Chevron Left
Back to Python for Data Science, AI & Development

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

4.6
stars
39,078 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

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.

DR

Sep 27, 2024

This course was really helpful in make me understand all the topics of Python from scratch, including the slightly advanced topics, of APIs, for my level as a freshman just getting settled in college.

Filter by:

6176 - 6200 of 6,979 Reviews for Python for Data Science, AI & Development

By Michel M

Sep 3, 2019

Course content is good, however the Watson Studio partsare dominated by the platform complexity instead of the content and the guides/screenshots are outdated.

By Julia T

May 4, 2019

Some good content and good explanations in the videos, but the final project is really unclear and focuses more about using IBM software than coding in Python.

By Jiayao P

Jan 30, 2019

For this course, I think it is good in general, because it covers some fundamentals regarding python, however, it needs more practice questions in my opinion.

By WATTIEZ N

Sep 14, 2022

It's more a course about development, data manipulation and a bit of webscrapping/API. If you already some notion in data science, you will not learn a lot

By Michael L

Oct 12, 2020

It would have been beneficial to be learn more about building a dashboard visualization. That part of the quiz/test that I had trouble with for some reason.

By Mohamed A

Nov 9, 2022

You could have made this course longer, for example separate week for pandas and numpy, and web scrapping

Also, there should have been a week for matplotlib.

By Ytzen v d W

Jun 9, 2019

Fairly good course, but a terrible assignment. This assignment was not testing what we learned but added all sorts of fairly irrelevant different issues.

By Aaron M M

May 6, 2019

Some of the instruction at the end of the course was not very helpful and there were some errors with information or links. Overall it is a good course.

By Ashish R

Aug 15, 2021

The last part of the course seemed a bit hurried. Not enough practice exercises on "pandas" and "numpy" libraries. A bit disappointed with the course.

By Нестеров С

Dec 6, 2020

Дается очень мало информации, только общее представление о необходимом программном обеспечении. Нет серьезных заданий для самостоятельного выполнения.

By Pamela R

Jan 30, 2020

I wish there had been alittle more assistance when I needed it, some things are implied, and therefore can take longer if not explained appropriately

By Salman A Q

Sep 19, 2022

Labs need to be improved. There should be excercises for students to complete by themselves and more explanation in the videos on difficult topics.

By Eric A

Apr 23, 2021

Thorough for the time period. However, some knowledge was inferred when doing the labs instead of building on top of knowledge taught in the lessons

By Bernie M

Jun 3, 2020

Good course but very superficial, in order to truly create skills to find a job more projects may be needed per course to truly master the concepts.

By 丁灵君

Apr 10, 2019

A fast paced course. Good in some ways. But I feel the course is missing a lot details. And there are waaaaaaaaaay to much typos for a coding course

By Kai K

Sep 3, 2019

class is not that much challenging

but it's okay maybe this is for beginner

but IBM lab tutorial needs some effort to let user use it in daily work

By Alisson d S B

Jul 23, 2019

I hoped to have learnt a bunch more stuff on programming in python.

It was a nice start though. Full with some nice and practical tips and methods.

By Fayçal A

Sep 4, 2022

The hands on projects are too easy. They need to be a little more creative. They also don't go deep in the details of a new function/library ...

By Saqib H

Feb 3, 2022

Advice to someone newly learning phython "Start from somewhere else!" even tho course is good but it's also too small in terms of explaination.

By Enabor O

May 11, 2021

Most of the projects on IBM cloud had errors working with them. Overall, course was a good introduction to Python for Data Science application.

By ahmed j

Sep 29, 2019

Trés bon cours en terme de comprehension, parcontrel es exercices Quiz sont parfois banal, je propose qu'on y ajoute un peu plus de complexité.

By Abby M

Sep 17, 2018

Decent intro to python programming. The videos and labs need additional proofing. The labs need some off script activities in the later labs.

By Esosa G A

May 6, 2020

It's an okay course, but it can be better

And I wouldn't advice it for total beginners cause they skip steps and sometimes write wrong syntaxes

By Alok R S

Dec 24, 2018

There's no fun in doing assignment in lab as almost all of the coding is done by them only , although we can learn lots of syntax and tricks .