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Learner Reviews & Feedback for Python Essentials for MLOps by Duke University

4.2
stars
122 ratings

About the Course

Python Essentials for MLOps (Machine Learning Operations) is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow. By the end of the course, learners will have the necessary skills to write Python scripts for automating common MLOps tasks. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their Python skills....

Top reviews

RK

Jan 9, 2024

Amazing, if you have some python basics, but even if you don´t it gives a great overview. Well done :)

AM

Sep 12, 2023

It is very good for those getting into the field of MLOps

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26 - 28 of 28 Reviews for Python Essentials for MLOps

By marco m y p

Oct 4, 2023

This course provides a good overview of toolset and techniques involved for building machine learning applications. I enjoyed the most, when several methods where presented for the same goal. It is up to the engineer to decide for the approach that works best for him.

By Stefan P

Mar 2, 2024

For a specialisation that is marked as "Advanced Level" and a course named "Python Essentials for MLOps" where the accent is on MLOps this course is an embarrassment. The content starts with explaining the most basic things you can imagine in Python - variables, if/else conditions, etc. I assume that anyone who knows what MLOps is, knows how to declare Python variables and how to write for loops. I expected some advanced level tutorials but got just an advertisement for the course instructors' books, and a series of videos that just don't seem connected to each other, and really, look like they are re-used from somewhere else. I regret paying the subscription.

By Javed S

Jan 12, 2024

Absolute waste of time. HEADACHE.