LearnQuest
Advanced AI Techniques for the Supply Chain
LearnQuest

Advanced AI Techniques for the Supply Chain

This course is part of Machine Learning for Supply Chains Specialization

Taught in English

Rajvir Dua
Neelesh Tiruviluamala

Instructors: Rajvir Dua

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

22 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

22 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Machine Learning for Supply Chains Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

In this module, we'll learn about the use cases of machine learning in the supply chain. We'll start with the big picture applications before diving deeper into specific algorithms, including neural networks. Throughout the module, we'll explain not only the general artificial intelligence concepts and mathematics, but also how these algorithms can specifically be used for the supply chain.

What's included

4 videos4 readings2 quizzes1 discussion prompt1 ungraded lab

In this module, we'll cover the concepts relating to the ML paradigm. We'll start by learning how to pick a model, relying on considerations such as managing the bias-variance tradeoff. Next, we'll explore how machine learning models converge, including the use of stochastic gradient descent to minimize loss functions. Finally, we'll end with some practical considerations on coding advanced AI models with libraries for hyperparamter tuning.

What's included

3 videos4 readings1 quiz1 programming assignment3 ungraded labs

In this module, we'll expand beyond numbers and learn how to use machine learning on images and text. We'll start by talking about how to analyze text data and cover the primary methods behind natural language processing. Then, we'll learn how to analyze images by constructing convolutional neural networks complete with convolutions and pooling layers.

What's included

5 videos5 readings1 quiz1 discussion prompt2 ungraded labs

In this final project, we’ll apply what we learned in the last module to classify images of products based on whether there is a defect or not.

What's included

1 programming assignment1 ungraded lab

Instructors

Rajvir Dua
LearnQuest
8 Courses12,452 learners

Offered by

LearnQuest

Recommended if you're interested in Machine Learning

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