Skills you'll gain

There are 6 modules in this course

What you'll learn: 1. Optimize Decision-Making Using Python: Build and solve linear and mixed-integer optimization models with Python tools like Pyomo, tackling real-world challenges in logistics, resource allocation, and planning. 2. Transform Non-Linear Problems: Apply linearization techniques to convert complex non-linear constraints into linear forms for efficient and scalable solutions. 3. Model Complex Decisions: Incorporate integer variables and logical rules into optimization models to handle discrete decisions, such as project selection or facility placement. 4. Evaluate and Refine Models: Use sensitivity analysis, branching, bounding, and pruning techniques to ensure robust and effective solutions that adapt to changing conditions. 5. Leverage Prescriptive Analytics for Strategy: Apply optimization and prescriptive analytics to develop actionable recommendations, enhancing efficiency and decision-making in digital transformation contexts.

Optimization

Working with Linear Optimization

Adding Complexity for Discrete Decisions

Optimization in Python

Practicum

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