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Fundamentals of Machine Learning for Supply Chain
  • Level Foundation
  • المدة 13 ساعات hours
  • الطبع بواسطة LearnQuest
  • Offered by

عن

This course will teach you how to leverage the power of Python to understand complicated supply chain datasets. Even if you are not familiar with supply chain fundamentals, the rich data sets that we will use as a canvas will help orient you with several Pythonic tools and best practices for exploratory data analysis (EDA). As such, though all datasets are geared towards supply chain minded professionals, the lessons are easily generalizable to other use cases.

الوحدات

Welcome to the Course

    • 3 Videos
    • 1 Discussion
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1 Discussions

  • Welcome to the Course!

3 Videos

  • Welcome to the Course!
  • Why Python? Why Jupyter? Why ML?
  • Setting Up the Environment

Python Programming

    • 2 Videos
    • 1 Readings
    • 1 Lab
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1 Labs

  • The Playground

2 Videos

  • Module Introduction
  • Python and Jupyter Notebook Basics

1 Readings

  • Jupyter Notebook Basics

Data Structures for Data Science

    • 2 Videos
    • 1 Readings
    • 2 Lab
    • 2 Programming
    • 1 Assignment
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2 Programming

  • Lists
  • Dictionaries

1 Assignment

  • Data Structures Practice Quiz

2 Labs

  • Programming Assignment Solutions
  • Programming Assignment Solutions

2 Videos

  • Lists
  • Dictionaries

1 Readings

  • Python Docs: Data Structures

Loops and Functions

    • 2 Videos
    • 1 Readings
    • 2 Lab
    • 2 Programming
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2 Programming

  • Loops
  • Functions

2 Labs

  • Programming Assignment Solutions
  • Programming Assignment Solutions

2 Videos

  • Loops
  • Functions

1 Readings

  • Keyword Arguments

Libraries and Modules

    • 1 Videos
    • 1 Readings
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1 Videos

  • Libraries and Modules

1 Readings

  • Top 10 Python Libraries for Data Science

Linear Programming with Pulp

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Using Data Structures with Pulp

2 Videos

  • Linear Programming with Pulp (I)
  • Linear Programming with Pulp (II)

1 Readings

  • What is PuLP?

Introduction to Python Quiz

    • 1 Assignment
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1 Assignment

  • Introduction to Python

Introduction to Pandas and Numpy (A Tale of Two Matrices)

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Numpy Basics

2 Videos

  • Module Introduction
  • Introduction to Pandas and Numpy (A Tale of Two Matrices)

1 Readings

  • Numpy Quickstart

Deep Dive into Numpy

    • 3 Videos
    • 1 Discussion
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1 Discussions

  • Case Studies with Numpy

3 Videos

  • Deep Dive into Numpy (Part I)
  • Deep Dive Into Numpy (Part II)
  • Deep Dive Into Numpy (III)

Introduction to Pandas

    • 3 Videos
    • 1 Readings
    • 1 Lab
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1 Labs

  • Indexing DataFrames

3 Videos

  • Introduction to Pandas
  • Indexing in Pandas (I)
  • Indexing in Pandas (II)

1 Readings

  • Inputing Missing Data

Deep Dive into Pandas

    • 1 Videos
    • 1 Readings
    • 1 Lab
    • 1 Programming
    • 1 Assignment
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1 Programming

  • Pandas Timeseries Prediction and Plotting (Optional)

1 Assignment

  • Pandas

1 Labs

  • Programming Assignment Solutions

1 Videos

  • Pandas Deep Dive

1 Readings

  • 10 min to Pandas

Numpy and Pandas Quiz

    • 1 Assignment
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1 Assignment

  • Numpy and Pandas Quiz

Groupby, apply, transform

    • 3 Videos
    • 1 Readings
    • 1 Discussion
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1 Discussions

  • Using Groupby, apply, transform

3 Videos

  • Module Introduction
  • Groupby, apply
  • Groupby, apply, transform

1 Readings

  • Split-Apply-Combine

Beyond Basic Groupby

    • 2 Videos
    • 1 Lab
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1 Labs

  • Groupby and Sorting

2 Videos

  • Beyond Basic Groupby
  • Groupby Rolling

Combining Datasets and Reshaping Data

    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Combining Data

2 Readings

  • Iterating a Dataframe
  • List Comprehensions

Pandas Lab

    • 1 Lab
    • 1 Programming
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1 Programming

  • Finding Outliers

1 Labs

  • Programming Assignment Solutions

Math of Linear Programming

    • 2 Videos
    • 1 Assignment
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1 Assignment

  • Linear Programming

2 Videos

  • Math of Linear Programming I (Optional)
  • Math of Linear Programming II (Optional)

Course 1 Project: Filling Demand while Optimizing Cost

    • 1 Lab
    • 1 Programming
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1 Programming

  • Course 1 Project: Filling Demand while Optimizing Cost

1 Labs

  • Programming Assignment Solutions

Auto Summary

"Fundamentals of Machine Learning for Supply Chain" focuses on leveraging Python for complex supply chain datasets, offering foundational insights into Big Data and Analytics. Taught by Coursera, this 780-minute course emphasizes exploratory data analysis (EDA) with practical, generalizable lessons. Available through Starter and Professional subscriptions, it targets supply chain professionals and data enthusiasts alike.

Rajvir Dua
Instructors

Rajvir Dua

Neelesh Tiruviluamala
Instructors

Neelesh Tiruviluamala