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## Opiniones y comentarios de aprendices correspondientes a Data Science Math Skills por parte de Universidad Duke

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## Acerca del Curso

Data science courses contain mathâ€”no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time. Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material. Topics include: ~Set theory, including Venn diagrams ~Properties of the real number line ~Interval notation and algebra with inequalities ~Uses for summation and Sigma notation ~Math on the Cartesian (x,y) plane, slope and distance formulas ~Graphing and describing functions and their inverses on the x-y plane, ~The concept of instantaneous rate of change and tangent lines to a curve ~Exponents, logarithms, and the natural log function. ~Probability theory, including Bayesâ€™ theorem. While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel." Good luck and we hope you enjoy the course!...

## Principales reseÃ±as

VS

22 de sep. de 2020

This course syllabus is great. It starts wonderfully. Week 1 to 4 is taught by Paul Bendich, and Daniel Egger the instruction is awesome. Effective way to refresh and add the Data Science math skills!

RS

5 de may. de 2020

This was mostly review for me though probability especially Beyes Theorem derivation was new. The instructors provided clear often refreshing ways to look at material.

Thank you for a great class!!

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## 151 - 175 de 2,418 revisiones para Data Science Math Skills

por Marios P

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6 de nov. de 2020

Effective way to refresh and add the Data Science math skills! The course overall was great. It was well taught-- very relevant and clear for the most part. Thanks a lot! I think I am better prepared for data science afterward!

por JDiego G

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25 de jun. de 2020

Pretty fun and understandable. The last week resources and content was quite deep and confusing when it was explained. From the exercises I've found some errors in the solutions. Briefly, It fulfills my expectations pleasantly.

por Shar M G

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7 de oct. de 2020

Extra grateful for the refresher on essential math topics needed for data science. Week 1-2 is such a great way to review pre-calculus concepts. Week 3-4 modules were extremely helpful for those in need of Stat refreshers.

por J P K

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13 de oct. de 2020

Good Course for Beginners, with lot of insights, and its entirely basic ,anyone without any prior knowledge can do the best with this kind of course;And I thank Coursera as well as the Instructor for offering this course.

por Deleted A

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1 de ago. de 2020

Well, except for the last quiz of probability (basic and intermediate) others were too easy, and also this course is highly recommended for the ones who really are entirely new to math concepts present in this course.

por Eduardo C

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27 de abr. de 2021

buen curso para recordar y aprender los conceptos que se ven en estadÃ­stica bÃ¡sica, y algunos temas que en su momento se vieron de manera muy extensa y ahora se ven de manera resumida y aplicada , de manera resumida.

por Alice

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6 de sep. de 2020

It was delightful. I think this was a great introductory course. I still had to go on for more learning material for the harder topics, but the structure of the course really provided the backbone on what to learn.

por Aldrich W

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13 de jul. de 2020

Maybe the first three chapters are a little bit easy; but the fourth chapter is challenging. This is my very first Coursera course, and I have learned a lot. Shout out to Prof. Daniel Egger and Prof. Paul Bendich!

por Alex A

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13 de jun. de 2020

I was looking for a math class to refresh my math skills in preparation for getting into the field of Data Science and I am very glad that I found this course. It was well taught and very clear. Thank you so much.

por Sree B

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12 de may. de 2021

This course really gives me the very good understanding about the basic concepts which are necessary in the field of Data Science. A must try course for all beginner level who are keen in learning Data science.

por Suparit S

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19 de jul. de 2020

The course provides comprehensive basic math skills for the ones who might have forgotten all the maths they have learnt. Highly recommended for ones who wants to restart the math skills with clear intuition!

por Yasir M

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13 de jul. de 2020

It was a good basic level course of math design by Duke University.I just say thanks to all of this course team and especially thanks to coursera for providing such a amazing opportunity to learn more skills.

por Hemali V

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13 de sep. de 2020

It is an amazing course for everyone who want to learn Maths. after learning this basic math skill, i am capable to perform basic algorithms for Machine Learning.

It is very helpful course for me, Thank you!

por John M

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21 de sep. de 2021

Excellent refresher on somewhat basic mathematical concepts, starting with assumption of zero knowledge and preparing the student to tackle higher level courses in probability, statistics, and data science.

por Miguel b

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23 de dic. de 2021

Great Course! Review of introductory concepts, getting a little more challenging towards the las weeks. It was worth and it should not be scary. The intructors of the course are superb and easy to follow.

por Eloisa J R M

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8 de jul. de 2020

If you have previous background is easier, but in Baye's theorem it was a little hard to understand it. Overall, it is an excellent course, but a little more explanations in Baye's theorem could be better.

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26 de jun. de 2020

The course was really great. You could include some more offline practice questions with solutions for better practice at least 10 for each topic. Otherwise explanations were easy to understand and follow.

por Thomas G

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5 de mar. de 2022

Very good instructors, good technical quality the presentation. The refresh of basic math concepts is helpful und the brief introduction to Bayesian statistics is one if the better that I've seen.

por Guido T G

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17 de nov. de 2020

If you want to review and engage knowledge this course its a good reason for start the apllication of maths. The course have for you a good material and very good questions for real deep learning

por Weicheng(Will) H

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12 de ago. de 2020

For the part of Bayes' theorem, I think the explanation is no clear or through enough. Maybe more break-down is necessary. And the other parts are really good. I really enjoy taking this course.

por Nikisha E

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3 de ene. de 2021

I want to thank my educators for this wonderful job that they are doing.i have learn so much from you guys and i want to thank you all for your kind support in this data science maths skills.

por Abu I M S A

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18 de oct. de 2020

This is a great course, many things are basic but I have learned those a long day ago. Some explanations are from different perspective than conventional. However, definitely a great course.

por veer

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21 de jul. de 2020

A great foundation course for anybody whoose tryna find their feet in the excitng and vast world of data science,i learnt so many new things..it was truly an enriching experience.Thank you!!

por Altynay O

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7 de jul. de 2020

My first course on Data Science and was happy to share this experience with Duke University. The course was informational, very resourceful and hopefully beneficial for my future endeavors.

por Kensuke I

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30 de abr. de 2020

Good learning overall.

Some part are pretty easy, which I remember learning in junior high,

but some theorems are hard to apply.

Now I want to use these theory in real world and data science!