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Demand Forecasting
with Python

Build production-grade demand forecasting models in 8 weeks. From ARIMA to LSTM and Temporal Fusion Transformers — you train on real supply chain datasets, measure accuracy with MAPE/WAPE/bias, and deploy a forecasting pipeline your planning team can use on Monday.

🗓 Weekends⏱ 8 Weeks📊 48 Hours🇮🇳 ₹24,999🌍 $299
PYTHON FORECASTING
8
Weeks
48
Hours
6
Modules
12+
Models
5
Datasets
1
Capstone
🎯 Forecast Portfolio · Accuracy Dashboard · Certificate
ARIMA · SARIMA · ETS · Holt-Winters · XGBoost · LightGBM · LSTM · GRU · TFT · Prophet · NeuralProphet · MAPE · WAPE · Bias · Backtesting · pandas · statsmodels · PyTorch · scikit-learn · Feature Engineering · ARIMA · SARIMA · ETS · Holt-Winters · XGBoost · LightGBM · LSTM · GRU · TFT · Prophet · NeuralProphet · MAPE · WAPE · Bias · Backtesting · pandas · statsmodels · PyTorch · scikit-learn · Feature Engineering ·

Why Python Forecasting Is Essential

Supply chains run on data. The best teams use structured analytical methods — and they hire people who do too.

Who Is This Program For?

The Learning Roadmap

Each module includes live instruction, hands-on exercises with real datasets, and a graded assignment.

Tools & Libraries

Industry Case Studies

See It in Action

Python ARIMA Forecasting

Step-by-step supply chain time series

XGBoost Demand Forecasting

ML approach with feature engineering

Facebook Prophet Tutorial

Seasonal & holiday demand forecasting

Build Something Real

Choose your capstone track and build a production-ready model you can present to management or add to your portfolio.

Roles This Course Unlocks

📄 Download the Mathnal Training Brochure

Complete program deck with course details, curriculum, pricing and career outcomes for all Mathnal training programs.

Got Questions?

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Program Fee: ₹24,999

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Inventory health check + forecast accuracy audit. No signup required.

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