Supply Chain Demand forecasting with Python

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Jayakhanthan Sakthivel

2:27:15

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1 - Introduction to time series forecasting in python

1 - Introduction to moving average forecasting.mp4

01:57

1 - data to perform the analysis.zip

1 - link to python code jupyter notebooks.zip

2 - Learn to clean and prepare time series data in python.mp4

07:18

3 - Build a function for moving average forecast.mp4

11:18

4 - Visualize the time series forecast forecast results.mp4

04:11

2 - Measure forecast accuracy

5 - Forecast Bias.mp4

13:39

6 - 2.2.6.Mean-Absolute-Percentage-Error-MAPE.mp4

07:41

6 - Mean Absolute Percentage Error MAPE.mp4

07:41

7 - Mean Absolute Error MAE.mp4

03:46

8 - Root Mean Square Error RMSE.mp4

07:09

3 - Advanced time series forecasting models

9 - Weighted Moving Average.mp4

09:31

10 - Optimize parameters in Weighted Moving Average Forecast.mp4

08:08

11 - Single Exponential Smoothing.mp4

13:35

12 - Optimize Alpha Parameter for Single Exponential Smoothing.mp4

10:55

13 - Double Exponential Smoothing.mp4

18:19

14 - Double Exponential Smoothing with Damped Trend.mp4

08:25

15 - Triple Exponential Smoothing.mp4

13:42

Description

Learn to build advanced time series demand forecasting models in python

What You'll Learn?

Timeseries data cleaning and preparation
Implement simple moving average forecast in python
Learn different KPIs (Bias, MAPE, MAE, RMSE) to measure forecast accuracy & implement in Python
Implement weighted moving average forecast & optimize parameters in python
Implement single exponential smoothing model in python
Implement double exponential smoothing model in python
Implement double exponential smoothing with damped trend
Implement triple exponential smoothing model in python
Simulate and optimize Alpha, Beta, Gamma and Phi parameters for automatic model selection
Calculate error KPIs for each models
Visualize the results with actuals, forecast and forecast errors

Who is this for?

Supply chain analysts

Demand planners

Supply chain students

Supply chain planners

Store managers

Supply chain consultants

More details

Description
Understanding and predicting the demand is one of the key challenge in Supply chain planning. Having better forecasting meaning better supply planning and optimized business operations with good customer service, therefore learn to build better forecast is a key skill to master in Supply chain management. Demand forecasting sounds simple but it will get complex when we have thousands of SKUs and each with its own demand pattern such as seasonal, intermittent and lumpy.
In this course you will learn demand forecasting models from basic to more advanced. And implement each of the models in Python. You will gain practical knowledge with real life data with over 3000 skus and over 5 years of data and millions of transactions.
By the time you complete the course you would have learned how advanced demand forecasting engine works in expensive commercial software and you would build your own fully automated forecasting engine.
In this course you will not only learn to build forecasting models and predict demand but also learn to build a python tool which can automatically optimize and select the best forecasting model based on your data.
Last but not least, you will learn to visualize all the forecasted data and errors in an intutive way.

Who this course is for:
Supply chain analysts
Demand planners
Supply chain students
Supply chain planners
Store managers
Supply chain consultants

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Jayakhanthan is a Supply Chain Analytics Expert based in Singapore. He has extensive knowledge and experience in optimizing and solving real life supply chain problems with the use of Python programming and Data Science. Jayakhanthan has worked with industries ranging from FMCG, Automotive, Mining, Oil & Gas, Logistics and Ecommerce. His experience in applying data science across varies supply chain topics such as inventory optimization, network optimization, S&OP, demand forecasting and supply chain simulation enables him to bring his practical solution based approach to data science in supply chain.All the courses designed and delivered by Jayakhanthan will focus on solving practical supply chain problems with data science.

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