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Learner Reviews & Feedback for Python for Data Science, AI & Development by IBM

4.6
stars
35,197 ratings

About the Course

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher. This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs. You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python. This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles....

Top reviews

MA

May 16, 2020

The syllabus of the course takes you in a roller-coaster ride.

From basic level to advance level and you won't feel any trouble nor hesitate a bit.

It's easy, it's vast, and it's really usefull.

TM

Nov 17, 2019

it becomes easier wand clearer when one gets to complete the assignments as to how to utilize what has been learned. Practical work is a great way to learn, which was a fundamental part of the course.

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By Ağgül İ

Oct 17, 2023

good

By Sanjay .

Oct 10, 2023

good

By Muhammad J

Sep 23, 2023

Best

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Aug 22, 2023

Good

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May 21, 2023

good

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Apr 24, 2023

GOOD

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Apr 20, 2023

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Apr 18, 2023

good

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Dec 7, 2022

good

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Nov 20, 2022

nice

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Nov 15, 2022

good

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Nov 7, 2022

nice

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Sep 3, 2022

GOOD

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Aug 22, 2022

very

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Aug 14, 2022

Good

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Aug 13, 2022

good

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Jul 28, 2022

good

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Jul 27, 2022

GOOD

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Jul 20, 2022

nice

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Jul 5, 2022

G00D

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Jul 1, 2022

cool

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Jun 30, 2022

good

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Jun 16, 2022

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May 20, 2022

Good

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Apr 26, 2022

Good