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Learner Reviews & Feedback for Practical Python for AI Coding 2 by Korea Advanced Institute of Science and Technology(KAIST)

4.7
stars
17 ratings

About the Course

Introduction video : https://youtu.be/TRhwIHvehR0 This course is for a complete novice of Python coding, so no prior knowledge or experience in software coding is required. This course selects, introduces and explains Python syntaxes, functions and libraries that were frequently used in AI coding. In addition, this course introduces vital syntaxes, and functions often used in AI coding and explains the complementary relationship among NumPy, Pandas and TensorFlow, so this course is helpful for even seasoned python users. This course starts with building an AI coding environment without failures on learners’ desktop or notebook computers to enable them to start AI modeling and coding with Scikit-learn, TensorFlow and Keras upon completing this course. Because learners have an AI coding environment on their computers after taking this course, they can start AI coding and do not need to join or use the cloud-based services....

Top reviews

MG

Apr 1, 2022

A nice syllabus of Python course. And the quizs are nice to enjoy.

Thank you professor and Coursera community.

HM

Jan 22, 2024

I would recommend this course to any programming beginner, not only for python

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1 - 5 of 5 Reviews for Practical Python for AI Coding 2

By Martin P

•

Jul 31, 2023

Professor Kwon's course is one of the best introductions to Python you will find. I especially how this all comes together so well in week 5. Plus, in my opinion, giving recent advances in the field of AI, I don't think there is another Python course that is more relvant at this point.

By MARU G G

•

Apr 2, 2022

A nice syllabus of Python course. And the quizs are nice to enjoy.

Thank you professor and Coursera community.

By Hope M

•

Jan 22, 2024

I would recommend this course to any programming beginner, not only for python

By Youjong K

•

Jun 30, 2022

The content is easy to follow from the scratch, and the content is very essential for data engineering. If there is a basic explanation and example for object oriented programming, it will be better.

By Piotr J

•

Mar 12, 2024

lack of exercises at the end of lessons/modules lowers the score. You get a lot of information about methods in libraries and you're expected to memorize them.