What you’ll learn
• A-Z Guide to Mastering R for Data Science.
• Become a data driven supply chain manager.
• Set stock policies and safety stocks for all of your Business products.
• Offer product recommendations for your customers.
• Learn simulations to make informed supply chain decisions.
• Move Beyond Excel, analyze and make decisions at scale!!
• Become a supply chain data scientist.
• Learn Supply chain techniques you will only find in this course. Guaranteed!
• Work as A demand Planner.
• Become a data driven sourcing manager.
• Increase profit of your business with pricing optimizations.
• Forecast and analyze all of your products at once.
• Move to Consultancy with your new acquired skills in this course.
• Learn the Power of Data Science in Supply Chain.
• Segment Customers, Products and suppliers to maximize service levels and reduce costs.
Requirements
♦ Microsoft Excel
♦ Motivation to Learn R
♦ Motivation to use data on a bigger scale than excel
Description
Course Design
The course is designed as experiential learning Modules, the first couple of modules are for supply chain fundamentals followed by R 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 R-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:
1- Introduction to supply chain.
2- Supply chain Flows.
3- Data produced by supply chains.
R Programming Fundamentals Module includes:
1- Basics of R
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- Forecasting aggregation approaches.
6- Pricing and Markdowns optimization Techniques.
7- Inventory Policy and Safety stock Calculations.
8- Inventory simulations.
9- Machine Learning for supply-chain.
10- Product Recommendations for customers.
11- 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 R. 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.
*Bonus: one hour webinar of Intro to machine learning where I am the panelist for NOBLE PROG; the host and organizer of the webinar event. the webinar has a demo on how to use orange for data mining.