A Deep Dive Into Forecasting with Excel and Python.

Forecasting with Excel & Python. Machine learning and statistical forecasting for Supply Chain.

4.88 (54 reviews)
Udemy
platform
English
language
Operations
category
A Deep Dive Into Forecasting  with  Excel and Python.
2,417
students
17.5 hours
content
Sep 2023
last update
$94.99
regular price

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 Python and using it as everyday tool for forecasting.

Using the sktime Package for advanced forecasting methods and aggregations.

Time Series Forecasting.

Different Applications of forecasting.

Python

Arima

Machine learning forecasting

hierarchal forecasting

Excel

Why take this course?


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 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 Python. "Don't worry if you don't know Python, 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 Python.

2- Univariate analysis for time series in Excel and Python..

3- Bivariate analysis and auto-correlation in Excel and Python..

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 Python and using it as an everyday tool for forecasting.

10- Using the sktime Package for advanced forecasting methods and aggregations.

11- Using statsmodels package for grid search on ARIMA.

12- Applying a workflow of different models in two lines of code.

13- Calibrating forecasting methods.

14- Applying Hierarchical time series with Bottom-up, middle-out, and Top-down Approaches.

16- Use the new sktime reconciliation method for aggregation.

15- Using Fable to generate forecasts for 10000-time series and much more !!

16- Time series feature Generation.

17-Resampling and Forecasting cross-validation.



Many of the concepts and analyses 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 forecasting challenges.


Happy Forecasting!

Haytham

Rescale Analytics



Feedback from Clients, Training and other online courses:

"I attended this course with high expectations. And I was not disappointed. It´s incredible to see what is possible with Python in terms of supply chain planning and optimization. Haytham is doing a great job as a trainer. Starting with explanation of basics and ending with presentation of advanced techniques supply chain managers can apply in real life."

Larsen Block

Director Supply Chain Management at Freudenberg Home and Cleaning Solutions GmbH




"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



Screenshots

A Deep Dive Into Forecasting  with  Excel and Python. - Screenshot_01A Deep Dive Into Forecasting  with  Excel and Python. - Screenshot_02A Deep Dive Into Forecasting  with  Excel and Python. - Screenshot_03A Deep Dive Into Forecasting  with  Excel and Python. - Screenshot_04

Reviews

Kriz
January 3, 2024
really informative. I'm a beginner in supply chain and its a struggle but this course did explain a lot to me even more on the python course.. thank you!

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5277398
udemy ID
4/17/2023
course created date
5/20/2023
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