Home AI Courses Fundamentals of ML for Supply Chain

Fundamentals of ML for Supply Chain

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Using Python, participants will analyze supply chain datasets, resolve optimization issues, and cultivate transferable data analysis abilities.

Key AI Functions:data science,numpy,pandas,linear programming (lp),supply chain

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Description for Fundamentals of ML for Supply Chain

Data Manipulation with Python: Teach yourself how to merge, sanitize, and manipulate datasets with Python libraries like Numpy and Pandas.
Advanced Python Functionalities: Become proficient in the application of lambda functions, the utilization of list comprehensions, and the importation of modules to facilitate efficient programming.
Exploratory Data Analysis (EDA): Create Pythonic skills and best practices for analyzing complex supply chain datasets, with techniques that are applicable to other disciplines.
Optimization of the Supply Chain: Utilize Linear Programming and the Pulp library to resolve a supply chain cost optimization issue.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 21

Offered by: On Coursera provided by LearnQuest

Duration: 3 weeks at 4 hours a week

Schedule: Flexible

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