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Learner Reviews & Feedback for Statistics for Data Science with Python by IBM

4.5

stars

415 ratings

About the Course

This Statistics for Data Science course is designed to introduce you to the basic principles of statistical methods and procedures used for data analysis. After completing this course you will have practical knowledge of crucial topics in statistics including - data gathering, summarizing data using descriptive statistics, displaying and visualizing data, examining relationships between variables, probability distributions, expected values, hypothesis testing, introduction to ANOVA (analysis of variance), regression and correlation analysis. You will take a hands-on approach to statistical analysis using Python and Jupyter Notebooks – the tools of choice for Data Scientists and Data Analysts. At the end of the course, you will complete a project to apply various concepts in the course to a Data Science problem involving a real-life inspired scenario and demonstrate an understanding of the foundational statistical thinking and reasoning. The focus is on developing a clear understanding of the different approaches for different data types, developing an intuitive understanding, making appropriate assessments of the proposed methods, using Python to analyze our data, and interpreting the output accurately. This course is suitable for a variety of professionals and students intending to start their journey in data and statistics-driven roles such as Data Scientists, Data Analysts, Business Analysts, Statisticians, and Researchers. It does not require any computer science or statistics background. We strongly recommend taking the Python for Data Science course before starting this course to get familiar with the Python programming language, Jupyter notebooks, and libraries. An optional refresher on Python is also provided. After completing this course, a learner will be able to: ✔Calculate and apply measures of central tendency and measures of dispersion to grouped and ungrouped data. ✔Summarize, present, and visualize data in a way that is clear, concise, and provides a practical insight for non-statisticians needing the results. ✔Identify appropriate hypothesis tests to use for common data sets. ✔Conduct hypothesis tests, correlation tests, and regression analysis. ✔Demonstrate proficiency in statistical analysis using Python and Jupyter Notebooks....

Top reviews

Nov 30, 2021

Excellent Course! Clear and didactical explanations, objectives exercices and very oriented subjects! For those who are interested in data analytics, this the trainning you should take!

Jan 19, 2021

The final assignment is very well designed, I was able to review the entire course material and consolidate the learning. I have now a good understanding of hypothesis testing.

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51 - 75 of 98 Reviews for Statistics for Data Science with Python

By Sunny .

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Apr 1, 2021

Excellent Course...Would be great if add few more examples

By MohamadReza H

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Jan 20, 2024

this course is completely useful for statistic and python

By Christan J G

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Oct 20, 2023

I learned a lot in this course specially in Lab activity.

By 佐藤淳一

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Jan 29, 2021

It easy to understand. Not too difficult. Not too easy.

By Kajal L

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May 18, 2023

It was very informational and interesting, Thank you!!

By vijay k A

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Jun 23, 2021

the course is more useful and cover basic concepts

By Shanuka D

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May 29, 2024

One of the best courses I've enrolled In so far

By JUAN R P G

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Jun 19, 2023

Just Great!

Excellent course. I learned a lot.

By Mohammad_Anas

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Apr 18, 2023

Amazing course in the journey of data science

By Олена Щ

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Apr 20, 2023

Interesting course with real project

By Ankit G

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Apr 15, 2022

Well Explained with guided project.

By Akhas R

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Mar 20, 2021

Extraordinary. Very interesting.

By Ume K

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Oct 29, 2022

very informative and helpful

By Ashraful I S

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Mar 15, 2022

AMAZING EXPERIENCES WITH IBM

By JiSeub L

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Feb 28, 2024

easy to understand.

By ALEXANDRE R P

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Mar 17, 2022

Outstanding course!

By Irshad A k

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Sep 28, 2023

Very useful course

By Htet A L T

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Jul 16, 2021

Thank You IBM

By Ekofiongo E

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Aug 25, 2023

Super cours

By Samuel I R J

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Mar 18, 2024

TODO BIEN

By Raúl O M

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Mar 12, 2024

excelente

By Александр Ф

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Nov 1, 2023

all good

By Miguel A T J

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Dec 21, 2024

Great!

By Aloisius G N

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Jan 4, 2023

good

By Usama G

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Jun 13, 2022

Good