A Deep Dive into Forecasting- Excel & R.
A Deep Dive into Forecasting- Excel & R., available at $64.99, has an average rating of 4.25, with 184 lectures, 1 quizzes, based on 119 reviews, and has 18076 subscribers.
You will learn about Time Series Decomposition. Univariate analysis for time series Bivariate analysis and auto-correlation Smoothing the time series seasonally adjusting the time series Generating and Calibrating Forecasting in Excel Learning R and using it as everyday tool for forecasting. Using the Fable Package for advanced forecasting methods and aggregations Time Series Forecasting Different Applications of forecasting R Fable Business Forecasting Excel tidymodels This course is ideal for individuals who are Planners or Strategists or Retail merchandise or Financiers or Supply chain or Economists or Operation managers or Budgeters It is particularly useful for Planners or Strategists or Retail merchandise or Financiers or Supply chain or Economists or Operation managers or Budgeters.
Enroll now: A Deep Dive into Forecasting- Excel & R.
Summary
Title: A Deep Dive into Forecasting- Excel & R.
Price: $64.99
Average Rating: 4.25
Number of Lectures: 184
Number of Quizzes: 1
Number of Published Lectures: 183
Number of Published Quizzes: 1
Number of Curriculum Items: 185
Number of Published Curriculum Objects: 184
Original Price: $84.99
Quality Status: approved
Status: Live
What You Will Learn
- Time Series Decomposition.
- Univariate analysis for time series
- Bivariate analysis and auto-correlation
- Smoothing the time series
- seasonally adjusting the time series
- Generating and Calibrating Forecasting in Excel
- Learning R and using it as everyday tool for forecasting.
- Using the Fable Package for advanced forecasting methods and aggregations
- Time Series Forecasting
- Different Applications of forecasting
- R
- Fable
- Business Forecasting
- Excel
- tidymodels
Who Should Attend
- Planners
- Strategists
- Retail merchandise
- Financiers
- Supply chain
- Economists
- Operation managers
- Budgeters
Target Audiences
- Planners
- Strategists
- Retail merchandise
- Financiers
- Supply chain
- Economists
- Operation managers
- Budgeters
update : machine learning forecasting is added as the last chapter (Aug 2023)
Hello 🙂
Forecasting has been around for 1000s of years. it stems from our need to plan so we can have some direction for the future. We can consider forecasting as the stepping stone for planning. and that’s why it is as important as ever to have good forecasters in institutions, supply chains, companies, and businesses.
With the ever-growing concerns of sustainability and Carbon-footprint. Would you believe it? a good forecast actually contributes to saving resources through the value chain and actually saving the planet. one forecaster at a time. needless to mention, forecasting is integral in marketing, operations, finance, and planning for supply chains. Pretty much everything
This course is aimed to orient you to the latest statistical forecasting techniques and trends. but first, we need to understand how forecasting works and the reasoning behind statistical methods, and when each method is suitable to be used. that’s why we start first with excel and we scale with R. “Don’t worry if you don’t know R, Crash fundamental sections are included!.
the course is for all levels because we start from Zero to Hero in Forecasting.
in this course we will learn and apply :
1- Time Series Decomposition in Excel and R.
2- Univariate analysis for time series in Excel and R.
3- Bivariate analysis and auto-correlation in Excel and R.
4- Smoothing the time series and getting the Trend with Double and centered moving average.
5- seasonally adjusting the time series.
6- Simple and complex forecasts in Excel.
7- Use transformations to reduce the variance while forecasting.
8-Generating and Calibrating Forecasting in Excel.
9- Learning R and using it as an everyday tool for forecasting.
10- Using the Fable Package for advanced forecasting methods and aggregations.
11- Using Forecast package for grid search on ARIMA.
12- Applying a workflow of different models in two lines of code.
13- Calibirating forecasting methods.
14- Applying Hierarchical time series with Bottom-up, middle out, and Top-down Approaches.
16- Use the new R-Fable reconciliation method for aggregation.
15- Using Fable to generate forecasts for 10000 time-series and much more !!
*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 forecasting challenges.
Happy Forecasting!
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 has the pedagogy to explain us very difficult calculations and formula in a simple way. I highly recommend this training.”
Djamel BOUREMIZ
Purchasing Manager at Mineral Circles Bearings
Course Curriculum
Chapter 1: Introduction
Lecture 1: Hello.
Lecture 2: Forecasting is the stepping stone of planning
Lecture 3: Time Series
Lecture 4: Difficulties in forecasting
Lecture 5: Forecasting applications
Lecture 6: Forecasting in inventory management
Lecture 7: Different Forecasting Methods
Lecture 8: 2020 and COVID
Lecture 9: Time Series analysis
Lecture 10: Causal Methods
Lecture 11: Stationarity of the data
Lecture 12: Summary
Chapter 2: Time Series and Pattern extraction
Lecture 1: Introduction
Lecture 2: Univariate Statistical analysis
Lecture 3: Univariate Part2
Lecture 4: Bivariate Statistics
Lecture 5: Auto-Correlation
Lecture 6: Assignment
Lecture 7: Assignment Solution
Lecture 8: Summary
Chapter 3: Simple Forecasting Methods
Lecture 1: Simple Forecasting methods
Lecture 2: Naive and Seasonal Naive
Lecture 3: Mean Percentage error
Lecture 4: Seasonal average
Lecture 5: Mean absolute scaled error
Lecture 6: Simple exponential smoothing and log transformations
Lecture 7: Simple forecasting Methods
Lecture 8: Naive and Simple forecasting methods
Lecture 9: linear Regression , Custom weighted moving average and SES
Lecture 10: Optimizing the Parameters
Lecture 11: Best Simple Forecasting Method
Lecture 12: Simple Forecasting assignments
Lecture 13: Solution
Lecture 14: Summary
Chapter 4: Double Moving average, Centered Moving average and Decomposition.
Lecture 1: Introduction
Lecture 2: Moving averages
Lecture 3: Detrending the series
Lecture 4: Time series Decomposition
Lecture 5: Additive Decomposiition
Lecture 6: Multiplicative Decomposition
Lecture 7: Assignment
Lecture 8: Decomposition solved
Lecture 9: Summary
Chapter 5: Exponential Smoothing
Lecture 1: Introduction
Lecture 2: Simple Exponential Smoothing
Lecture 3: Holt Exponential Smoothing
Lecture 4: Initialization of alpha and Beta
Lecture 5: Holt Model in Excel
Lecture 6: Holt-winters Explanation
Lecture 7: Additive Holt Winters Model
Lecture 8: 12 month Forecast with Holt Winters
Lecture 9: Multiplicative Holt-Winters
Lecture 10: 12 Month ahead with multiplicative exponential smoothing
Lecture 11: Assignment Holt
Lecture 12: Assignment Solution
Chapter 6: Multiple Linear Regression
Lecture 1: Introduction
Lecture 2: Intro to linear regression
Lecture 3: Multiple linear regression in excel
Lecture 4: Fitting the model
Lecture 5: shifting to R
Chapter 7: Welcome to R
Lecture 1: Welcome to the World of R!
Lecture 2: What is R statistical language?
Lecture 3: How to install R
Lecture 4: How to install Rstudio
Lecture 5: A walkthrough tutorial
Lecture 6: Setup your project
Lecture 7: install packages!
Lecture 8: Summary
Chapter 8: R fundmentals
Lecture 1: Introduction- r-Basics
Lecture 2: Different Data Structures and types in R
Lecture 3: Do arithmetic Calculations in R and write vectors
Lecture 4: Creating a list
Lecture 5: Importing Data in R and basic Exploration functions
Lecture 6: Selecting Data in dataframe.
Lecture 7: If Else function
Lecture 8: Conditions
Lecture 9: Functions with conditions
Lecture 10: For loops
Lecture 11: applying a function inside a forloop
Lecture 12: for loop on a data frame
Lecture 13: Applying a function on a dataframe
Lecture 14: Assignment
Lecture 15: Assignment section 4 answer Part1
Lecture 16: Assignment Section 4 answer Part 2
Lecture 17: Summary
Chapter 9: Working with dates in R
Lecture 1: Intro
Lecture 2: Motivation for working with dates
Lecture 3: Parsing Dates with R
Lecture 4: Make inference from dates in R
Lecture 5: Working with lubridate
Instructors
-
Haytham Omar-Ph.D
Consultant-Supply chain
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 2 votes
- 3 stars: 16 votes
- 4 stars: 32 votes
- 5 stars: 68 votes
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