RA: Data Science and Supply chain analytics.(A-Z with R)

Learn R,Supply-chain Data Science, Inventory Optimization,Big Data forecasting, Machine learning and Revenue Management.

4.58 (351 reviews)
Udemy
platform
English
language
Data & Analytics
category
3,628
students
39.5 hours
content
Aug 2023
last update
$69.99
regular price

What you will learn

A-Z Guide to Mastering R for Data Science.

Work as A demand Planner.

Become a data driven supply chain manager.

Become a data driven sourcing manager.

Set stock policies and safety stocks for all of your Business products.

Increase profit of your business with pricing optimizations.

Offer product recommendations for your customers.

Segment Customers, Products and suppliers to maximize service levels and reduce costs.

Learn simulations to make informed supply chain decisions.

Forecast and analyze all of your products at once.

Move Beyond Excel, analyze and make decisions at scale!!

Move to Consultancy with your new acquired skills in this course.

Become a supply chain data scientist.

Learn the Power of Data Science in Supply Chain.

Learn Supply chain techniques you will only find in this course. Guaranteed!

Description

*Update: machine learning forecasting with tidy models is added in the last chapter (Aug 2023)



made by a supply chainer for supply chainers.  A course designed for the modern supply chain profession.


" 60000 Professionals are using inventorize across R & Python. Know how to use it only in this course"


It's been seven years since I moved from Excel to R and since then I have never looked back! With eleven years between working in Procurement, lecturing in universities, training over 70000 professionals in supply chain and data science with R and python, and finally opening my own business in consulting for five years now. I am extremely excited to share with you this course and learn with you through this unique rewarding course. My goal is that all of you become experts in data science and supply-chain. I have put all the techniques I have learned and practiced in this one sweet bundle of data science and supply chain.

As a consultancy, we develop algorithms for retailers and supply chains to make aggregate and item controllable forecasting, optimize stocks, plan assortment and Maximize profit margin by optimizing prices. 13000 people are already using our free package for supply chain analysis "Inventorize" and we can't wait to share its capabilities with you so you can start dissecting supply chain problems...for free!

The motivation behind this project is filling the gap of finding a comprehensive course that tackles supply chains using data science. there are courses for data science, forecasting, revenue management, inventory management, and simulation modeling. but here we tackle all of them as a bundle. Lectures, Concepts, codes, exercises, and spreadsheets. and we don't present the code, we do the code with you, step by step.

the abundance of data from customers, suppliers, products, and transactions have opened the way for making informed business decisions on a bigger and more dynamic scale that can no longer be achieved by spreadsheets. In this course, we learn data science from a supply chain mindset.

Don't worry If you don't know how to code, we learn step by step by applying supply chain analysis!

*NOTE: Full course includes downloadable resources and R project files, homework and course quizzes, lifetime access, and a 30-day money-back guarantee.

Who this course is for:

· If you are an absolute beginner at coding, then take this course.

· If you work in supply-chain and want to make data-driven decisions, this course will equip you with what you need.

· If you work as a demand planner and want to make aggregate and item controllable forecasting, take this course.

· 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 R capabilities. You will become a regular R user in no time.

· If you want to take a deep dive (not just talking) in supply chain management, then take this course.

· If you want to apply machine learning techniques for supply -chain, we will walk you through the methods of supervised and unsupervised learning.

· If you are switching from Excel to a data science language. then this course will fast track your goal.

· If you are tired of doing the same analysis again and again on spreadsheets and want to find ways to automate it, this course is for you.

· If you are frustrated about the limitations of data loading and available modules in excel, then Moving to R will make our lives a whole lot easier.


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.



Happy Supply Chain mining!

Haytham

Rescale Analytics


Feedback from Clients and Training:


"In Q4 2018, I was fortunate to find an opportunity to learn R in Dubai, after hearing about it from indirect references in UK.


I attended a Supply Chain Forecasting & Demand Planning Masterclass conducted by Haitham Omar and the possibilities seemed endless. So, we requested Haitham to conduct a 5-day workshop in our office to train 8 staff members, which opened us up as a team to deeper data analysis. Today, we have gone a step further and retained Haitham, as a consultant, to take our data analysis to the next level and to help us implement inventory guidelines for our business. The above progression of our actions is a clear indication of the capabilities of Haitham as a specialist in R and in data analytics, demand planning, and inventory management."


Shailesh Mendonca

Commercial lead-in Adventure AHQ- Sharaf Group



“ Haytham mentored me in my Role of Head of Supply Chain efficiency. He is extremely knowledgebase about the supply concepts, latest trends, and benchmarks in the supply chain world. Haytham’s analytics-driven approach was very helpful for me to recommend and implement significant changes to our supply chain at Aster group”

Saify Naqvi

Head of Supply Chain Efficiency



“I participated to the training session called "Supply Chain Forecasting & Management" on December 22nd 2018. This training helped me a lot in my daily work since I am working in Purchase Dpt. Haytham have the pedagogy to explain us very difficult calculations and formula in simple way. I highly recommend this training.”

Djamel BOUREMIZ

Purchasing Manager at Mineral Circles Bearings




Content

Introduction

Why I chose R for this course ?
Why we should Learn Coding.
Curriclum
Supply chain Visualization
Cost and Service Dynamics.
Service level and Product Characteristics
Customer and Supplier Characteristics
Supply chain Views
The Financial Flow
Why is supply chain Complicated

Supply chain Data!

Introduction
Types Of Data in supply chain
Data From suppliers
Data From Production
Data From Stocks
Data From Sales & Customers
Why we Need to learn Data Science?
Analytics Types

Installation and Overview of R

Welcome to the World of R!
What is R statistical Language.
How to Install R
How To install Rstudio
A walk through Tutorial
setup your Project!
install Packages!
Summary

R programming Fundmentals.

Introduction
Different Data Structures and types in R
Do arithmetic Calculations in R and write vectors
Creating a list
Importing Data in R and basic Exploration functions
Selecting Data in dataframe.
Writing Functions in R and for loops
for loops 2
Assignment
Summary

Supply Chain Statistical Analysis

Intro
Calculating Measures of Centrality and spread 1
Calculating Measures of Centrality and spread 2
Calculating Measures of Centrality and spread 3
Correlations
Calculating Correlations
Intro to Linear Regression
Linear Regression
Intro to Distributions.
Distributions
Distributions in Excel
Distributions Chi-Square test
Cover for 90% of the Normal Distribution
Assignment Distributions in Excel
Distributions in R
Assignment
Summary

Data Cleaning and Manipulation.

Intro
Intro To Dplyr
Investigate with Dplyr
Investigate with Dplyr 2
Joining
Restructure data with tidyR 1
Restructure data with tidyR 2
Separate and paste
putting it all together
Assignment: New York airlines
Summary

Working with Dates in R.

Intro.
Motivation for working with dates
Parsing dates with R.
Make inference from dates in R
Woking with Lubridate
Modeling inter-arrival time of Customers 1
modeling inter arrival time of customers 2
Assignment
Summary

Visualize with ggplot2 and Plotly.

Introduction
line plots
scatter plots
Barplots
Distribution Plots
Boxplots
Histograms
Histograms 2
Assignment.
Summary

Suppliers and Products Segmentation.

Intro
Intro to segmentation
Why we need segmentation in our supply chain?
Multi- Criteria segmentation.
Transforming the data for excel
ABC_Analysis_in Excel
Assignment Explanation
ABC_analysis in R
Multi-Criteria ABC analysis
Multi-Criteria ABC analysis_store level
Assignment
Supplier Segmentation.
Supplier Segmentation 2
Krajic in R
Visualizing Krajic
Summary

Forecasting Basics.

Why We Need Forecasts
Qualitative and Quantitative Forecasting
Optimistic and Pessimistic Forecasting
Preparing the Data for regression
Changing the format of posixct to date.
Multiple linear Regression in Excel
Assignment Explanation
Validating forecast and adding more regressors
fitting the second model
Measuring forecasting accuracy
fitting forecast with Regression_in_R
Forecasting with linear regression in R
Assignment.
Summary

Time-Series Forecasting

Introduction To Time series forecasting
Converting data to time-series
Weekly and Daily time_series
Analyze the time series
De-sasonalizing and de-Tending the data.
Dissecting components inside R
Measuring strength of trend and seasonality.
Forecasting models
Accuracy Measures for forecasting
Determine Arima Orders
Training and testing
Dynamic Harmonic regression
Measuring accuracy Of new model
Assignment
Summary

Forecasting Aggregation

Intro
Hierarchal and Grouping
Aggregation approaches
Preparing the data for aggregation
Hierarchal Structuring
Aggregate forecasting
Testing and Accuracy for aggregation
Comparison between Middle out, Bottom Up and Top Down
Assignment
Summary

Products segmentation for Demand Planning.

Intro
Product's Classifications for forecasting.
Checking for holidays
SKU grouping by date
Customizing a holiday count Function
For-looping the holiday function
Calculating Average demand intervals and CV squared.
Visualizing the classification
Assignment
Summary

Supply chain Simulations

Intro
Waiting Line and Queue theory.
Example Demonstration
Waiting line in excel
Simulation assignment
Waiting lines in R
Making 400 Simulations At once.
Waiting Line in call centre
Defining the Right K
Simulation With Capacity Constraints
Assignment
Sequential services in one system
Many Services
Multiple Service simulations in R
Conclusion
Assignment
Summary

Inventory Basics

Intro
Why we need inventory?
Inventory Strategies
Inventory Types and EOQ
Total Logistics Cost and total relevant cost
Economic Order Quantity With Excel
EOQ with quantity discounts
Eoq Sensitivity
EOQ with inventorize
T practical in R
EOQ with Lead Time.
Practical Example inside R
Assignment
Summary
Summary 2

Inventory with Uncertainty

Intro
Uncertainty and Variability in supply chain
Demand Lead-time and Sigma DL
Calculating average daily demand
Method 1 for safety stock calculation.
Method 2 for safety Stock Calculation
Preparing SKUs for safety stock calculations.
Calculating average demand and sd
Setting Cycle service level in R
Calculating re-order point with inventorize
Calculating re-order point with lead time variability
Lead Time Variability in Excel
lead Time Variability with Inventorize.
Wrap for Indeterministic Inventory
Assignment
Summary

Inventory Simulations

Introduction to Inventory Policies
Min Q Demonstration
Min Q policy
Min,Q example in excel
Periodic Review Demonstration.
Periodic Review Policy
Excel Example for periodic review.
Min Max Demonstration.
Min Max Policy
Min Max Example in Excel
Base Stock Demonstration.
Base Stock Policies
Base stock Policy_Example
Assignment
Simulating (s,Q) Policy
Comparing Ordering quantity with Inventorize
Visualizing the simulation
Poisson Min-Max Simulation
Visualizing variations of one policy!
Visualizing all policies.
Metrics Comparison
Assignment.
Summary

Seasonal Inventory

Introduction
Seasonal Products
Point of maximum Profit
How much I will sell ?
Data Table
Critical Ratio
Critical Ratio in Excel
What's Actually happening.
Critical Ratio in R with inventorize
Expected Profit with Inventorize
Preparing the data for Calculating Maximum Profit
A practical Supply chain Example
Apply MPN to all seasonal products.
Assignment
Summary

Consumer Behavior and Pricing

Revenue Management
Pricing History
Why is Pricing important?
Customer's perception of Price.
Pricing Mechanisms
Commodities
Price response Function
Price Response Function Motivation In R.
Assignment
Elasticity Intro
Elasticity
Linear Elasticity with Inventorize
Practical Example: Preparing the data for modeling
Modeling all retail SKUs at once.
Optimum Price for All Skus
Optimum Pricing validation
Assignment
Summary

Optimizing the Price for a single product.

intro
Intro to logistic regression
Logit modeling with inventorize
Assignment

Multi-Product Optimization

Intro
Competing Products.
The Co-relation Among products
Multi-Variate Regression fitting.
Relation_among_products
ANOVA
Updating the model
Assignment
Comparing between the two models
Prediction with Multivariate regression
multinomial choice models
Optimizing competing prices with Inventorize
Results of Optimization
Applying the Algoritm on 40000 Observations
Assignment
Summary

Markdowns and Time-based Discounts

Intro
Markdowns
Why We do Markdowns
Customers Segments to Markdowns
Problem Formulation
Markdowns for Multiple periods.
Setting Up Solver
Solver with salvage Value
Markdowns with forecasting
Sensitivity analysis
Markdowns for one period
Assignment

Customer Segmentations.

RFM Analysis
Segmentation of customers based on RFM Analysis.
Preparing the data.
Recency
Joining KPIs together.
Visualization
Ranking
Grouping into tiles.
3D scatterplots
Demo
Assignment

Machine Learning

Intro To machine learning
Decision tree demo
Kmeans
Overfitting
Kmeans in R
Total sum of squares
Silhouette
Interactive three dimensional scatter plot.
Assignment
Supervised learning : Linear regression.
Supervised Learning : Decision Trees and random forest.
Comparing Models
Classification data orientation
Exploring the data
Correlation matrix
Splitting
Training and Testing
Control the fitting.
Logistic Regression Classification.
Probabilities of the logistic Regression
Confusion Matrix
ROC
Decision tree model
Assignment
Conclusion
Summary

Association Rules

Introduction
Intro to Market basket analysis
Top 10 Products
Reading Transactions.
Summary of Transactions
Apriori
Top 10 rules
Subsetting
Assignment

Bonus Webinar! Noble Prog

Introduction To Webinar
Webinar

Screenshots

RA: Data Science and Supply chain analytics.(A-Z with R) - Screenshot_01RA: Data Science and Supply chain analytics.(A-Z with R) - Screenshot_02RA: Data Science and Supply chain analytics.(A-Z with R) - Screenshot_03RA: Data Science and Supply chain analytics.(A-Z with R) - Screenshot_04

Reviews

Wanyi
October 19, 2023
it made me notice the necessity of using a programming language to handle the daily work of a SC staff, and depicted what i will go through over the course, thanks!
Sundaram89250
August 23, 2022
This is wonderful course - As a beginner I just completed 67 videos - it give me lot of information both theory and practical
Deepak
June 3, 2022
Yes,the course is a good match & so far the way the explaination is given is very good for making us understand.
José
June 2, 2022
Hola, es buena elección, solamente los subtitulos tienen el problema de que no interpreta bien al expositor, por ejemplo: mother en lugar de model, para que sea revisado.
Edwin
January 3, 2022
Haitham has put together a very solid course. The right mix of theory (just the barest minimum), programming and even Excel. Although, I am moving away from excel to R and python, I agree there is no better application for explanations than Excel. The course is just amazing!! The course is what I have been looking for. This is how Supply chain should be taught at universities, not just using proprietary software like AMPL, SPSS, Arena etc but using open source programming languages. The examples are not toy examples with simple fictitious data but "real life-looking" data, probably from an ERP system and other sources that may involves significant amount of data cleaning. There is a great blend of Base R and Tidyverse that pushes you to see the relevance of knowing both of them. The course is intensive and helps provide a solid background for understanding supply chain concepts and most importantly, creates the basis for solving real-world complex supply chain problems (with thousands of skus). This course is wake-up call to us all that there is data everywhere in our activities/operations and we just need to get the data and analyze them!!
Manuel
December 11, 2021
Muchas veces las presentaciones ayudan a asimilar mejor la información. Más adelante vi que si tenía mucho material visual.
Qasim
November 14, 2021
Very good course. The lecturer have very good knowledge on supply chain and utilizes R perfectly. I highly recommend this course. You get a bonus as you skill up your R programming.
Naffisa
October 22, 2021
So far the course is very interesting and easy to keep up with the instructor . it doesn’t seem complicated and the breakdown of the sessions helps you stay focused .
Wesley
August 26, 2021
A fantastic course, you truly learn a lot and Haytham is very quick with his responses to any questions you may have. You will be able to use some of the skills and techniques that he goes through. This course was worth every cent.
Rohan
January 21, 2021
Course content is good for a beginner to understand supply chain issues but the overall course is not well organized . As a result it takes too much time for one to quickly understand the challenges or problems in supply chain and understand where data science can play an important role.
Ruchi
January 20, 2021
It is one of the best course to understand the need of analytics in supply chain industries. I did several course but I never find any domain specific analytics course with detailed explanation. I really enjoyed the Haytham way of explaining. Thanks for all your efforts !!!
Abdurohman
January 18, 2021
The course is beyond my expectation from the completeness of the lessons point of view related to supply chain management. totally worth the price. I wish there are more people like this guy who is an actual expert giving lectures instead of the academics people. there are some deficiency though but on a very small percentage, such as inconsistencies of codes or variables naming. but as long as you pay attention and understand what this guy is doing at the moment, this is not much of a problem.
Aravind
January 3, 2021
Well, I haven't completed the course yet, but from what i see, it has been great. As a supply chain student about to graduate, this course is tailor made for Analytics knowledge that we are ought to have in our Arsenal. Thank you for thinking of students when you made this course. 38 hours of course is completely worth it.
Kavin
December 2, 2020
I am in the beginning of the course and the instructed has structured the course well. It shows his expertise in the field. Looking forward to see howthe resr of the course goes.
Ahmed
November 8, 2020
Best Course available for Supply Chain showcasing how to leverage the Analytics in this industry...And the Instructor is having good business acumen and he knows the subject very well

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10/19/202189% OFF
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3/9/2023100% OFF
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3229795
udemy ID
6/12/2020
course created date
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