Lab instructions and assets for the 2018 Fast Start Decision Optimization Lab.

Please use the same DSX Local cluster assigned to you for the DSX Local labs.

In this workshop you will learn how to use the CPLEX Python API to develop Decision Optimization notebooks, load data and create scenarios utilizing the new Decision Optimization for Data Science Add-on. There are 3 labs:

1. Lab 1: Utilizing the DOCplex Python API using Jupyter Notebooks.
2. Lab 2: Creating an Optimization Model & Planning scenarios with DODS.
3. Lab 3: Guided preview of the upcoming Execution Service.

This repository contains a folder for each lab. Please download the this archive and unzip it on your local machine.

1. Basic knowledge of analytics and Operation Research. These labs do not teach you how to build optimization models. The purpose of this workshop is to provide hands-on experience on the different ways to utilize Prescriptive analytics in DSX Local.
2. To run this workshop you need an instance of DSX Local. Please note that while most code is the same between DSX Local and DSX Cloud, the notebooks included in sample projects will work in DSX Local only