• views: 191
• date: 22 November 2025
• posted by: voska89

What you'll learn
Build LSTM models for demand, ERP sales, and anomaly detection
Use ANN, MLP, DNN for cross sell, CLV, promotional success & regional sales analysis
Convert business datasets into deep learning training pipelines
Evaluate and deploy business prediction models in PyTorch
Requirements
Basic Python knowledge
No prior ML experience needed
No prior PyTorch experience needed
Understanding of CSV or Excel data
Description
Course DescriptionThis tutorial course provides a practical, business oriented introduction to deep learning using PyTorch. You will learn how to build predictive models that solve real industry problems, such as forecasting inventory demand using LSTM, predicting customer lifetime value, identifying cross sell opportunities with ANN, detecting sales anomalies, measuring promotion performance using MLP, and comparing regional sales with DNN models.Throughout this tutorial course, you will work hands on with real datasets, learn how to preprocess business data, design neural network architectures, train models step by step, evaluate accuracy, and interpret results for business decision-making. This tutorial course is designed to help professionals move from simple ML concepts to fully functional deep learning models used in retail, ERP, Finance, Supply chain, and CRM analytics. This Tutorial course primarily focuses on Applying deep learning techniques to solve real world business forecasting problems such as demand prediction, sales analysis, customer behavior forecasting, and promotional performance measurement.By the end of this tutorial course, you will be able toBuild LSTM models for demand, ERP sales, and anomaly detectionUse ANN, MLP, DNN for cross sell, CLV, promotional success & regional sales analysisConvert business datasets into deep learning training pipelinesEvaluate and deploy business prediction models in PyTorchIn this tutorial course, You will learn, how to build end to end predictive analytics models such asInventory demand predictor using LSTMCLV forecaster using PyTorchANN model for cross selling & repeat customer predictionLSTM model for sales trend & anomaly detectionMLP & DNN for promotional success & regional performance scoring
Who this course is for
Data Analysts
Machine Learning Pro
Business Intelligence Professionals
ERP, CRM, Finance Domain Users
Professionals who want to learn Predictive Modeling
Professionals preparing for AI, ML Job Roles
Homepage

https://www.udemy.com/course/pytorch-for-business-forecasting-predictive-analytics/

   
   
   

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