Using R for Data Science and Supply Chain Analytics
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.
Data Science | core | 37 hours | Published: Aug 2021
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Overview
1.7KSTUDENTS*
94.9%RECOMMEND*
This course includes:
37 hours on-demand video
126 downloadable resources
Full lifetime access
Certificate of completion
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:
Basics of python
Data cleaning and manipulation.
Statistical analysis.
Data visualization.
Advanced programming.
Supply chain Applications Module include :
Product segmentations single and multi-criteria.
Supplier segmentations.
Customers segmentations.
Forecasting techniques and accuracy testing.
Linear Programming and logistics optimizations.
Pricing and markdowns optimization techniques.
Inventory policy and safety stock calculations.
Inventory simulations.
Machine learning for supply-chain.
Simulations for optimizing capacity and resources.
Skills You Will Gain
Data Science
Inventory Management
Linear Programming
Python
Supply chain
Learning Outcomes (At The End Of This Program, You Will Be Able To...)
Work as a demand planner.
Become a data driven supply chain manager.
Use linear Programming in python for logistics optimization and production scheduling.
Set stock policies and safety stocks for all of your business products.
Revenue management
Segment customers, products and suppliers to maximize service levels and reduce costs.
Learn simulations to make informed supply chain decisions.
Become a supply chain data scientist.
Learn Supply chain techniques you will only find in this course. Guaranteed!
Prerequisites
Basic knowledge of excel.
Who Should Attend
If you are an absolute beginner at coding.
If you work in a supply-chain and want to make data-driven decisions, this course will equip you with what you need.
If you are an inventory manager and want to optimize inventory for 1000000 products at once, then this course is for you.
If you work in finance and want to forecast your budget by taking trends, seasonality, and other factors into account then this course is just what you need.
If you are a seasoned R user, then take this course to get up to speed quickly with python capabilities. You will become a regular python user in no time.
Curriculum
Instructors
*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Welcome to the course!
2Module 1: Introduction
3Module 2: Supply Chain Data
4Module 3: Installation and Overview of R
5Module 4: R Programming fundamentals
6Module 5: Supply Chain Statistical Analysis
7Module 6: Data Cleaning and Manipulation
8Module 7: Working with Dates in R
9Module 8: Visualize with ggplot2 and Plotly
10Module 9: Supplier and Products Segmentation
11Module 10: Forecasting Basics
12Module 11: Time Series Forecasting
13Module 12: Forecasting Aggregation
14Module 13: Product Segmentation for Demand Planning
15Module 14: Supply Chain Simulations
16Module 15: Inventory Basics
17Module 16: Inventory with Uncertainty
18Module 17: Inventory Simulations
19Module 18: Seasonal Inventory
20Module 19: Consumer Behavior and Pricing
21Module 20: Optimizing the Price for Single Product
22Module 21: Multi Product Optimization
23Module 22: Markdowns and Time Based Discounts
24Module 23: Customer Segmentation
25Module 24: Machine Learning
About this course: Overview, Learning Outcomes, Who Should Enroll...
Segment - 19 - Welcome to the World of R
Segment - 20 - What is R Statistical Language
Segment - 21 - How to Install R
Segment - 22 - How to Install R Studio
Segment - 23 - A Walk Through Tutorial
Segment - 24 - Setup your Project
Segment - 25 - Install Packages!
Segment - 26 - Summary
Segment - 01 - Why I Chose R for this Course
Segment - 02 - Why We Should Learn Coding
Segment - 03 - Curriculum
Segment - 04 - Supply Chain Visualization
Segment - 05 - Cost and Service Dynamics
Segment - 06 - Service Level and Product Characteristics
Segment - 07 - Customer and Supplier Characteristics
Segment - 08 - Supply Chain Views
Segment - 09 - The Financial Flow
Segment - 10 - Why is Supply Chain Complicated
Segment - 11 - Introduction
uSegment - 12 - Types of Data in Supply Chain
Segment - 13 - Data from Suppliers
Segment - 14 - Data from Production
Segment - 15 - Data from Stocks
Segment - 16 - Data from Sales and Customers
Segment - 17 - Why We Need to Learn Data Science
Segment - 18 - Analytics Types
Segment - 27 - Introduction
Segment - 28 - Different Data Structures and Types in R
Segment - 29 - Do Arithmetic Calculations in R and Write Functions
Segment - 30 - Creating a List
Segment - 31 - Importing Data in R and Basic Exploration
Segment - 32 - Selecting Data in Dataframe
Segment - 33 - If Else Function
Segment - 34 - Conditions
Segment - 36 - For Loops
Segment - 35 - Functions With Conditions
Segment - 37 - Applying a Function Inside a For Loop
Segment - 38 - For Loop on a Dataframe
Segment - 39 - Applying the Function on a Dataframe
Segment - 40 - Assignment
Segment - 41 - Assignment Section 4 Answer Part 1
Segment - 42 - Assignment Section 4 Answer Part 2
Segment - 43 - Summary
Haytham Omar
He brings a wealth of expertise in supply chain management and data science to the online education platform. With a deep-rooted background in strategic consulting and academic instruction, he has held pivotal roles in optimizing global supply chains and pioneering data-driven solutions. Holding a doctoral degree focused on basket data-driven forecasting and inventory management, his research has significantly advanced understanding in omni-channel logistics. He has cultivated this knowledge through extensive hands-on experience and academic pursuits, including a Master’s in Global Supply Chain Management from KEDGE Business School and a MicroMasters in Supply Chain Management from MITx on edX.
Throughout his career, he has championed numerous innovative projects in collaboration with international institutions and corporations. His contributions extend beyond theoretical frameworks to practical implementations that enhance operational efficiency and profitability. Notably, he has developed specialized courses and workshops covering diverse aspects of supply chain management, from purchasing and inventory control to logistics optimization and lean management. His teaching approach blends rigorous academic insights with real-world applications, empowering learners to navigate complex supply chain challenges with confidence.
As an instructor on the platform, he is dedicated to equipping students with essential skills in supply chain analytics, data-driven forecasting, and strategic management. His courses are designed to foster critical thinking and problem-solving abilities, essential for navigating the dynamic landscapes of global business operations. Whether aspiring supply chain professionals, business owners seeking to optimize logistics, or data enthusiasts looking to delve into practical applications, learners gain invaluable insights and actionable knowledge from his expertise.
