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Learner Reviews & Feedback for Introduction to Data Analytics by IBM

4.8
stars
14,704 ratings

About the Course

Ready to start a career in Data Analysis but don’t know where to begin? This course presents you with a gentle introduction to Data Analysis, the role of a Data Analyst, and the tools used in this job. You will learn about the skills and responsibilities of a data analyst and hear from several data experts sharing their tips & advice to start a career. This course will help you to differentiate between the roles of Data Analysts, Data Scientists, and Data Engineers. You will familiarize yourself with the data ecosystem, alongside Databases, Data Warehouses, Data Marts, Data Lakes and Data Pipelines. Continue this exciting journey and discover Big Data platforms such as Hadoop, Hive, and Spark. By the end of this course you’ll be able to understand the fundamentals of the data analysis process including gathering, cleaning, analyzing and sharing data and communicating your insights with the use of visualizations and dashboard tools. This all comes together in the final project where it will test your knowledge of the course material, and provide a real-world scenario of data analysis tasks. This course does not require any prior data analysis, spreadsheet, or computer science experience....

Top reviews

MS

May 3, 2023

A very structured course to give basic and useful insight to the world of data analysis. From zero, one absorbs the possible levels of details and requirements to get into the world of data analysis.

BS

Oct 21, 2020

A great Introductory course by IBM and Coursera to start your career in Data analytics. Learned a lot from this course like what are the skills that are needed in order to become a good data analyst.

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2926 - 2950 of 3,073 Reviews for Introduction to Data Analytics

By Ali E H

Nov 28, 2023

good

By RAHUL K

Oct 4, 2023

good

By Chinni K K

Aug 15, 2023

Good

By Ramit M

Aug 3, 2023

good

By Muhamad A A M N

May 28, 2023

good

By NITHISH V (

Apr 26, 2023

GOOG

By Prashamsa K 2

Feb 2, 2023

GOOD

By Fleku G J J

Jan 6, 2023

good

By Oyepitan T G

Dec 5, 2022

good

By Giorgio

Dec 4, 2022

good

By Sudani R A

Dec 4, 2022

good

By Farah F M S

Nov 16, 2022

good

By VISHNUDEV J

Oct 24, 2022

nil

By Rani S

Sep 6, 2022

Good

By Fatima H A

Jun 24, 2022

good

By Suhail B j

May 17, 2022

شكرا

By Fonkwe A

May 11, 2022

Good

By MANAR N m

Sep 24, 2021

good

By Mattia F

Feb 2, 2021

Nice

By KHOR H J

Oct 30, 2021

ok

By Preksha S

Oct 13, 2020

.

By Matthew K

May 31, 2021

I believe that my initial submission of my final assignment was graded by a person who had a low level of English proficiency. COURSERA NEEDS TO INSTITUTE LANGUAGE PROFICIENCY Standards for students, whether it's for a course taught in English, Hindi, Japanese, Arabic, or any other language. The students should meet reasonable standards of language proficiency for the language the course is presented in.

I suspect this because I SAW A LOT OF VERY POOR EXAMPLES OF ENGLISH USAGE IN THE FORUMS of THIS COURSE. I also saw this in the final assignments of other students. If I am correct about that, that is unfair to everyone taking the course, as this course is presented ENTIRELY in English. I am GLAD that this course is available to students around the world, but they should have to demonstrate proficiency in the language in which the course is given.

If I were taking a course presented in Hindi (or ANY OTHER LANGUAGE OTHER THAN ENGLISH) and I wasn't proficient in Hindi, then how could I be expected to comprehend and accurately grade the work of a student who writes in higher-level Hindi than I could comprehend? It would be gravely unfair to that student if my poor comprehension of the language resulted in him getting a low grade.

The other possibility is that my original submission was simply graded by a lazy person who didn't want to take the time to read one of my lengthy answers. This is also not fair. Don't do this to your peers. This is serious. It's a graded course.

By Jackie S

May 26, 2023

I strongly advise anyone using Coursera to ALWAYS double-check your peer-reviewed finals. Both peer-reviewed finals I have completed, on the first round of "peer-review" have been incorrectly graded. The only reason I know this is because I double-checked my grades and peer reviews. BOTH TIMES, the initial "peer-reviewer" has incorrectly graded my final, and the only recourse I could take is to re-submit my final, not knowing if the next :peer-reviewer" would actually grade correctly, according to the rubric. Just saying, double check your final grades, and fight for the grade you know you deserve.

By H.

Jul 18, 2021

Very general overview for people early on in their career who are looking to gain conceptual knowledge of the field. Has very little actual information on producing visuals. Also there is no way to mark the course as complete if you are auditing, which is not fair. I thought the purchase option was to have a certificate to walk away with, not to hold you hostage after taking the entire course that you can't mark as complete.

By Sebastian R M

Apr 2, 2024

Para ser un curso introductorio está bien, abarca el grán abanico de temas iniciales para el análisis de datos. Sin embargo, el bombardeo conceptual parece a veces innecesario y los ejemplos prácticos para el tema estadísitico insuficientes. En vez de listas interminables de tipos de elementos de datos, falta más ilustración de esos conceptos en el análisis real y práctico. Incluir laboratorios no estaría de más.