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AI410: Sales Forecasting and Inventory Optimization with Machine Learning

Training: Artificial Intelligence

Participants receive a practical introduction to time series analysis and machine learning for sales forecasting. The course covers the analysis of retail data with Python, statsmodels, and scikit-learn. It addresses inventory optimization using bootstrapping, forecasting models for stock planning, and practical exercises for implementation.

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Possible course languages: German

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Agenda:

Motivation, data preparation and exploratory data analysis in Pandas and Matplotlib

Time series analysis fundamentals with statsmodels
- Autocorrelation
- ARMA models
- Regression
- Trends
- Stationarity
- Forecasting
- Forecast evaluation

ML forecasting with scikit-learn
- Regularization
- Random Forests etc.

Calculate forecast intervals using bootstrapping and optimize inventory management and ordering

Final discussion

Objectives:

Understand fundamentals of time series analysis, develop models for sales forecasting, optimize inventory management and ordering processes.

Target audience:

Developers
IT Professionals

Prerequisites:

To effectively follow the learning pace and content of the training AI410 Sales Forecasting and Inventory Optimization with Machine Learning, we recommend prior participation in the following courses:

Alternatively, prior knowledge in the following areas is required:

Python programming fundamentals
Data extraction and data preprocessing
Machine Learning

Description:

The participants of the workshop AI410 Sales Forecasting and Inventory Optimization with Machine Learning learn how to utilize time series analysis and machine learning models in Python to forecast sales. Specifically, a dataset will be analyzed to analyze and forecast sales of various retail products.

Using the developed models, you can calculate how many products a company should keep in inventory and optimize the number of orders. The course covers a broad range of topics, including fundamentals of time series analysis with statsmodels, ML forecasting with scikit-learn, and inventory optimization through bootstrapping.

Please also note the content-related module AI412 Time Series Analysis for Financial Data with Machine Learning.