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Comentários e feedback de alunos de Statistics for Data Science with Python da instituição IBM

4.6
estrelas
158 classificações
35 avaliações

Sobre o curso

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....

Melhores avaliações

HD
13 de Jan de 2021

A well structured course, simple and direct to the point, with a little of exercising you'll come out with a huge understanding of the statistical concepts.

ED
19 de Nov de 2020

Excellent course to help clear doubts for the level of statistics needed for data science. It a great experience. well done IBM!

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1 — 25 de 38 Avaliações para o Statistics for Data Science with Python

por Vũ V H

28 de Mai de 2021

At first, I find this course to be somewhat challenging at first since I don't have any prior knowledge in statistic, but after a few lecture and some self study later, I have gain a pretty good understanding of statistics and its application in Data Science.

I especially like the final assignment as it give me a feel for what being a Data Scientist is like. It also make me go through all of the previous lab for reference. By doing so, I have a chance to review the things I have learnt and get a deeper understanding of the material. I can't speak for everyone but if you are completely new to statistic like me and planning to break into Data Science field, I think this course might be a good starting point for you.

por cynthia e

16 de Nov de 2020

I enjoyed taking this course and found it was well explained. Having been out of school for a long time and not using stats in my daily job, I found that I had to listen to the videos over and over again to fully understand the concepts introduced. I also struggled initially with python as it was a new concept for me. I recommend it for others, take it slowly and try to revisit the videos and readings and ensure you follow and thoroughly complete the lab exercises as this will help with the project.

por Ofure E

3 de Nov de 2020

This course was seamlessly easy to understand and follow. During my undergraduate studies, I struggled with statistics which made me a bit worried taking the course.

I am glad I pushed passed my fear and took the course , as it has sparked my interest to learn statistics, how it applies to data and making business decisions.

Thanks Aije and Murtaza - I look forward to taking more courses from you both on here.

por Zara U

9 de Nov de 2020

I really enjoyed taking this course. It was really easy to follow and I absolutely loved how the course was put together. I will recommend anyone looking to use Python for Data Science to take this course.

por Nabilla A

9 de Nov de 2020

Amazing course . Very easy to follow . Definitely improved on my python skills . Would 100% recommend .

por Alfred K S

29 de Dez de 2020

Challenging for non statiticians

por Brandon B

17 de Jan de 2021

The videos, readings, and labs were not sufficient for me to feel prepared for the assessments. I ended up using outside resources just to understand what was being presented here. There was really no explanation of why you would use certain tools or the underlying statistics principles; the course assumes a lot of the learner (both in statistics and Python) considering it's aimed at beginners. I believe this is a newer course, so hopefully it will continue to be revised, but I was disappointed in the content compared to other IBM courses I've taken through Coursera.

por Ebenezer D

20 de Nov de 2020

Excellent course to help clear doubts for the level of statistics needed for data science. It a great experience. well done IBM!

por Robert S

6 de Abr de 2021

The videos, readings, and labs were not sufficient for me to feel prepared for the assessments. I ended up using outside resources just to understand what was being presented here.

por Jason C

12 de Set de 2021

E​njoyed course the most from teh IBM Data Science Modules! Being less technical, it was easier to understand with minimal knowledge on the subject and the excersixes and final project were very practical and helpful in understanding

por Marcelo d C

1 de Dez de 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!

por Joao L

20 de Jan de 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.

por Hichem D

14 de Jan de 2021

A well structured course, simple and direct to the point, with a little of exercising you'll come out with a huge understanding of the statistical concepts.

por Yodefia R

27 de Jul de 2021

Great introduction to basic statistics for data science. Python specialization suits those with no experience in the language.

por Muhammad F H

2 de Set de 2021

A worth-to-try course if you are curious about implementing some statistical tests in Python.

por k b

7 de Fev de 2021

Excellent course with a step by step explanation and complete final assignment.

por Asif Y

13 de Jan de 2021

One of the best course I have taken online. Way of teaching was outstanding.

por Khusan T

30 de Mar de 2021

Understandable and easy to grasp the basics of statistical analysis

por Vaseekaran V

13 de Mai de 2021

A good introduction to those who want a brief taste of statistics

por Sunny .

1 de Abr de 2021

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

por 佐藤淳一

29 de Jan de 2021

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

por vijay k A

23 de Jun de 2021

the course is more useful and cover basic concepts

por Akhas R

20 de Mar de 2021

Extraordinary. Very interesting.

por Htet A L T

16 de Jul de 2021

Thank You IBM

por André J A

22 de Jul de 2021

ok