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

4.6
stars
38,831 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

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.

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.

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4501 - 4525 of 6,937 Reviews for Python for Data Science, AI & Development

By Farrux B

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Jan 26, 2024

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By Viswanathan R

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May 18, 2023

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May 13, 2023

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Nov 17, 2022

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Aug 9, 2022

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Jun 27, 2022

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Nov 2, 2020

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Jul 30, 2020

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By Antonio C

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Dec 28, 2019

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Jun 10, 2019

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Apr 20, 2019

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By Sam

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Nov 21, 2024

The structure is excellent, with videos, readings, and quizzes. The labs are a great way to practice the material learned in the videos and readings. Additionally, the breadth of content is great. I feel like it covers a great amount of Python to get started on your first projects. That said, there are a lot of errors in the material and the labs. I reported most as I came across them, but it can be frustrating when something is explained incorrectly or you are given contradictory information. There are many grammatical mistakes in the lab explanations, as well. The mistakes do not ruin the course, as most of the information is phenomenal, and a lot of detail is packed in. However, it significantly hurts the experience and makes the process frustrating. This is on top of the frustration of labs including code that is not explained. There are some functions used in the sample code, and keywords used, that are not explained in comments or the lab preamble. Maybe the idea was not to overexplain, but I found this is very frustrating when it happened. All that said, this course is still worth 4 stars. It's a lot of information with a lot of resources given. I'm glad I took the course (although with the caveat that it was free since I completed it during the 7-day free Coursera Plus trial).

By Gargi M

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Aug 17, 2020

Thank you for giving the opportunity to learn Python.

As for my review of this course, I suggest proofreading the labs before publishing them because they have many spelling errors. Since one of the recommended qualities of a Data Scientist is to be detailed oriented, it would be better for all the English and non-English speaking students to have instruction without errors. This will set a good role model for them to be more aware of their work.

Additionally, it would help students who have no prior knowledge of Python to be given some context before starting the labs. There are some labs that expect more than what is explained in the videos.

In regards to creating an object in Watson Studio, I highly recommend including Alex Aklson's video in the curriculum. Screenshots that are provided for the labs are helpful, however, the video is more comprehensive, and the step-by-step process eliminates confusion. Please devote more time to the subject of Numpy as it seems to be a vast subject and needs more instruction and examples.

Overall, this was an informative course that had an enormous amount of material to cover. Thank you once again and continue teaching thousands of students like me around the world.

By Lena G

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Nov 15, 2022

I thoroughly enjoyed this course. It skims the surface of basic Python you need for Data Analysis, which is exactly what I was looking for. You get a general understanding of basic Python elements, syntax, useful libraries and some examples of really simple data analysis.

The main disadvantage of this course is a couple of exercises at the end of hands-on labs that do not correspond to the course material by their level of difficulty. To me, as a person with zero programming background, it felt like I've just been explained addition on examples like 2+3 and then asked to add something like exponential numbers and square roots. Judging by the discussion forums, I am not the only one who felt this way, which was the only thing to keep me from thinking that I am too dumb for this and giving up. I believe those tasks are great as extra challenges but must be marked accordingly.

The other odd thing is that really useful info specifically for Data Analysis process is contained in optional videos and labs, so I advise future learners to draw attention to them despite their being non-compulsory to finish this course.

Thanks to all the course authors and moderators.

By Rui Z

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May 24, 2019

The course itself was fine, and the project was helpful. I’m thankful to IBM to come out with this course. But the Watson Studio part could be very frustrating. It is not really relevant to Python study, but you will have to use the Studio for your final project. I found he Studio to have very complex layouts, very hard to nevigate, a lack of guidance on the studio itself. I was to give 3 stars as my final project experience was so ruined by the Watson Studio, I definitely spent way more hours on figuring out Watson Studio than the Python part of the studio, and not feel it’s helpful to know Watson Studio as I probably will not use it in the future. But my reasonableness and fairness side told me, the very end of an experience in general puts more weight on one’s overall experience on something, so a bad ending of it could potentially make me to give a biased opinion, towards the down side, to the experience. So trying to overcome that bias, and being appreciate for IBM to put this course together and Coursera to offer it, I gave 4 stars.

By Khailendra P

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Apr 13, 2023

The Coursera course on Python for Data Science, AI & Development is an exceptional resource for anyone who wants to learn Python programming and its applications in data science and artificial intelligence. The course starts with the basics of Python programming and gradually progresses to advanced topics such as data manipulation, visualization, and machine learning. One of the key strengths of the course is its practical approach, with numerous hands-on exercises and projects that allow learners to apply what they have learned in real-world scenarios. The instructors are knowledgeable and engaging, and the course is well-structured and easy to follow, with clear explanations and examples. Additionally, the course provides a supportive learning environment, with a dedicated discussion forum where learners can ask questions and get help from instructors and other learners. Overall, I would highly recommend this course to anyone who wants to improve their Python programming skills and learn its applications in data science and AI.