Fundamentals of Machine Learning for Supply Chain
- Offered byCoursera
Fundamentals of Machine Learning for Supply Chain at Coursera Overview
Duration | 13 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
Fundamentals of Machine Learning for Supply Chain at Coursera Highlights
- Reset deadlines in accordance to your schedule.
- Earn a Certificate upon completion
- Start instantly and learn at your own schedule.
- Course 1 of 4 in the Machine Learning for Supply Chains Specialization.
Fundamentals of Machine Learning for Supply Chain at Coursera Course details
- 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.
Fundamentals of Machine Learning for Supply Chain at Coursera Curriculum
Introduction to Programming Concepts and Python Practices
Welcome to the Course!
Why Python? Why Jupyter? Why ML?
Setting Up the Environment
Module Introduction
Python and Jupyter Notebook Basics
Lists
Dictionaries
Loops
Functions
Libraries and Modules
Linear Programming with Pulp (I)
Linear Programming with Pulp (II)
Jupyter Notebook Basics
Python Docs: Data Structures
Keyword Arguments
Top 10 Python Libraries for Data Science
What is PuLP?
Data Structures Practice Quiz
Using Data Structures with Pulp
Introduction to Python
Digging Into Data: Common Tools for Data Science
Module Introduction
Introduction to Pandas and Numpy (A Tale of Two Matrices)
Deep Dive into Numpy (Part I)
Deep Dive Into Numpy (Part II)
Deep Dive Into Numpy (III)
Introduction to Pandas
Indexing in Pandas (I)
Indexing in Pandas (II)
Pandas Deep Dive
Numpy Quickstart
Inputing Missing Data
10 min to Pandas
Numpy Basics
Pandas
Numpy and Pandas Quiz
Higher Level Data Wrangling and Manipulation
Module Introduction
Groupby, apply
Groupby, apply, transform
Beyond Basic Groupby
Groupby Rolling
Split-Apply-Combine
Iterating a Dataframe
List Comprehensions
Practice Quiz: Combining Data
Course 1 Final Project
Math of Linear Programming I (Optional)
Math of Linear Programming II (Optional)
Linear Programming
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