Optimization Analytics in PythonBeginner’s edition
No coding background needed but willingness to learn.
Optimization is a mathematical science that depends on getting the best results over iteration of inputs, think about which quantity to produce and for which products to maximize profit or the price we set for a product to maximize revenue. Where do we open factories and how much personnel do I need for my business. Purchasing decisions, Production planning and capacity allocation are also commonly solved through optimization. Even optimization of routes uses optimization .
The problems you can improve with optimization are basically limitless. And the principles are same, we have a goal , inputs and constrains to follow in order to reach the right solution.In this masterclass , we will learn how to code with python for the purpose of optimization and how can we use python scale to solve real world problems in our business as fast and as efficiently as possible. The masterclass is divided into three modules ; orientation to python , principles of optimization and problems solving using optimization tools in python.
Module No 1 : (Practical)
To enable the diving in the optimization world, we have first to get used to python as the masterclass is designed for beginner’s , we will spend the first module practicing python commands , especially commands that we will use recursively in our optimization problems.
- What is python.
- Hands on practice with python.
- Python data structures.
- Python Data types .
- Simple mathematics with Python.
Module no 2: (Practical)
Before entering the optimization world , a Q&A will be held on common problems the business stakeholders face and which of them can be an optimization problem , then we explain the different types and complexity of optimization problems. From the very easy to conduct and solve to the complex multivariate problems.
- Understanding the problem.
- What is linear Programming.
- Objective function formulation.
- Constraints definition and binding constraints.
- Integer and nonlinear programming.
Module no 3 : (Practical)
Module 3 encompasses simple case studies that can be encountered with optimization and how to calibrate these solutions to more flexible to uncertainty of the future. I.e we will give examples on how to make discrete and continuous simulations to test the model against uncertainty.
- Purchasing decisions Optimization.
- Supply chain design optimization.
- Production planning optimization.
- Pricing optimization.
- Capacity allocation optimization.
This Masterclass is designed for Business stakeholders who face quantitative and analytical decisions every day and need an optimum recommendation to back up their decision.
While the Masterclass is for beginner’s , the Masterclass intensity and the problems become more complex from module 1 to module 3. So clear understanding of context and coping up quickly with the Modules pace will be highly appreciated.