis capabilities within the familiar framework of Microsoft Excel. This combination allows users to enhance their spreadsheet models with the power of Python's machine learning and statistical tools, making complex predictive analytics accessible right from Excel.

Excel has long been the go-to tool for financial and data analysis due to its ease of use and widespread availability. However, its built-in capabilities can be limited when it comes to more sophisticated analytics. Python, on the other hand, is a versatile programming language favored for its extensive libraries that cater to data manipulation, statistical modeling, and machine learning. By utilizing Python within Excel, users can execute powerful algorithms to forecast outcomes, identify trends, and make data-driven decisions without leaving the Excel interface.

The session will cover practical examples such as building predictive models for sales forecasting, customer behavior analysis, and financial trends. Attendees will also explore how to visualize the results within Excel to make them actionable for decision-makers.

This session is ideal for professionals who rely on Excel for data analysis and are looking to extend their capabilities with Python’s advanced analytics. It will empower participants to tackle more complex data challenges and provide a competitive edge in their respective fields.

Who should attend?

  • Data Analyst
  • Business Analyst
  • Financial Analyst
  • Marketing Analyst
  • Operations Manager
  • Project Manager
  • Financial Controller
  • Accountant
  • Data Scientist
  • Business Intelligence Specialist
  • IT Manager
  • HR Analyst
  • Sales Manager
  • Administrative Coordinator
  • Excel Trainer
  • Management Consultant

Why should you attend?

This webinar offers a compelling opportunity for anyone looking to harness the powerful combination of Excel's user-friendly interface with Python's robust analytics capabilities.

By attending, participants will learn how to leverage Python within Excel to perform advanced data analysis, predict trends, and make informed decisions more efficiently. This session is particularly valuable for business analysts, data scientists, and anyone involved in data-driven decision making, as it will enhance their ability to model complex scenarios and forecast outcomes using accessible tools.

Moreover, attendees will gain practical skills in setting up Python in Excel, executing Python scripts, and interpreting results—all within the familiar spreadsheet environment. This integration not only streamlines workflow but also opens up new possibilities for data manipulation and visualization that are not readily achievable with Excel alone.

Whether you're aiming to improve your analytical capabilities or integrate more sophisticated analytical techniques into your daily work, this webinar will provide the knowledge and tools needed to elevate your data analysis to the next level.

Faculty - Mr.George Mount

George Mount is the founder and CEO of Stringfest Analytics, a consulting firm specializing in analytics education and upskilling. He has worked with leading bootcamps, learning platforms and practice organizations to help individuals excel at analytics.

George regularly blogs and speaks on data analysis, data education and workforce development and is the author of Advancing into Analytics: From Excel to Python and R (O’Reilly Media, 2021). He is a recipient of the Microsoft Most Valuable Professional (MVP) award for exceptional technical expertise and community advocacy in the field of Excel.

George holds a bachelor’s degree in economics from Hillsdale College and master’s degrees in finance and information systems from Case Western Reserve University. He resides in Cleveland, Ohio.

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