Fundamentals of Machine Learning for Supply Chain

This course is part of Machine Learning for Supply Chains Specialization

Instructors: Rajvir Dua +1 more

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What you'll learn

  •   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

    • Skills you'll gain

  •   Supply Chain
  •   Exploratory Data Analysis
  •   Programming Principles
  •   Data Analysis
  •   Pandas (Python Package)
  •   Data Structures
  •   Data Manipulation
  •   Data Wrangling
  •   Operations Research
  •   Data Transformation
  •   Computer Programming
  •   Applied Machine Learning
  •   Data Cleansing
  •   Plot (Graphics)
  •   Python Programming
  •   NumPy

    • There are 4 modules in this course

    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.

    Digging Into Data: Common Tools for Data Science

    Higher Level Data Wrangling and Manipulation

    Course 1 Final Project

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