Lab: Developing a Machine Learning Model for Sales Forecasting

Build Your First Predictive Algorithm

Experience the full machine learning journey in this practical workshop where we'll create a real sales forecasting model from scratch. Working with the familiar sales dataset, we'll follow the exact process data scientists use when developing predictive solutions. 

Learn how to properly prepare data for modeling by creating training and testing splits, select an appropriate algorithm for our business goals, and transform raw data into powerful predictive features. Witness firsthand how models are developed, refined through validation, and rigorously tested before deployment. 

By evaluating the model's performance using industry-standard metrics, we'll gain the critical skills needed to assess AI solutions in organizations.

This hands-on experience demystifies the "black box" of machine learning, giving valuable perspectives on how predictive models are built, what they can achieve, and where they might fall short. This is essential knowledge for any leader implementing AI-driven forecasting.

• Session outline
• Splitting the dataset
• Choosing an algorithm
• Feature engineering
• Development, validation and testing
• Evaluation

• Format
• This session is hands-on. Attendees work on their laptops

• Level
• Beginner

• Prerequisite Knowledge
• Data Fundamentals
• Data Science and Statistical Analysis
• Exploratory Data Analysis and Visualization
• Machine Learning Fundamentals
• Working with Data in Organizations

• Learning Outcomes
• Experience developing simple machine learning predictive models