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Voltar para Data Science Math Skills

Comentários e feedback de alunos de Data Science Math Skills da instituição Universidade Duke

4.5
2,130 classificações
477 avaliações

Sobre o curso

Data science courses contain math—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 Bayes’ 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!...

Melhores avaliações

AS

Jan 12, 2019

Effective way to refresh and add the Data Science math skills! Thanks a lot! At the time of the study some of the quizzes content were not rendering correctly on mobile devices (both iPad and Android)

PS

Jul 23, 2017

This is neat little course to revise math fundamentals. I generally find learning probability a little tricky. This course helped me a lot in better understanding Bayes Theorem. Thank you professors.

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176 — 200 de {totalReviews} Avaliações para o Data Science Math Skills

por Venkat N

Oct 04, 2017

Excellent Course. Must-do course for beginners in data science. Great instructors

por Florent C

Aug 09, 2017

Great course to refresh memory about mathematics. Pace and quizzes well balanced.

por Gaurav P

Mar 07, 2018

Looking forward to advanced courses on Linear algebra, eculidean geometry that would make the concepts of vectors, matrices, plane and any application of those in the data science problems.

por Georgia P

Jun 03, 2018

Thank you!

por Subramanian N

Aug 20, 2017

This was an excellent review of the basic mathematical concepts useful in data science and machine learning. Thank you very much for the very concise and clear explanations of the various topics! Much appreciated!

por Mys

Jun 04, 2017

it was a great course for me having left maths for a while and needing it again now

por Nilanjan D

Jul 09, 2017

A great introduction to the basic Mathematics skill needed to start Data Science Career. A must course for does not have the mathematics background required for Data Science.

por Jackie C

Apr 07, 2017

First three weeks were mostly review, but the fourth week was incredibly helpful. Would appreciate some more background/derivation of the binomial theorem - it was hard for me to develop an intuition for it in the same way I could for the Bayesian theorem.

por Toan T L

Jun 26, 2018

Great course. Help me to refresh my knowledge on basic maths which is necessary for my following study plan.

por Hosameldeen S

Jun 12, 2017

To the Point!

por Ahsan B

Jul 26, 2017

Impressive way to explain basic concept. Really a good refresher.

por Yuliya S

Apr 07, 2018

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por Insan N

Oct 30, 2017

Nice

por Carlos M B B

Sep 20, 2017

It was a great oppotunity to get involved in math skills.

por Leonardo A

Jun 20, 2017

Very good course, can't wait for the more advance classes.

por vivek m

Feb 05, 2017

Basic math course help to get revise all the high school concept. Even those who haven't any background on mathematics can get it easily.

por Miriam C

Jul 24, 2017

cannot believe I took a programming course without doing this - the math was taking me so long and it was because I hadn't finished high school math a decade ago (our school didn't require it) - really thankful to have found this course!

por Glenn L

May 23, 2017

Great Primer for Data Science Math!

por Ned T

Sep 11, 2017

This is a very interesting course for those who have not used math for many years and now want to pursue the field of data science. The basic concepts are presented coherently and understandably attracted me throughout the course.

por mehak

Nov 12, 2017

can i get the certificate ?

por William W d F

Oct 10, 2017

Excelent course! I am studying at the Data Science Math Skills to fill some math gaps, and also doing the Data Scientist Toolbox . All of them are really great courses. Enjoy!

por Josué R G S M

Jan 04, 2018

Los contenidos son en inglés pero los profesores tienen una perfecta dicción y no hablan rápido de tal modo que los puedes entender perfectamente con sólo un poco de inglés. Los contenidos matemáticos están debidamente dosificados y muy interesantes. Recomiendo el curso

por Kehinde O

Aug 24, 2017

This is a great course for anyone who has little or no experience with elementary algebra and for those who might have forgotten.

por Thomas J H

Aug 22, 2017

Helpful course -- highly recommended for people who need more background or who need a refresher.

por Ankur A

Apr 18, 2018

Hi. A very good refresher course that serves as a pre-requisite to Machine Learning and Data Science courses. Probability could have been a little better explained, specially the processes and event part. I would also like to see Vectors and Matrices added to this course, which is equally vital for Data Science.