Events

Predictive AI in Practice Mini-Course

Unlock the potential of predictive AI modeling in this immersive, three-part mini-course led by Windfall's Data Science Lead, CEO, and Data Scientist. You'll gain hands-on experience transforming data into actionable insights-learning how to prepare datasets, build and evaluate models, and communicate results effectively to both technical and non-technical audiences. Each session includes guided exercises and homework designed to help you apply what you've learned. Participants who complete all three sessions and the associated homework will receive a Windfall Data Science Certification to share on their professional profiles. While you can join any session, we recommend completing the homework to maximize your learning and qualify for certification.
When
12/3/2025 - 12/17/2025

Program

   
Description
Full Series Registration
This full series registration includes all three sessions. If you do not want to register for the full series, then see the options below to register for the individual sessions.
Time
12/3/2025 2:00 PM - 12/17/2025 3:00 PM
12/3/2025 2:00 PM

Session 1: Introduction to Data Science & Modeling
Get started with the foundations of predictive modeling and learn how to make data science approachable-and actionable. In this first session, you'll explore the key concepts behind classification models, from data preparation and training to understanding accuracy and bias. You'll leave with a sample dataset and access to a web-based notebook (like a Google Colab/Jupyter notebook) to build your first predictive model right away. Key takeaways: Understand the fundamentals of data science and predictive modeling Learn to evaluate model accuracy and minimize bias Gain hands-on experience preparing and training a dataset
Time
2:00 PM - 3:00 PM
12/3/2025 2:00 PM

Session 2: Progressing on Predictive AI: Feature Engineering
Take your models to the next level with the art and science of feature engineering. This session will explore how to transform, clean, and enhance your data for better predictive performance. Through guided examples, you'll learn how to handle sparse or imperfect data, build meaningful features, and understand which variables drive the most impact in your models. Key takeaways: - Apply ETL (Extract, Transform, Load) best practices for data preparation - Conduct exploratory data analysis (EDA) to uncover insights - Design and test features that strengthen model performance
Time
2:00 PM - 3:00 PM
12/10/2025 2:00 PM

Session 3: Advanced Modeling & Performance Evaluation
In the final session, you'll go beyond the basics to explore advanced modeling techniques and performance metrics. Learn how to balance model simplicity and accuracy, experiment with clustering and multimodal models, and learn how to measure feature importance to interpret model behavior. You'll also gain insights into how to communicate technical findings to business and go-to-market leaders in a clear, meaningful way. Key takeaways: - Explore advanced modeling methods and evaluation frameworks - Learn which model interpretability tools can help you interpret how your model works - Develop strategies to present data science insights to non-technical stakeholders
Time
2:00 PM - 3:00 PM
12/17/2025 2:00 PM

Sign In