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Learner Reviews & Feedback for Data Analysis with Python by IBM

4.7
stars
19,363 ratings

About the Course

Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You’ll learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you’ll gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement....

Top reviews

RP

Apr 19, 2019

perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.

AB

Feb 12, 2020

Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.

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By Nat N

Sep 10, 2023

The Data Analysis with Python course is a decent intro into data handling, cleaning and some basic model building. I would say however that without prior Python or data analysis experience, it is probably quite a steep learning curve. I am from a science background with a bit of advanced maths knowledge, and the Model evaluation part got a little bit crazy even for me, I'll probably have to revisit it a few times. But you also can't expect to do a course like this and have a complete grasp of everything guaranteed, still have to be willing to do your own further reading/research outside of it, just like you would for uni. Some of the notebooks contained errors or the answers were spelled out which was a bit disappointing. My last project was graded immediately which was great, and I made sure to grade a couple extra to help other learners. Over all a great intro into some trickier topics, I enjoyed it.

By Armagaan

Feb 23, 2019

I had to remove 1 star just because of the fact that a project is not included in this one. Yes, you do have labs but there you are forced to write code in way so that you don't encounter problems later in the notebook.

In a project or an assignment work, you have to play with variables and confusions and errors out of wonderland show up which lead to greater clarification.

The course in itself is great and undoubtedly good in functioning as a prerequisite for Machine Learning and surely I'd recommend it to anyone who asks for an opinion. The explanations are good and much easier to understand along with the visual demonstrations.

I'd advise that after learning anything during this course, look for some database online and play with it yourself(I didn't but had to regret cuz I'd forget the code again and again).

OVERALL : GO AHEAD, it's worth it