AI in Demand Forecasting and Inventory Management

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AI in Demand Forecasting and Inventory Management

Supply Chain Management (SCM) / Demand Planning

AI in Demand Forecasting and Inventory Management

Dominate the Market: Drive Efficiency with AI-Powered Forecasting & Inventory Control

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Intermediate

English

Marc Kloepfel

AI in Demand Forecasting and Inventory Management

This Course Includes:

2h 30m
27 Lectures
Full Lifetime Access
Access On Mobile And Tv
Certificate On Completion

At the Price of Just $49.00

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Overview

What will AIXplorers learn in this course?

Use the power of AI to predict demand with laser precision, ensuring you never miss a sale and always have the right stock at the right time.
Say goodbye to costly stockouts and overstocking! Learn how to use AI to optimize your inventory management, slash operational costs, and boost profits.
Automate your inventory and replenishment processes with AI, cutting down manual work, reducing errors, and making your supply chain a well-oiled machine.
Get hands-on experience with the top AI tools and learn how to easily integrate them into your operations to elevate supply chain performance.

What are the requirements or prerequisites for taking this course?

Basic Understanding of Supply Chain Concepts
Some experience working with data, whether through Excel, ERP systems, or other business analytics tools
A general curiosity or interest in Artificial Intelligence
Access to a Computer and Internet

Who is the course for?

Supply Chain Managers and Professionals
Business Leaders and Decision Makers
Data Analysts and IT Professionals
Technology Enthusiasts and Innovators
Professionals guiding companies in supply chain optimization or AI adoption

Description

Course Tags

ai Demand Forecasting Inventory Management Procurement artificial intelligence ai ixx

Course Content

8 Sections
27 Lectures
2h 30m Total Length

Section 1

Introduction to AI-Powered Demand Forecasting and Inventory Management

Step into the Future! Discover how AI is revolutionizing the supply chain world. Get ready to boost efficiency, cut costs, and take full control of your demand forecasting and inventory management.

Time 20m

Lectures 3

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Overview of Inventory Management

0:07:31

Basics of Demand Forecasting

0:06:27

Importance of AI in Modern Forecasting and Management

0:06:44

Section 2

Data Collection and Preprocessing

This section focuses on the types of data necessary for forecasting, and how to clean, prepare, and transform data to ensure it is accurate and ready for analysis by AI systems. By understanding these processes, participants will learn how to feed data into AI systems to optimize decision-making.

Time 16m

Lectures 3

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Types of Data Used in Forecasting

0:05:37

Data Cleaning and Preparation Techniques

0:05:24

Introduction to Data Normalization and Transformation

0:05:32

Section 3

Fundamentals of Machine Learning

This section provides a comprehensive overview of machine learning, focusing on its key concepts, how algorithms are trained, and their application in forecasting and inventory management. Participants will explore the differences between supervised and unsupervised learning and how to evaluate mach

Time 16m

Lectures 3

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Core Concepts of Machine Learning

0:05:04

Supervised vs Unsupervised Learning

0:06:12

Evaluating Machine Learning Models

0:04:44

Section 4

Time Series Forecasting

Time series forecasting is crucial in supply chain management. This section delves into understanding time-series data, its components, and how advanced forecasting models like ARIMA and exponential smoothing can be applied to make more accurate predictions.

Time 16m

Lectures 3

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Understanding Time Series Data

0:06:52

Common Time Series Forecasting Models

0:04:58

Advanced Techniques

0:04:23

Section 5

Machine Learning Models for Forecasting

This section dives into the different machine learning models used for forecasting, such as regression models, decision trees, and neural networks. Participants will understand the power of each model and how to implement them for more accurate forecasting and inventory management.

Time 18m

Lectures 4

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Regression Models

0:05:42

Decision Trees and Random Forests

0:04:04

Neural Networks and Deep Learning Approaches

0:04:16

RapidMiner and DataRobot

0:04:42

Section 6

Integrating AI into Inventory Management

This section discusses the practical application of AI in automating key inventory management processes, such as replenishment and stock optimization, using case studies to illustrate real-world success.

Time 17m

Lectures 3

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Automating Replenishment with AI

0:05:37

AI for Stock Optimization

0:05:39

Case Studies of AI in Inventory Management

0:06:06

Section 7

Practical AI Solutions for Demand Forecasting and Inventory Management

This section provides step-by-step guides for implementing AI solutions in demand forecasting and inventory management, helping participants evaluate AI tools and navigate the technical aspects of deployment.

Time 17m

Lectures 3

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Evaluating AI Tools and Providers

0:05:31

Step-by-Step Guide to Implementing AI for Demand Forecasting

0:07:52

Step-by-Step Guide to Implementing AI for Inventory Management

0:03:47

Section 8

Implementation and Ethics

This final section focuses on the limitations and ethical considerations of AI implementation, addressing the challenges businesses face and the importance of responsible AI use in supply chain management.

Time 27m

Lectures 5

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Understanding the Limitations of AI in Demand Forecasting and Inventory Management