Predictive Analytics

Learn to turn data into actionable insights with Predictive Analytics for Digital Transformation. This hands-on course equips you with Python skills, predictive modeling techniques, and analytics strategies to drive innovation and efficiency in digital transformation with Dartmouth Thayer School of Engineering faculty Vikrant Vaze and Reed Harder. What you'll learn: 1. Build Predictive Models Using Python: Gain hands-on experience with Scikit-learn to develop and refine regression and classification models, applying them to real-world scenarios. 2. Diagnose and Improve Model Performance: Identify issues like overfitting and underfitting, apply cross-validation, and select optimal features to ensure robust, generalizable results. 3. Leverage Advanced Techniques: Explore neural networks, regularization, and cloud-based tools to scale and optimize predictive analytics for complex business challenges. 4. Integrate Analytics into Decision-Making: Translate data-driven insights into actionable strategies to drive innovation and efficiency in digital transformation initiatives

• Turn data into actionable insights using predictive analytics
• Build predictive models with Python and Scikit-learn
• Develop and refine regression and classification models for real scenarios
• Diagnose and improve model performance using cross-validation

• Basic familiarity with the topic and its common terminology
• Readiness to practice through applied exercises or case-based work