Will I earn university credit for completing the Specialization?

No this is not a university course.

What will I be able to do upon completing the Specialization?

You will be able to use statistical models and machine learning to analyze retail stock and predict future sales as well as how many items to stock.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Machine Learning for Supply Chains 专项课程

Use Machine Learning in the Supply Chain. You will learn to use machine language techniques to analyze and predict retail stock in the supply chain.

位教师：Neelesh Tiruviluamala

3,758 人已注册

包含在 Coursera Plus 中

了解更多

4 门课程系列

深入学习学科知识

3.7

（66 条评论）

中级等级

推荐体验

4 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

4 门课程系列

深入学习学科知识

3.7

（66 条评论）

中级等级

推荐体验

4 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

This specialization is intended for students who wish to use machine language to analyze and predict product usage and other similar tasks. There is no specific prerequisite but some general knowledge of supply chain will be helpful, as well as general statistics and calculus.

应用的学习项目

You will learn and practice skills as you go through each of the courses, using the Coursera lab environment. The final course is a capstone project where you will analyze data and make predictions about retail product usage, and then calculate optimal safety stock storage.

要了解的详细信息

可分享的证书

添加到您的领英档案

授课语言：英语（English）

了解顶级公司的员工如何掌握热门技能

了解关于 Coursera for Business 的更多信息

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

精进特定领域的专业知识

向大学和行业专家学习热门技能
借助实践项目精通一门科目或一个工具
培养对关键概念的深入理解
通过 LearnQuest 获得职业证书

专业化 - 4门课程系列

应用的学习项目

Fundamentals of Machine Learning for Supply Chain

第 1 门课程13小时

您将学到什么

Learn to merge, clean, and manipulate data using Python libraries such as Numpy and Pandas
Gain familiarity with the basic and advaned Python functonalities such as importing and using modules, list compreohensions, and lambda functions.
Solve a supply chain cost optimization problem using Linear Programming with Pulp

您将获得的技能

类别：Python Programming

类别：Data Structures

类别：NumPy

类别：Data Manipulation

类别：Data Analysis

类别：Programming Principles

类别：Pandas (Python Package)

类别：Data Transformation

类别：Data Cleansing

类别：Data Wrangling

类别：Plot (Graphics)

类别：Supply Chain

类别：Computer Programming

类别：Operations Research

类别：Data Science

类别：Applied Machine Learning

类别：Exploratory Data Analysis

Demand Forecasting Using Time Series

第 2 门课程9小时

您将学到什么

Building ARIMA models in Python to make demand predictions
Developing the framework for more advanced neural netowrks (such as LSTMs) by understanding autocorrelation and autoregressive models.

您将获得的技能

类别：Time Series Analysis and Forecasting

类别：Correlation Analysis

类别：Trend Analysis

类别：Regression Analysis

类别：Forecasting

类别：Customer Demand Planning

类别：Exploratory Data Analysis

类别：Applied Machine Learning

类别：Predictive Modeling

类别：Pandas (Python Package)

类别：Data Visualization

类别：Matplotlib

类别：Supply Chain Management

类别：Machine Learning

类别：Demand Planning

类别：Plot (Graphics)

类别：Python Programming

类别：Predictive Analytics

类别：Statistical Modeling

类别：Data Analysis

Advanced AI Techniques for the Supply Chain

第 3 门课程22小时

您将学到什么

In this course, we’ll learn about more advanced machine learning methods that are used to tackle problems in the supply chain. We’ll start with an overview of the different ML paradigms (regression/classification) and where the latest models fit into these breakdowns. Then, we’ll dive deeper into some of the specific techniques and use cases such as using neural networks to predict product demand and random forests to classify products. An important part to using these models is understanding their assumptions and required preprocessing steps. We’ll end with a project incorporating advanced techniques with an image classification problem to find faulty products coming out of a machine.

您将获得的技能

类别：Artificial Intelligence and Machine Learning (AI/ML)

类别：Computer Vision

类别：Artificial Neural Networks

类别：Machine Learning Methods

类别：Image Analysis

类别：Machine Learning Algorithms

类别：Anomaly Detection

类别：Demand Planning

类别：Applied Machine Learning

类别：Deep Learning

类别：Customer Demand Planning

类别：Classification And Regression Tree (CART)

类别：Supervised Learning

类别：Supply Chain Management

类别：Natural Language Processing

类别：Statistical Modeling

类别：Random Forest Algorithm

类别：Supply Chain

类别：Machine Learning

类别：Predictive Modeling

Capstone Project: Predicting Safety Stock

第 4 门课程10小时

您将学到什么

Calcualte safety stock using SARIMA predictions combined with manipulaitng lead times.

您将获得的技能

类别：Time Series Analysis and Forecasting

类别：Predictive Analytics

类别：Predictive Modeling

类别：Pandas (Python Package)

类别：Exploratory Data Analysis

类别：Data Visualization

类别：Machine Learning

类别：Data Wrangling

类别：Statistical Modeling

类别：Inventory Management

类别：Data Manipulation

类别：Inventory Management System

类别：Demand Planning

类别：Data Analysis

类别：Feature Engineering

类别：Data Transformation

类别：Forecasting

类别：Matplotlib

类别：Inventory Control

获得职业证书

将此证书添加到您的 LinkedIn 个人资料、简历或履历中。在社交媒体和绩效考核中分享。

位教师

Neelesh Tiruviluamala

LearnQuest

8 门课程19,333 名学生

提供方

LearnQuest

人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

自 2018开始学习的学生

''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情，我就可以学习。'

Jennifer J.

自 2020开始学习的学生

''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'

Larry W.

自 2021开始学习的学生

''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'

Chaitanya A.

''学习不仅仅是在工作中做的更好：它远不止于此。Coursera 让我无限制地学习。'

通过 Coursera Plus 开启新生涯

无限制访问 10,000+ 世界一流的课程、实践项目和就业就绪证书课程 - 所有这些都包含在您的订阅中

了解更多

通过在线学位推动您的职业生涯

获取世界一流大学的学位 - 100% 在线

探索学位

加入超过 3400 家选择 Coursera for Business 的全球公司

提升员工的技能，使其在数字经济中脱颖而出

了解更多

常见问题

To complete all four courses, you will spend 3-5 hours per week for 13 weeks.

Machine learning is mathematical. There are no specific background requirements, but knowledge of algebra and calculus will be helpful, as well as a general understanding of supply chain concepts.

Yes, the courses build knowledge as they progress so we recommend taking them in order.