What you’ll learn
• A-Z Guide to Mastering Python for Data Science.
• Become a data driven supply chain manager.
• Set stock policies and safety stocks for all of your Business products.
• Become a supply chain data scientist.
• Work as A demand Planner.
• Use linear Programming in python for logistics optimization and Production scheduling.
• Revenue management
• Learn simulations to make informed supply chain decisions.
• Learn Supply chain techniques you will only find in this course. Guaranteed!
• Segment Customers, Products and suppliers to maximize service levels and reduce costs.
Requirements
♦ Excel
♦ Anaconda
♦ spyder
Description
Course Design
The course is designed as experiential learning Modules, the first couple of modules are for supply chain fundamentals followed by Python programming fundamentals, this is to level all of the takers of this course to the same pace. and the third part is supply chain applications using Data science which is using the knowledge of the first two modules to apply. while the course delivery method will be a mix of me explaining the concepts on a whiteboard, Presentations, and Python-coding sessions where you do the coding with me step by step. there will be assessments in most of the sections to strengthen your newly acquired skills. all the practice and assessments are real supply chain use cases.
Supply chain Fundamentals Module includes:
- Introduction to supply chain
- Supply chain Flows.
- Data produced by supply chains.
Python Programming Fundamentals Module includes:
1- Basics of Python
2- Data cleaning and Manipulation.
3- Statistical analysis.
4- Data Visualization.
5- Advanced Programming.
Supply chain Applications Module include
1- Product segmentations single and Multi-criteria.
2- Supplier segmentations.
3- Customers segmentations.
4- Forecasting techniques and accuracy testing.
5- Linear Programming and logistics optimizations.
6- Pricing and Markdowns optimization Techniques.
7- Inventory Policy and Safety stock Calculations.
8- Inventory simulations.
9- Machine Learning for supply-chain.
10- Simulations for optimizing Capacity and Resources.
*NOTE: Many of the concepts and analysis I explain first in excel as I find excel the best way to first explain a concept and then we scale up, improve and generalize with Python. By the end of this course, you will have an exciting set of skills and a toolbox you can always rely on when tackling supply chain challenges. The course may take from 12-16 weeks to finish, 4-5 hours of lectures, and practice every week.