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

4.6
stars
41,238 ratings

About the Course

Kickstart your Python journey with this beginner-friendly, self-paced course taught by an expert. Python is one of the most popular programming languages, and the demand for individuals with Python skills continues to grow. This course takes you from zero to programming in Python in a matter of hours—no prior programming experience is necessary! You’ll begin with Python basics, including data types, expressions, variables, and string operations. You will explore essential data structures such as lists, tuples, dictionaries, and sets, learning how to create, access, and manipulate them. Next, you will delve into logic concepts like conditions and branching, learning how to use loops and functions, along with important programming principles like exception handling and object-oriented programming. As you progress, you will gain practical experience reading from and writing to files and working with common file formats. You’ll also use powerful Python libraries like NumPy and Pandas for data manipulation and analysis. The course also covers APIs and web scraping, teaching you how to interact with REST APIs using libraries like requests and extract data from websites using BeautifulSoup. 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 individuals interested in pursuing careers in Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps and a variety of other technology-related roles....

Top reviews

DR

Sep 28, 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.

EH

Jun 11, 2021

It is a very valuable course that I have learned for the Python skillset. It contains some advanced methods. It helps me to build more confidence in using Python and understand the concept in general.

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226 - 250 of 7,414 Reviews for Python for Data Science, AI & Development

By James H

•

Apr 20, 2020

Excellent course presented well and labs were good hands-on way to learn... Could have done without the Numpy sections tho... Once it started talking about adding/calculating vectors without explaining what they were, i had to skip over it... But rest of class was great

By Vedant P

•

Mar 3, 2022

The quizzes could have been a little tough. Also, the course could have contained writing few programs, and also output like questions should have contained some complex and bigger codes..Quizzes were very very basic. Otherwise, course was fantastic.. Thank you so much

By Taimoor Y

•

Jul 18, 2023

The Reason im giving it 4 stars is that they tried to teach basic python in very short period of time and with less explanation.

Im suggesting everyone should take "Python for everybody" OR "Python 3 programming" by University Of Michigan as prerequisite.

By John C

•

May 29, 2019

I like the project, practical orientation of the course compared to more academic approaches. The slides on

usage of the Watson Studio features and sharing could be improved. Spent more time messing with that than the programming. Seemed excessive

By Jennifer E

•

May 31, 2019

The cloud storage question on the final is just a ploy to get us to use IBM products and shouldn't be part of the grade. The course was a good pace and nice, slow introduction for new Python users.

By Matthew N

•

May 23, 2019

Everything for this was great, up to the last part of the project. The instructions to load to the IBM cloud were some of the most confusing and overtly difficult exercises.

By Thanh C D

•

May 31, 2019

I was going to give it a 5, however, there are some mistakes and inconsistencies in the powerpoint slides. But overall, great courses, and I'm so glad I decided to take it.

By Tram V

•

Apr 4, 2021

W4 and W5 syllabus is too much to comprehend for non-computer science people. Me personally find it difficult to link previous lessons with the next ones

By Tianhan L

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May 12, 2019

I don't like the system for the final project. It took me a long time to figure out things not directly related to python.

By ashirwad s

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May 14, 2019

A few more hands-on for using IBM Watson studio efficiently would have been helpful. Still it was an amazing course.

By Milan

•

May 28, 2025

Es un muy buen curso, te va guiando de lo basico de python hasta en la recopilación de datos en la web.

By Gaurav D

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Jun 21, 2019

The videos are good. The level of assignments can be improved.They are quite easy and straight forward.

By Vivian R

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May 25, 2019

The IBM section at the end is depending on the cloud services that sometimes have connectivity issues.

By Steven S

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May 27, 2019

The final assignment needs some editing. The instructions were vague and grammar needs some work.

By pooja s

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Apr 2, 2021

Python basics are taught well but at the end sessions got too hard all of a sudden.

By Mariana N

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Aug 31, 2021

Gives insight into the language of Python, but not much application practice.

By Anushil G

•

Jun 5, 2019

well structured courses and assignments the quizzes could be more challenging

By Flint C

•

May 3, 2023

some parts were simple with difficult assignments following immediately

By ANIRUDDHA B

•

May 21, 2019

Peer to Peer assignment was confusing and misleading.

By Ahmad K

•

Jul 15, 2024

it covers the essential basics for data science

By Sharath S

•

Nov 11, 2020

Explanations too cumbersome around APIs

By Vikash R

•

Feb 27, 2021

This course was of intermediate level.

By Hima K

•

Sep 18, 2023

Good

By Aman C

•

Feb 19, 2023

mmm

By Peter S

•

Feb 15, 2025

I think the introduction is excellent, but suddenly in Module 5 it becomes complex very quickly and is a bit less refined. For instance, in the initial sections it has many graphics showing how things work both in the labs and the videos, but later when doing web scraping the labs and docs are expecting you to remember and visualize everything in your head. Also the labs themselves are not so refined. - I was having issues and using AI found 3+ bugs in the example code directly from the labs. I put the comment in the Discussion Board and essentially got the answer "you are right" without the confirmation "we will update the code". - Some of the code snippets in the labs execute but give you no output or feedback. Like the Scrappy example. I ran code and it executed - now what? What am I to learn or get from it? The course is good, but the Module 5, which is probably the most important/useful could really use to have more depth and explanation. I hope someone in Coursera / IBM can take this feedback as constructive and enhance a bit!